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Sample records for rapidly growing segment

  1. Incorporating Edge Information into Best Merge Region-Growing Segmentation

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    Tilton, James C.; Pasolli, Edoardo

    2014-01-01

    We have previously developed a best merge region-growing approach that integrates nonadjacent region object aggregation with the neighboring region merge process usually employed in region growing segmentation approaches. This approach has been named HSeg, because it provides a hierarchical set of image segmentation results. Up to this point, HSeg considered only global region feature information in the region growing decision process. We present here three new versions of HSeg that include local edge information into the region growing decision process at different levels of rigor. We then compare the effectiveness and processing times of these new versions HSeg with each other and with the original version of HSeg.

  2. Segmentation of Extrapulmonary Tuberculosis Infection Using Modified Automatic Seeded Region Growing

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    Nordin Abdul

    2009-01-01

    Full Text Available Abstract In the image segmentation process of positron emission tomography combined with computed tomography (PET/CT imaging, previous works used information in CT only for segmenting the image without utilizing the information that can be provided by PET. This paper proposes to utilize the hot spot values in PET to guide the segmentation in CT, in automatic image segmentation using seeded region growing (SRG technique. This automatic segmentation routine can be used as part of automatic diagnostic tools. In addition to the original initial seed selection using hot spot values in PET, this paper also introduces a new SRG growing criterion, the sliding windows. Fourteen images of patients having extrapulmonary tuberculosis have been examined using the above-mentioned method. To evaluate the performance of the modified SRG, three fidelity criteria are measured: percentage of under-segmentation area, percentage of over-segmentation area, and average time consumption. In terms of the under-segmentation percentage, SRG with average of the region growing criterion shows the least error percentage (51.85%. Meanwhile, SRG with local averaging and variance yielded the best results (2.67% for the over-segmentation percentage. In terms of the time complexity, the modified SRG with local averaging and variance growing criterion shows the best performance with 5.273 s average execution time. The results indicate that the proposed methods yield fairly good performance in terms of the over- and under-segmentation area. The results also demonstrated that the hot spot values in PET can be used to guide the automatic segmentation in CT image.

  3. SAR Imagery Segmentation by Statistical Region Growing and Hierarchical Merging

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    Ushizima, Daniela Mayumi; Carvalho, E.A.; Medeiros, F.N.S.; Martins, C.I.O.; Marques, R.C.P.; Oliveira, I.N.S.

    2010-05-22

    This paper presents an approach to accomplish synthetic aperture radar (SAR) image segmentation, which are corrupted by speckle noise. Some ordinary segmentation techniques may require speckle filtering previously. Our approach performs radar image segmentation using the original noisy pixels as input data, eliminating preprocessing steps, an advantage over most of the current methods. The algorithm comprises a statistical region growing procedure combined with hierarchical region merging to extract regions of interest from SAR images. The region growing step over-segments the input image to enable region aggregation by employing a combination of the Kolmogorov-Smirnov (KS) test with a hierarchical stepwise optimization (HSWO) algorithm for the process coordination. We have tested and assessed the proposed technique on artificially speckled image and real SAR data containing different types of targets.

  4. Topological leakage detection and freeze-and-grow propagation for improved CT-based airway segmentation

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    Nadeem, Syed Ahmed; Hoffman, Eric A.; Sieren, Jered P.; Saha, Punam K.

    2018-03-01

    Numerous large multi-center studies are incorporating the use of computed tomography (CT)-based characterization of the lung parenchyma and bronchial tree to understand chronic obstructive pulmonary disease status and progression. To the best of our knowledge, there are no fully automated airway tree segmentation methods, free of the need for user review. A failure in even a fraction of segmentation results necessitates manual revision of all segmentation masks which is laborious considering the thousands of image data sets evaluated in large studies. In this paper, we present a novel CT-based airway tree segmentation algorithm using topological leakage detection and freeze-and-grow propagation. The method is fully automated requiring no manual inputs or post-segmentation editing. It uses simple intensity-based connectivity and a freeze-and-grow propagation algorithm to iteratively grow the airway tree starting from an initial seed inside the trachea. It begins with a conservative parameter and then, gradually shifts toward more generous parameter values. The method was applied on chest CT scans of fifteen subjects at total lung capacity. Airway segmentation results were qualitatively assessed and performed comparably to established airway segmentation method with no major visual leakages.

  5. Liver Segmentation Based on Snakes Model and Improved GrowCut Algorithm in Abdominal CT Image

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    Huiyan Jiang

    2013-01-01

    Full Text Available A novel method based on Snakes Model and GrowCut algorithm is proposed to segment liver region in abdominal CT images. First, according to the traditional GrowCut method, a pretreatment process using K-means algorithm is conducted to reduce the running time. Then, the segmentation result of our improved GrowCut approach is used as an initial contour for the future precise segmentation based on Snakes model. At last, several experiments are carried out to demonstrate the performance of our proposed approach and some comparisons are conducted between the traditional GrowCut algorithm. Experimental results show that the improved approach not only has a better robustness and precision but also is more efficient than the traditional GrowCut method.

  6. CAMSHIFT IMPROVEMENT WITH MEAN-SHIFT SEGMENTATION, REGION GROWING, AND SURF METHOD

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    Ferdinan Ferdinan

    2013-10-01

    Full Text Available CAMSHIFT algorithm has been widely used in object tracking. CAMSHIFT utilizescolor features as the model object. Thus, original CAMSHIFT may fail when the object color issimilar with the background color. In this study, we propose CAMSHIFT tracker combined withmean-shift segmentation, region growing, and SURF in order to improve the tracking accuracy.The mean-shift segmentation and region growing are applied in object localization phase to extractthe important parts of the object. Hue-distance, saturation, and value are used to calculate theBhattacharyya distance to judge whether the tracked object is lost. Once the object is judged lost,SURF is used to find the lost object, and CAMSHIFT can retrack the object. The Object trackingsystem is built with OpenCV. Some measurements of accuracy have done using frame-basedmetrics. We use datasets BoBoT (Bonn Benchmark on Tracking to measure accuracy of thesystem. The results demonstrate that CAMSHIFT combined with mean-shift segmentation, regiongrowing, and SURF method has higher accuracy than the previous methods.

  7. Nucleus and cytoplasm segmentation in microscopic images using K-means clustering and region growing.

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    Sarrafzadeh, Omid; Dehnavi, Alireza Mehri

    2015-01-01

    Segmentation of leukocytes acts as the foundation for all automated image-based hematological disease recognition systems. Most of the time, hematologists are interested in evaluation of white blood cells only. Digital image processing techniques can help them in their analysis and diagnosis. The main objective of this paper is to detect leukocytes from a blood smear microscopic image and segment them into their two dominant elements, nucleus and cytoplasm. The segmentation is conducted using two stages of applying K-means clustering. First, the nuclei are segmented using K-means clustering. Then, a proposed method based on region growing is applied to separate the connected nuclei. Next, the nuclei are subtracted from the original image. Finally, the cytoplasm is segmented using the second stage of K-means clustering. The results indicate that the proposed method is able to extract the nucleus and cytoplasm regions accurately and works well even though there is no significant contrast between the components in the image. In this paper, a method based on K-means clustering and region growing is proposed in order to detect leukocytes from a blood smear microscopic image and segment its components, the nucleus and the cytoplasm. As region growing step of the algorithm relies on the information of edges, it will not able to separate the connected nuclei more accurately in poor edges and it requires at least a weak edge to exist between the nuclei. The nucleus and cytoplasm segments of a leukocyte can be used for feature extraction and classification which leads to automated leukemia detection.

  8. Segmentation of Large Unstructured Point Clouds Using Octree-Based Region Growing and Conditional Random Fields

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    Bassier, M.; Bonduel, M.; Van Genechten, B.; Vergauwen, M.

    2017-11-01

    Point cloud segmentation is a crucial step in scene understanding and interpretation. The goal is to decompose the initial data into sets of workable clusters with similar properties. Additionally, it is a key aspect in the automated procedure from point cloud data to BIM. Current approaches typically only segment a single type of primitive such as planes or cylinders. Also, current algorithms suffer from oversegmenting the data and are often sensor or scene dependent. In this work, a method is presented to automatically segment large unstructured point clouds of buildings. More specifically, the segmentation is formulated as a graph optimisation problem. First, the data is oversegmented with a greedy octree-based region growing method. The growing is conditioned on the segmentation of planes as well as smooth surfaces. Next, the candidate clusters are represented by a Conditional Random Field after which the most likely configuration of candidate clusters is computed given a set of local and contextual features. The experiments prove that the used method is a fast and reliable framework for unstructured point cloud segmentation. Processing speeds up to 40,000 points per second are recorded for the region growing. Additionally, the recall and precision of the graph clustering is approximately 80%. Overall, nearly 22% of oversegmentation is reduced by clustering the data. These clusters will be classified and used as a basis for the reconstruction of BIM models.

  9. Global left ventricular function in cardiac CT. Evaluation of an automated 3D region-growing segmentation algorithm

    International Nuclear Information System (INIS)

    Muehlenbruch, Georg; Das, Marco; Hohl, Christian; Wildberger, Joachim E.; Guenther, Rolf W.; Mahnken, Andreas H.; Rinck, Daniel; Flohr, Thomas G.; Koos, Ralf; Knackstedt, Christian

    2006-01-01

    The purpose was to evaluate a new semi-automated 3D region-growing segmentation algorithm for functional analysis of the left ventricle in multislice CT (MSCT) of the heart. Twenty patients underwent contrast-enhanced MSCT of the heart (collimation 16 x 0.75 mm; 120 kV; 550 mAseff). Multiphase image reconstructions with 1-mm axial slices and 8-mm short-axis slices were performed. Left ventricular volume measurements (end-diastolic volume, end-systolic volume, ejection fraction and stroke volume) from manually drawn endocardial contours in the short axis slices were compared to semi-automated region-growing segmentation of the left ventricle from the 1-mm axial slices. The post-processing-time for both methods was recorded. Applying the new region-growing algorithm in 13/20 patients (65%), proper segmentation of the left ventricle was feasible. In these patients, the signal-to-noise ratio was higher than in the remaining patients (3.2±1.0 vs. 2.6±0.6). Volume measurements of both segmentation algorithms showed an excellent correlation (all P≤0.0001); the limits of agreement for the ejection fraction were 2.3±8.3 ml. In the patients with proper segmentation the mean post-processing time using the region-growing algorithm was diminished by 44.2%. On the basis of a good contrast-enhanced data set, a left ventricular volume analysis using the new semi-automated region-growing segmentation algorithm is technically feasible, accurate and more time-effective. (orig.)

  10. Integrating multiscale polar active contours and region growing for microcalcifications segmentation in mammography

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    Arikidis, N S; Karahaliou, A; Skiadopoulos, S; Panagiotakis, G; Costaridou, L; Likaki, E

    2009-01-01

    Morphology of individual microcalcifications is an important clinical factor in microcalcification clusters diagnosis. Accurate segmentation remains a difficult task due to microcalcifications small size, low contrast, fuzzy nature and low distinguishability from surrounding tissue. A novel application of active rays (polar transformed active contours) on B-spline wavelet representation is employed, to provide initial estimates of microcalcification boundary. Then, a region growing method is used with pixel aggregation constrained by the microcalcification boundary estimates, to obtain the final microcalcification boundary. The method was tested on dataset of 49 microcalcification clusters (30 benign, 19 malignant), originating from the DDSM database. An observer study was conducted to evaluate segmentation accuracy of the proposed method, on a 5-point rating scale (from 5:excellent to 1:very poor). The average accuracy rating was 3.98±0.81 when multiscale active rays were combined to region growing and 2.93±0.92 when combined to linear polynomial fitting, while the difference in rating of segmentation accuracy was statistically significant (p < 0.05).

  11. Automated Segmentation of Coronary Arteries Based on Statistical Region Growing and Heuristic Decision Method

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    Yun Tian

    2016-01-01

    Full Text Available The segmentation of coronary arteries is a vital process that helps cardiovascular radiologists detect and quantify stenosis. In this paper, we propose a fully automated coronary artery segmentation from cardiac data volume. The method is built on a statistics region growing together with a heuristic decision. First, the heart region is extracted using a multi-atlas-based approach. Second, the vessel structures are enhanced via a 3D multiscale line filter. Next, seed points are detected automatically through a threshold preprocessing and a subsequent morphological operation. Based on the set of detected seed points, a statistics-based region growing is applied. Finally, results are obtained by setting conservative parameters. A heuristic decision method is then used to obtain the desired result automatically because parameters in region growing vary in different patients, and the segmentation requires full automation. The experiments are carried out on a dataset that includes eight-patient multivendor cardiac computed tomography angiography (CTA volume data. The DICE similarity index, mean distance, and Hausdorff distance metrics are employed to compare the proposed algorithm with two state-of-the-art methods. Experimental results indicate that the proposed algorithm is capable of performing complete, robust, and accurate extraction of coronary arteries.

  12. Automatic segmentation of MRI head images by 3-D region growing method which utilizes edge information

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    Jiang, Hao; Suzuki, Hidetomo; Toriwaki, Jun-ichiro

    1991-01-01

    This paper presents a 3-D segmentation method that automatically extracts soft tissue from multi-sliced MRI head images. MRI produces a sequence of two-dimensional (2-D) images which contains three-dimensional (3-D) information of organs. To utilize such information we need effective algorithms to treat 3-D digital images and to extract organs and tissues of interest. We developed a method to extract the brain from MRI images which uses a region growing procedure and integrates information of uniformity of gray levels and information of the presence of edge segments in the local area around the pixel of interest. First we generate a kernel region which is a part of brain tissue by simple thresholding. Then we grow the region by means of a region growing algorithm under the control of 3-D edge existence to obtain the region of the brain. Our method is rather simple because it uses basic 3-D image processing techniques like spatial difference. It is robust for variation of gray levels inside a tissue since it also refers to the edge information in the process of region growing. Therefore, the method is flexible enough to be applicable to the segmentation of other images including soft tissues which have complicated shapes and fluctuation in gray levels. (author)

  13. Video Segmentation Using Fast Marching and Region Growing Algorithms

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    Eftychis Sifakis

    2002-04-01

    Full Text Available The algorithm presented in this paper is comprised of three main stages: (1 classification of the image sequence and, in the case of a moving camera, parametric motion estimation, (2 change detection having as reference a fixed frame, an appropriately selected frame or a displaced frame, and (3 object localization using local colour features. The image sequence classification is based on statistical tests on the frame difference. The change detection module uses a two-label fast marching algorithm. Finally, the object localization uses a region growing algorithm based on the colour similarity. Video object segmentation results are shown using the COST 211 data set.

  14. A two-stage rule-constrained seedless region growing approach for mandibular body segmentation in MRI.

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    Ji, Dong Xu; Foong, Kelvin Weng Chiong; Ong, Sim Heng

    2013-09-01

    Extraction of the mandible from 3D volumetric images is frequently required for surgical planning and evaluation. Image segmentation from MRI is more complex than CT due to lower bony signal-to-noise. An automated method to extract the human mandible body shape from magnetic resonance (MR) images of the head was developed and tested. Anonymous MR images data sets of the head from 12 subjects were subjected to a two-stage rule-constrained region growing approach to derive the shape of the body of the human mandible. An initial thresholding technique was applied followed by a 3D seedless region growing algorithm to detect a large portion of the trabecular bone (TB) regions of the mandible. This stage is followed with a rule-constrained 2D segmentation of each MR axial slice to merge the remaining portions of the TB regions with lower intensity levels. The two-stage approach was replicated to detect the cortical bone (CB) regions of the mandibular body. The TB and CB regions detected from the preceding steps were merged and subjected to a series of morphological processes for completion of the mandibular body region definition. Comparisons of the accuracy of segmentation between the two-stage approach, conventional region growing method, 3D level set method, and manual segmentation were made with Jaccard index, Dice index, and mean surface distance (MSD). The mean accuracy of the proposed method is [Formula: see text] for Jaccard index, [Formula: see text] for Dice index, and [Formula: see text] mm for MSD. The mean accuracy of CRG is [Formula: see text] for Jaccard index, [Formula: see text] for Dice index, and [Formula: see text] mm for MSD. The mean accuracy of the 3D level set method is [Formula: see text] for Jaccard index, [Formula: see text] for Dice index, and [Formula: see text] mm for MSD. The proposed method shows improvement in accuracy over CRG and 3D level set. Accurate segmentation of the body of the human mandible from MR images is achieved with the

  15. Nosocomial rapidly growing mycobacterial infections following laparoscopic surgery: CT imaging findings.

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    Volpato, Richard; de Castro, Claudio Campi; Hadad, David Jamil; da Silva Souza Ribeiro, Flavya; Filho, Ezequiel Leal; Marcal, Leonardo P

    2015-09-01

    To identify the distribution and frequency of computed tomography (CT) findings in patients with nosocomial rapidly growing mycobacterial (RGM) infection after laparoscopic surgery. A descriptive retrospective study in patients with RGM infection after laparoscopic surgery who underwent CT imaging prior to initiation of therapy. The images were analyzed by two radiologists in consensus, who evaluated the skin/subcutaneous tissues, the abdominal wall, and intraperitoneal region separately. The patterns of involvement were tabulated as: densification, collections, nodules (≥1.0 cm), small nodules (<1.0 cm), pseudocavitated nodules, and small pseudocavitated nodules. Twenty-six patients met the established criteria. The subcutaneous findings were: densification (88.5%), small nodules (61.5%), small pseudocavitated nodules (23.1 %), nodules (38.5%), pseudocavitated nodules (15.4%), and collections (26.9%). The findings in the abdominal wall were: densification (61.5%), pseudocavitated nodules (3.8%), and collections (15.4%). The intraperitoneal findings were: densification (46.1%), small nodules (42.3%), nodules (15.4%), and collections (11.5%). Subcutaneous CT findings in descending order of frequency were: densification, small nodules, nodules, small pseudocavitated nodules, pseudocavitated nodules, and collections. The musculo-fascial plane CT findings were: densification, collections, and pseudocavitated nodules. The intraperitoneal CT findings were: densification, small nodules, nodules, and collections. • Rapidly growing mycobacterial infection may occur following laparoscopy. • Post-laparoscopy mycobacterial infection CT findings are densification, collection, and nodules. • Rapidly growing mycobacterial infection following laparoscopy may involve the peritoneal cavity. • Post-laparoscopy rapidly growing mycobacterial intraperitoneal infection is not associated with ascites or lymphadenopathy.

  16. Rapidly growing ovarian endometrioid adenocarcinoma involving the vagina: A case report

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    Sunghun Na

    2011-12-01

    Conclusion: Epithelial ovarian cancer may grow very rapidly. The frequent measurement of tumor size by ultrasonography may provide important information on detection in a subset of ovarian carcinomas that develop from preexisting, detectable lesions.

  17. Adaptive region-growing with maximum curvature strategy for tumor segmentation in 18F-FDG PET

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    Tan, Shan; Li, Laquan; Choi, Wookjin; Kang, Min Kyu; D'Souza, Warren D.; Lu, Wei

    2017-07-01

    Accurate tumor segmentation in PET is crucial in many oncology applications. We developed an adaptive region-growing (ARG) algorithm with a maximum curvature strategy (ARG_MC) for tumor segmentation in PET. The ARG_MC repeatedly applied a confidence connected region-growing algorithm with increasing relaxing factor f. The optimal relaxing factor (ORF) was then determined at the transition point on the f-volume curve, where the volume just grew from the tumor into the surrounding normal tissues. The ARG_MC along with five widely used algorithms were tested on a phantom with 6 spheres at different signal to background ratios and on two clinic datasets including 20 patients with esophageal cancer and 11 patients with non-Hodgkin lymphoma (NHL). The ARG_MC did not require any phantom calibration or any a priori knowledge of the tumor or PET scanner. The identified ORF varied with tumor types (mean ORF  =  9.61, 3.78 and 2.55 respectively for the phantom, esophageal cancer, and NHL datasets), and varied from one tumor to another. For the phantom, the ARG_MC ranked the second in segmentation accuracy with an average Dice similarity index (DSI) of 0.86, only slightly worse than Daisne’s adaptive thresholding method (DSI  =  0.87), which required phantom calibration. For both the esophageal cancer dataset and the NHL dataset, the ARG_MC had the highest accuracy with an average DSI of 0.87 and 0.84, respectively. The ARG_MC was robust to parameter settings and region of interest selection, and it did not depend on scanners, imaging protocols, or tumor types. Furthermore, the ARG_MC made no assumption about the tumor size or tumor uptake distribution, making it suitable for segmenting tumors with heterogeneous FDG uptake. In conclusion, the ARG_MC was accurate, robust and easy to use, it provides a highly potential tool for PET tumor segmentation in clinic.

  18. Structural analysis of biofilm formation by rapidly and slowly growing nontuberculous mycobacteria

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    Mycobacterium avium complex (MAC) and rapidly growing mycobacteria (RGM) such as M. abscessus, M. mucogenicum, M. chelonae and M. fortuitum, implicated in healthcare-associated infections, are often isolated from potable water supplies as part of the microbial flora. To understa...

  19. Rapid diagnosis of aneuploidy using segmental duplication quantitative fluorescent PCR.

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    Xiangdong Kong

    Full Text Available The aim of this study was use a simple and rapid procedure, called segmental duplication quantitative fluorescent polymerase chain reaction (SD-QF-PCR, for the prenatal diagnosis of fetal chromosomal aneuploidies. This method is based on the co-amplification of segmental duplications located on two different chromosomes using a single pair of fluorescent primers. The PCR products of different sizes were subsequently analyzed through capillary electrophoresis, and the aneuploidies were determined based on the relative dosage between the two chromosomes. Each primer set, containing five pairs of primers, was designed to simultaneously detect aneuploidies located on chromosomes 21, 18, 13, X and Y in a single reaction. We applied these two primer sets to DNA samples isolated from individuals with trisomy 21 (n = 36; trisomy 18 (n = 6; trisomy 13 (n = 4; 45, X (n = 5; 47, XXX (n = 3; 48, XXYY (n = 2; and unaffected controls (n = 40. We evaluated the performance of this method using the karyotyping results. A correct and unambiguous diagnosis with 100% sensitivity and 100% specificity, was achieved for clinical samples examined. Thus, the present study demonstrates that SD-QF-PCR is a robust, rapid and sensitive method for the diagnosis of common aneuploidies, and these analyses can be performed in less than 4 hours for a single sample, providing a competitive alternative for routine use.

  20. Mycobacterium aquiterrae sp. nov., a rapidly growing bacterium isolated from groundwater.

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    Lee, Jae-Chan; Whang, Kyung-Sook

    2017-10-01

    A strain representing a rapidly growing, Gram-stain-positive, aerobic, rod-shaped, non-motile, non-sporulating and non-pigmented species of the genus Mycobacterium, designated strain S-I-6 T , was isolated from groundwater at Daejeon in Korea. The strain grew at temperatures between 10 and 37 °C (optimal growth at 25 °C), between pH 4.0 and 9.0 (optimal growth at pH 7.0) and at salinities of 0-5 % (w/v) NaCl, growing optimally with 2 % (w/v) NaCl. Phylogenetic analyses based on multilocus sequence analysis of the 16S rRNAgene, hsp65, rpoB and the 16S-23S internal transcribed spacer indicated that strain S-I-6 T belonged to the rapidly growing mycobacteria, being most closely related to Mycobacterium sphagni. On the basis of polyphasic taxonomic analysis, the bacterial strain was distinguished from its phylogenetic neighbours by chemotaxonomic properties and other biochemical characteristics. DNA-DNA relatedness among strain S-I-6 T and the closest phylogenetic neighbour strongly support the proposal that this strain represents a novel species within the genus Mycobacterium, for which the name Mycobacterium aquiterrae sp. nov. is proposed. The type strain is S-I-6 T (=KACC 17600 T =NBRC 109805 T =NCAIM B 02535 T ).

  1. Attributed relational graphs for cell nucleus segmentation in fluorescence microscopy images.

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    Arslan, Salim; Ersahin, Tulin; Cetin-Atalay, Rengul; Gunduz-Demir, Cigdem

    2013-06-01

    More rapid and accurate high-throughput screening in molecular cellular biology research has become possible with the development of automated microscopy imaging, for which cell nucleus segmentation commonly constitutes the core step. Although several promising methods exist for segmenting the nuclei of monolayer isolated and less-confluent cells, it still remains an open problem to segment the nuclei of more-confluent cells, which tend to grow in overlayers. To address this problem, we propose a new model-based nucleus segmentation algorithm. This algorithm models how a human locates a nucleus by identifying the nucleus boundaries and piecing them together. In this algorithm, we define four types of primitives to represent nucleus boundaries at different orientations and construct an attributed relational graph on the primitives to represent their spatial relations. Then, we reduce the nucleus identification problem to finding predefined structural patterns in the constructed graph and also use the primitives in region growing to delineate the nucleus borders. Working with fluorescence microscopy images, our experiments demonstrate that the proposed algorithm identifies nuclei better than previous nucleus segmentation algorithms.

  2. An Algorithm to Automate Yeast Segmentation and Tracking

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    Doncic, Andreas; Eser, Umut; Atay, Oguzhan; Skotheim, Jan M.

    2013-01-01

    Our understanding of dynamic cellular processes has been greatly enhanced by rapid advances in quantitative fluorescence microscopy. Imaging single cells has emphasized the prevalence of phenomena that can be difficult to infer from population measurements, such as all-or-none cellular decisions, cell-to-cell variability, and oscillations. Examination of these phenomena requires segmenting and tracking individual cells over long periods of time. However, accurate segmentation and tracking of cells is difficult and is often the rate-limiting step in an experimental pipeline. Here, we present an algorithm that accomplishes fully automated segmentation and tracking of budding yeast cells within growing colonies. The algorithm incorporates prior information of yeast-specific traits, such as immobility and growth rate, to segment an image using a set of threshold values rather than one specific optimized threshold. Results from the entire set of thresholds are then used to perform a robust final segmentation. PMID:23520484

  3. A novel region-growing based semi-automatic segmentation protocol for three-dimensional condylar reconstruction using cone beam computed tomography (CBCT.

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    Tong Xi

    Full Text Available OBJECTIVE: To present and validate a semi-automatic segmentation protocol to enable an accurate 3D reconstruction of the mandibular condyles using cone beam computed tomography (CBCT. MATERIALS AND METHODS: Approval from the regional medical ethics review board was obtained for this study. Bilateral mandibular condyles in ten CBCT datasets of patients were segmented using the currently proposed semi-automatic segmentation protocol. This segmentation protocol combined 3D region-growing and local thresholding algorithms. The segmentation of a total of twenty condyles was performed by two observers. The Dice-coefficient and distance map calculations were used to evaluate the accuracy and reproducibility of the segmented and 3D rendered condyles. RESULTS: The mean inter-observer Dice-coefficient was 0.98 (range [0.95-0.99]. An average 90th percentile distance of 0.32 mm was found, indicating an excellent inter-observer similarity of the segmented and 3D rendered condyles. No systematic errors were observed in the currently proposed segmentation protocol. CONCLUSION: The novel semi-automated segmentation protocol is an accurate and reproducible tool to segment and render condyles in 3D. The implementation of this protocol in the clinical practice allows the CBCT to be used as an imaging modality for the quantitative analysis of condylar morphology.

  4. Rapidly growing mycobacteria in Singapore, 2006-2011.

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    Tang, S S; Lye, D C; Jureen, R; Sng, L-H; Hsu, L Y

    2015-03-01

    Nontuberculous mycobacteria infection is a growing global concern, but data from Asia are limited. This study aimed to describe the distribution and antibiotic susceptibility profiles of rapidly growing mycobacterium (RGM) isolates in Singapore. Clinical RGM isolates with antibiotic susceptibility tests performed between 2006 and 2011 were identified using microbiology laboratory databases and minimum inhibitory concentrations of amikacin, cefoxitin, clarithromycin, ciprofloxacin, doxycycline, imipenem, linezolid, moxifloxacin, sulfamethoxazole or trimethoprim-sulfamethoxazole, tigecycline and tobramycin were recorded. Regression analysis was performed to detect changes in antibiotic susceptibility patterns over time. A total of 427 isolates were included. Of these, 277 (65%) were from respiratory specimens, 42 (10%) were related to skin and soft tissue infections and 36 (8%) were recovered from blood specimens. The two most common species identified were Mycobacterium abscessus (73%) and Mycobacterium fortuitum group (22%), with amikacin and clarithromycin being most active against the former, and quinolones and trimethoprim-sulfamethoxazole against the latter. Decreases in susceptibility of M. abscessus to linezolid by 8.8% per year (p 0.001), M. fortuitum group to imipenem by 9.5% per year (p 0.023) and clarithromycin by 4.7% per year (p 0.033) were observed. M. abscessus in respiratory specimens is the most common RGM identified in Singapore. Antibiotic options for treatment of RGM infections are increasingly limited. Copyright © 2014 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

  5. An algorithm to automate yeast segmentation and tracking.

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    Andreas Doncic

    Full Text Available Our understanding of dynamic cellular processes has been greatly enhanced by rapid advances in quantitative fluorescence microscopy. Imaging single cells has emphasized the prevalence of phenomena that can be difficult to infer from population measurements, such as all-or-none cellular decisions, cell-to-cell variability, and oscillations. Examination of these phenomena requires segmenting and tracking individual cells over long periods of time. However, accurate segmentation and tracking of cells is difficult and is often the rate-limiting step in an experimental pipeline. Here, we present an algorithm that accomplishes fully automated segmentation and tracking of budding yeast cells within growing colonies. The algorithm incorporates prior information of yeast-specific traits, such as immobility and growth rate, to segment an image using a set of threshold values rather than one specific optimized threshold. Results from the entire set of thresholds are then used to perform a robust final segmentation.

  6. Automated lung tumor segmentation for whole body PET volume based on novel downhill region growing

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    Ballangan, Cherry; Wang, Xiuying; Eberl, Stefan; Fulham, Michael; Feng, Dagan

    2010-03-01

    We propose an automated lung tumor segmentation method for whole body PET images based on a novel downhill region growing (DRG) technique, which regards homogeneous tumor hotspots as 3D monotonically decreasing functions. The method has three major steps: thoracic slice extraction with K-means clustering of the slice features; hotspot segmentation with DRG; and decision tree analysis based hotspot classification. To overcome the common problem of leakage into adjacent hotspots in automated lung tumor segmentation, DRG employs the tumors' SUV monotonicity features. DRG also uses gradient magnitude of tumors' SUV to improve tumor boundary definition. We used 14 PET volumes from patients with primary NSCLC for validation. The thoracic region extraction step achieved good and consistent results for all patients despite marked differences in size and shape of the lungs and the presence of large tumors. The DRG technique was able to avoid the problem of leakage into adjacent hotspots and produced a volumetric overlap fraction of 0.61 +/- 0.13 which outperformed four other methods where the overlap fraction varied from 0.40 +/- 0.24 to 0.59 +/- 0.14. Of the 18 tumors in 14 NSCLC studies, 15 lesions were classified correctly, 2 were false negative and 15 were false positive.

  7. Rapid Automated Target Segmentation and Tracking on 4D Data without Initial Contours

    International Nuclear Information System (INIS)

    Chebrolu, V.V.; Chebrolu, V.V.; Saenz, D.; Tewatia, D.; Paliwal, B.R.; Chebrolu, V.V.; Saenz, D.; Paliwal, B.R.; Sethares, W.A.; Cannon, G.

    2014-01-01

    To achieve rapid automated delineation of gross target volume (GTV) and to quantify changes in volume/position of the target for radiotherapy planning using four-dimensional (4D) CT. Methods and Materials. Novel morphological processing and successive localization (MPSL) algorithms were designed and implemented for achieving auto segmentation. Contours automatically generated using MPSL method were compared with contours generated using state-of-the-art deformable registration methods (using Elastix © and MIMV ista software). Metrics such as the Dice similarity coefficient, sensitivity, and positive predictive value (PPV) were analyzed. The target motion tracked using the centroid of the GTV estimated using MPSL method was compared with motion tracked using deformable registration methods. Results. MPSL algorithm segmented the GTV in 4DCT images in 27.0 ±11.1 seconds per phase ( 512 ×512 resolution) as compared to 142.3±11.3 seconds per phase for deformable registration based methods in 9 cases. Dice coefficients between MPSL generated GTV contours and manual contours (considered as ground-truth) were 0.865 ± 0.037. In comparison, the Dice coefficients between ground-truth and contours generated using deformable registration based methods were 0.909 ± 0.051. Conclusions. The MPSL method achieved similar segmentation accuracy as compared to state-of-the-art deformable registration based segmentation methods, but with significant reduction in time required for GTV segmentation.

  8. Rapidly Growing Chondroid Syringoma of the External Auditory Canal: Report of a Rare Case

    Science.gov (United States)

    Vasileiadis, Ioannis; Kapetanakis, Stylianos; Petousis, Aristotelis; Karakostas, Euthimios; Simantirakis, Christos

    2011-01-01

    Introduction. Chondroid syrinoma of the external auditory canal is an extremely rare benign neoplasm representing the cutaneous counterpart of pleomorphic adenoma of salivary glands. Less than 35 cases have been reported in the international literature. Case Presentation. We report a case of a 34-year-old male in whom a rapidly growing, well-circumscribed tumor arising from the external auditory canal was presented. Otoscopy revealed a smooth, nontender lesion covered by normal skin that almost obstructs the external auditory meatus. MRI was performed to define the extension of the lesion. It confirmed the presence of a 1.5 × 0.8 cm T2 high-signal intensity lesion in the superior and posterior wall of EAC without signs of bone erosion. The patient underwent complete resection of the tumor. The diagnosis was confirmed by histopathologic examination. Conclusion. Although chondroid syringoma is extremely rare, it should always be considered in the differential diagnosis of an aural polyp. Chondroid syringomas are usually asymptomatic, slow-growing, single benign tumors in subcutaneous or intradermal location. In our case, the new information is that this benign tumor could present also as a rapidly growing lesion, arising the suspicion for malignancy. PMID:21941560

  9. Rapidly Growing Chondroid Syringoma of the External Auditory Canal: Report of a Rare Case

    Directory of Open Access Journals (Sweden)

    Ioannis Vasileiadis

    2011-01-01

    Full Text Available Introduction. Chondroid syrinoma of the external auditory canal is an extremely rare benign neoplasm representing the cutaneous counterpart of pleomorphic adenoma of salivary glands. Less than 35 cases have been reported in the international literature. Case Presentation. We report a case of a 34-year-old male in whom a rapidly growing, well-circumscribed tumor arising from the external auditory canal was presented. Otoscopy revealed a smooth, nontender lesion covered by normal skin that almost obstructs the external auditory meatus. MRI was performed to define the extension of the lesion. It confirmed the presence of a 1.5×0.8 cm T2 high-signal intensity lesion in the superior and posterior wall of EAC without signs of bone erosion. The patient underwent complete resection of the tumor. The diagnosis was confirmed by histopathologic examination. Conclusion. Although chondroid syringoma is extremely rare, it should always be considered in the differential diagnosis of an aural polyp. Chondroid syringomas are usually asymptomatic, slow-growing, single benign tumors in subcutaneous or intradermal location. In our case, the new information is that this benign tumor could present also as a rapidly growing lesion, arising the suspicion for malignancy.

  10. Surgical site infections due to rapidly growing mycobacteria in puducherry, India.

    Science.gov (United States)

    Kannaiyan, Kavitha; Ragunathan, Latha; Sakthivel, Sulochana; Sasidar, A R; Muralidaran; Venkatachalam, G K

    2015-03-01

    Rapidly growing Mycobacteria are increasingly recognized, nowadays as an important pathogen that can cause wide range of clinical syndromes in humans. We herein describe unrelated cases of surgical site infection caused by Rapidly growing Mycobacteria (RGM), seen during a period of 12 months. Nineteen patients underwent operations by different surgical teams located in diverse sections of Tamil Nadu, Pondicherry, Karnataka, India. All patients presented with painful, draining subcutaneous nodules at the infection sites. Purulent material specimens were sent to the microbiology laboratory. Gram stain and Ziehl-Neelsen staining methods were used for direct examination. Culture media included blood agar, chocolate agar, MacConkey agar, Sabourauds agar and Lowenstein-Jensen medium for Mycobacteria. Isolated microorganisms were identified and further tested for antimicrobial susceptibility by standard microbiologic procedures. Mycobacterium fortuitum and M.chelonae were isolated from the purulent drainage obtained from wounds by routine microbiological techniques from all the specimens. All isolates analyzed for antimicrobial susceptibility pattern were sensitive to clarithromycin, linezolid and amikacin but were variable to ciprofloxacin, rifampicin and tobramycin. Our case series highlights that a high level of clinical suspicion should be maintained for patients presenting with protracted soft tissue lesions with a history of trauma or surgery as these infections not only cause physical but also emotional distress that affects both the patients and the surgeon.

  11. Fast Edge Detection and Segmentation of Terrestrial Laser Scans Through Normal Variation Analysis

    Science.gov (United States)

    Che, E.; Olsen, M. J.

    2017-09-01

    Terrestrial Laser Scanning (TLS) utilizes light detection and ranging (lidar) to effectively and efficiently acquire point cloud data for a wide variety of applications. Segmentation is a common procedure of post-processing to group the point cloud into a number of clusters to simplify the data for the sequential modelling and analysis needed for most applications. This paper presents a novel method to rapidly segment TLS data based on edge detection and region growing. First, by computing the projected incidence angles and performing the normal variation analysis, the silhouette edges and intersection edges are separated from the smooth surfaces. Then a modified region growing algorithm groups the points lying on the same smooth surface. The proposed method efficiently exploits the gridded scan pattern utilized during acquisition of TLS data from most sensors and takes advantage of parallel programming to process approximately 1 million points per second. Moreover, the proposed segmentation does not require estimation of the normal at each point, which limits the errors in normal estimation propagating to segmentation. Both an indoor and outdoor scene are used for an experiment to demonstrate and discuss the effectiveness and robustness of the proposed segmentation method.

  12. Automatic Cell Segmentation in Fluorescence Images of Confluent Cell Monolayers Using Multi-object Geometric Deformable Model

    OpenAIRE

    Yang, Zhen; Bogovic, John A.; Carass, Aaron; Ye, Mao; Searson, Peter C.; Prince, Jerry L.

    2013-01-01

    With the rapid development of microscopy for cell imaging, there is a strong and growing demand for image analysis software to quantitatively study cell morphology. Automatic cell segmentation is an important step in image analysis. Despite substantial progress, there is still a need to improve the accuracy, efficiency, and adaptability to different cell morphologies. In this paper, we propose a fully automatic method for segmenting cells in fluorescence images of confluent cell monolayers. T...

  13. Rapidly growing ovarian endometrioid adenocarcinoma involving the vagina: a case report.

    Science.gov (United States)

    Na, Sunghun; Hwang, Jongyun; Lee, Hyangah; Lee, Jiyeon; Lee, Dongheon

    2011-12-01

    We present a rare case of a very rapidly growing stage IV ovarian endometrioid adenocarcinoma involving the uterine cervix and vagina without lymph node involvement. A 43-year-old woman visited the hospital with complaints of lower abdominal discomfort and vaginal bleeding over the previous 3 months. Serum levels of tumor marker CA 125 and SCC antigen (TA-4) were normal. On magnetic resonance imaging, a 7.9×9.7cm heterogeneous mass with intermediate signal intensity was observed in the posterior low body of the uterus. Two months ago, a computed tomography scan revealed an approximate 4.5×3.0cm heterogeneously enhanced subserosal mass with internal ill-defined hypodensities. A laparotomy, including a total abdominal hysterectomy with resection of the upper vagina, bilateral salpingo-oophorectomy, pelvic and para-aortic lymph node dissection, appendectomy, total omentectomy, and biopsy of rectal serosa was performed. A histological examination revealed poorly differentiated endometrioid ovarian adenocarcinoma with vaginal involvement. The patient had an uncomplicated post-operative course. After discharge, she completed six cycles of adjuvant chemotherapy with paclitaxel (175mg/m(2)) and carboplatin (300mg/m(2)) and has remained clinically disease-free until June 2010. Epithelial ovarian cancer may grow very rapidly. The frequent measurement of tumor size by ultrasonography may provide important information on detection in a subset of ovarian carcinomas that develop from preexisting, detectable lesions. Copyright © 2011. Published by Elsevier B.V.

  14. Rapid Automated Target Segmentation and Tracking on 4D Data without Initial Contours

    Directory of Open Access Journals (Sweden)

    Venkata V. Chebrolu

    2014-01-01

    Full Text Available Purpose. To achieve rapid automated delineation of gross target volume (GTV and to quantify changes in volume/position of the target for radiotherapy planning using four-dimensional (4D CT. Methods and Materials. Novel morphological processing and successive localization (MPSL algorithms were designed and implemented for achieving autosegmentation. Contours automatically generated using MPSL method were compared with contours generated using state-of-the-art deformable registration methods (using Elastix© and MIMVista software. Metrics such as the Dice similarity coefficient, sensitivity, and positive predictive value (PPV were analyzed. The target motion tracked using the centroid of the GTV estimated using MPSL method was compared with motion tracked using deformable registration methods. Results. MPSL algorithm segmented the GTV in 4DCT images in 27.0±11.1 seconds per phase (512×512 resolution as compared to 142.3±11.3 seconds per phase for deformable registration based methods in 9 cases. Dice coefficients between MPSL generated GTV contours and manual contours (considered as ground-truth were 0.865±0.037. In comparison, the Dice coefficients between ground-truth and contours generated using deformable registration based methods were 0.909 ± 0.051. Conclusions. The MPSL method achieved similar segmentation accuracy as compared to state-of-the-art deformable registration based segmentation methods, but with significant reduction in time required for GTV segmentation.

  15. Rapid Automated Target Segmentation and Tracking on 4D Data without Initial Contours.

    Science.gov (United States)

    Chebrolu, Venkata V; Saenz, Daniel; Tewatia, Dinesh; Sethares, William A; Cannon, George; Paliwal, Bhudatt R

    2014-01-01

    Purpose. To achieve rapid automated delineation of gross target volume (GTV) and to quantify changes in volume/position of the target for radiotherapy planning using four-dimensional (4D) CT. Methods and Materials. Novel morphological processing and successive localization (MPSL) algorithms were designed and implemented for achieving autosegmentation. Contours automatically generated using MPSL method were compared with contours generated using state-of-the-art deformable registration methods (using Elastix© and MIMVista software). Metrics such as the Dice similarity coefficient, sensitivity, and positive predictive value (PPV) were analyzed. The target motion tracked using the centroid of the GTV estimated using MPSL method was compared with motion tracked using deformable registration methods. Results. MPSL algorithm segmented the GTV in 4DCT images in 27.0 ± 11.1 seconds per phase (512 × 512 resolution) as compared to 142.3 ± 11.3 seconds per phase for deformable registration based methods in 9 cases. Dice coefficients between MPSL generated GTV contours and manual contours (considered as ground-truth) were 0.865 ± 0.037. In comparison, the Dice coefficients between ground-truth and contours generated using deformable registration based methods were 0.909 ± 0.051. Conclusions. The MPSL method achieved similar segmentation accuracy as compared to state-of-the-art deformable registration based segmentation methods, but with significant reduction in time required for GTV segmentation.

  16. A Study on the Application of Fuzzy Information Seeded Region Growing in Brain MRI Tissue Segmentation

    Directory of Open Access Journals (Sweden)

    Chuin-Mu Wang

    2014-01-01

    Full Text Available After long-term clinical trials, MRI has been proven to be used in humans harmlessly, and it is popularly used in medical diagnosis. Although MR is highly sensitive, it provides abundant organization information. Therefore, how to transform the multi-spectral images which is easier to be used for doctor’s clinical diagnosis. In this thesis, the fuzzy bidirectional edge detection method is used to solve conventional SRG problem of growing order in the initial seed stages. In order to overcome the problems of the different regions, although it is the same Euclidean distance for region growing and merging process stages, we present the peak detection method to improve them. The standard deviation target generation process (SDTGP is applied to guarantee the regions merging process does not cause over- or undersegmentation. Experimental results reveal that FISRG segments a multispectral MR image much more effectively than FAST and K-means.

  17. Modeling of market segmentation for new IT product development

    Science.gov (United States)

    Nasiopoulos, Dimitrios K.; Sakas, Damianos P.; Vlachos, D. S.; Mavrogianni, Amanda

    2015-02-01

    Businesses from all Information Technology sectors use market segmentation[1] in their product development[2] and strategic planning[3]. Many studies have concluded that market segmentation is considered as the norm of modern marketing. With the rapid development of technology, customer needs are becoming increasingly diverse. These needs can no longer be satisfied by a mass marketing approach and follow one rule. IT Businesses can face with this diversity by pooling customers[4] with similar requirements and buying behavior and strength into segments. The result of the best choices about which segments are the most appropriate to serve can then be made, thus making the best of finite resources. Despite the attention which segmentation gathers and the resources that are invested in it, growing evidence suggests that businesses have problems operationalizing segmentation[5]. These problems take various forms. There may have been a rule that the segmentation process necessarily results in homogeneous groups of customers for whom appropriate marketing programs and procedures for dealing with them can be developed. Then the segmentation process, that a company follows, can fail. This increases concerns about what causes segmentation failure and how it might be overcome. To prevent the failure, we created a dynamic simulation model of market segmentation[6] based on the basic factors leading to this segmentation.

  18. The impact of entrepreneurial capital and rapidly growing firms: the Canadian example

    DEFF Research Database (Denmark)

    Keen, Christian; Etemad, Hamid

    2011-01-01

    . It provides empirical evidence from small, young, high-growth enterprises that entrepreneurial capital contributes significantly to their growth through such augmentation. As emerging industries and regions face similar challenges as those of high and rapidly-growing smaller enterprises in increasingly more......World-class competitiveness is no longer an option for firms seeking growth and survival in the increasingly competitive, dynamic and interconnected world. This paper expands on the concept of entrepreneurial capital and formalizes it as a catalyst that augments other productive factors...

  19. A strategy analysis of the effectiveness of mobile marketing on the buying behaviour of the lower income segments

    OpenAIRE

    2015-01-01

    M.Com. (Business Management) Mobile marketing has rapidly grown during the past years, and will continue to grow with advancements in technology, enabling mobile phones to be used for much more than simple calls and personal text messaging. This study investigates how a mobile marketing company, Mobitainment, can successfully communicate, through mobile marketing initiatives, with the lower income segments. The various characteristics of the lower income segment are understood, and the pos...

  20. Clinical and Taxonomic Status of Pathogenic Nonpigmented or Late-Pigmenting Rapidly Growing Mycobacteria

    OpenAIRE

    Brown-Elliott, Barbara A.; Wallace, Richard J.

    2002-01-01

    The history, taxonomy, geographic distribution, clinical disease, and therapy of the pathogenic nonpigmented or late-pigmenting rapidly growing mycobacteria (RGM) are reviewed. Community-acquired disease and health care-associated disease are highlighted for each species. The latter grouping includes health care-associated outbreaks and pseudo-outbreaks as well as sporadic disease cases. Treatment recommendations for each species and type of disease are also described. Special emphasis is on ...

  1. Antimicrobial susceptibility testing of rapidly growing mycobacteria by microdilution - Experience of a tertiary care centre

    Directory of Open Access Journals (Sweden)

    Set R

    2010-01-01

    Full Text Available Purpose: The objective of the study was to perform antimicrobial susceptibility testing of rapidly growing mycobacteria (RGM isolated from various clinically suspected cases of extrapulmonary tuberculosis, from January 2007 to April 2008, at a tertiary care centre in Mumbai. Materials and Methods: The specimens were processed for microscopy and culture using the standard procedures. Minimum inhibitory concentrations (MIC were determined by broth microdilution, using Sensititre CA MHBT. Susceptibility testing was also carried out on Mueller Hinton agar by the Kirby Bauer disc diffusion method. Results: Of the 1062 specimens received for mycobacterial cultures, 104 (9.79% grew mycobacteria. Of the mycobacterial isolates, six (5.76% were rapid growers. M. abscessus and M. chelonae appeared to be resistant organisms, with M. chelonae showing intermediate resistance to amikacin and minocycline. However, all the six isolates showed sensitivity to vancomycin and gentamicin by the disc diffusion test. Also all three isolates of M. abscessus were sensitive to piperacillin and erythromycin. Further studies are required to test their sensitivity to these four antimicrobials by using the microbroth dilution test, before they can be prescribed to patients. Conclusions: We wish to emphasize that reporting of rapidly growing mycobacteria from clinical settings, along with their sensitivity patterns, is an absolute need of the hour.

  2. In vitro activity of flomoxef against rapidly growing mycobacteria.

    Science.gov (United States)

    Tsai, Moan-Shane; Tang, Ya-Fen; Eng, Hock-Liew

    2008-06-01

    The aim of this study was to determine the in vitro sensitivity of rapidly growing mycobacteria (RGM) to flomoxef in respiratory secretions collected from 61 consecutive inpatients and outpatients at Chang Gung Memorial Hospital-Kaohsiung medical center between July and December, 2005. Minimal inhibitory concentrations (MIC) of flomoxef were determined by the broth dilution method for the 61 clinical isolates of RGMs. The MICs of flomoxef at which 90% of clinical isolates were inhibited was >128 microg/mL in 26 isolates of Mycobacterium abscessus and 4 microg/mL in 31 isolates of M. fortuitum. Three out of 4 clinical M. peregrinum isolates were inhibited by flomoxef at concentrations of 4 microg/mL or less. Although the numbers of the clinical isolates of RGMs were small, these preliminary in vitro results demonstrate the potential activity of flomoxef in the management of infections due to M. fortuitum, and probably M. peregrinum in humans.

  3. Segmentation of isolated MR images: development and comparison of neuronal networks

    International Nuclear Information System (INIS)

    Paredes, R.; Robles, M.; Marti-Bonmati, L.; Masia, L.

    1998-01-01

    Segmentation defines the capacity to differentiate among types of tissues. In MR. it is frequently applied to volumetric determinations. Digital images can be segmented in a number of ways; neuronal networks (NN) can be employed for this purpose. Our objective was to develop algorithms for automatic segmentation using NN and apply them to central nervous system MR images. The segmentation obtained with NN was compared with that resulting from other procedures (region-growing and K means). Each NN consisted of two layers: one based on unsupervised training, which was utilized for image segmentation in sets of K, and a second layer associating each set obtained by the preceding layer with the real set corresponding to the previously segmented objective image. This NN was trained with previously segmented images with supervised regions-growing algorithms and automatic K means. Thus, 4 different segmentation were obtained: region-growing, K means, NN with region-growing and NN with K means. The tissue volumes corresponding to cerebrospinal fluid, gray matter and white matter obtained with the 4 techniques were compared and the most representative segmented image was selected qualitatively by averaging the visual perception of 3 radiologists. The segmentation that best corresponded to the visual perception of the radiologists was that consisting of trained NN with region-growing. In comparison, the other 3 algorithms presented low percentage differences (mean, 3.44%). The mean percentage error for the 3 tissues from these algorithms was lower for region-growing segmentation (2.34%) than for trained NN with K means (3.31%) and for automatic K-means segmentation (4.66%). Thus, NN are reliable in the automation of isolated MR image segmentation. (Author) 12 refs

  4. Clinical management of rapidly growing mycobacterial cutaneous infections in patients after mesotherapy.

    Science.gov (United States)

    Regnier, Stéphanie; Cambau, Emmanuelle; Meningaud, Jean-Paul; Guihot, Amelie; Deforges, Lionel; Carbonne, Anne; Bricaire, François; Caumes, Eric

    2009-11-01

    Increasing numbers of patients are expressing an interest in mesotherapy as a method of reducing body fat. Cutaneous infections due to rapidly growing mycobacteria are a common complication of such procedures. We followed up patients who had developed cutaneous infections after undergoing mesotherapy during the period October 2006-January 2007. Sixteen patients were infected after mesotherapy injections performed by the same physician. All patients presented with painful, erythematous, draining subcutaneous nodules at the injection sites. All patients were treated with surgical drainage. Microbiological examination was performed on specimens that were obtained before and during the surgical procedure. Direct examination of skin smears demonstrated acid-fast bacilli in 25% of the specimens that were obtained before the procedure and 37% of the specimens obtained during the procedure; culture results were positive in 75% of the patients. Mycobacterium chelonae was identified in 11 patients, and Mycobacterium frederiksbergense was identified in 2 patients. Fourteen patients were treated with antibiotics, 6 received triple therapy as first-line treatment (tigecycline, tobramycin, and clarithromycin), and 8 received dual therapy (clarithromycin and ciprofloxacin). The mean duration of treatment was 14 weeks (range, 1-24 weeks). All of the patients except 1 were fully recovered 2 years after the onset of infection, with the mean time to healing estimated at 6.2 months (range, 1-15 months). This series of rapidly growing mycobacterial cutaneous infections highlights the difficulties in treating such infections and suggests that in vitro susceptibility to antibiotics does not accurately predict their clinical efficacy.

  5. General Staining and Segmentation Procedures for High Content Imaging and Analysis.

    Science.gov (United States)

    Chambers, Kevin M; Mandavilli, Bhaskar S; Dolman, Nick J; Janes, Michael S

    2018-01-01

    Automated quantitative fluorescence microscopy, also known as high content imaging (HCI), is a rapidly growing analytical approach in cell biology. Because automated image analysis relies heavily on robust demarcation of cells and subcellular regions, reliable methods for labeling cells is a critical component of the HCI workflow. Labeling of cells for image segmentation is typically performed with fluorescent probes that bind DNA for nuclear-based cell demarcation or with those which react with proteins for image analysis based on whole cell staining. These reagents, along with instrument and software settings, play an important role in the successful segmentation of cells in a population for automated and quantitative image analysis. In this chapter, we describe standard procedures for labeling and image segmentation in both live and fixed cell samples. The chapter will also provide troubleshooting guidelines for some of the common problems associated with these aspects of HCI.

  6. Rapidly Growing Thyroid Mass in an Immunocompromised Young Male Adult

    Directory of Open Access Journals (Sweden)

    Mónica Santiago

    2013-01-01

    Full Text Available We describe a 20-year-old man diagnosed with a myelodysplastic syndrome (MDS, admitted to our hospital due to pancytopenia and fever of undetermined origin after myelosuppression with chemotherapy. Disseminated aspergillosis (DIA was suspected when he developed skin and lung involvement. A rapidly growing mass was detected on the left neck area, during hospitalization. A thyroid ultrasound reported a 3.7×2.5×2.9 cm oval heterogeneous structure, suggestive of an abscess versus a hematoma. Fine needle aspiration of the thyroid revealed invasion of aspergillosis. Fungal thyroiditis is a rare occurrence. Thyroid fungal infection is difficult to diagnose; for this reason it is rarely diagnosed antemortem. To our knowledge, this is the 10th case reported in the literature in an adult where the diagnosis of fungal invasion to the thyroid was able to be corroborated antemortem by fine needle aspiration biopsy.

  7. Rapidly- growing firms and their main characteristics: a longitudinal study from United States

    DEFF Research Database (Denmark)

    Keen, Christian; Etemad, Hamid

    2011-01-01

    concerning the theoretical relations between high-growth and location, size and temporal characteristics of the high-growth enterprises. Using non parametric tests, we analyze a 21-year longitudinal database of privately held rapidly growing enterprises from the USA. This analysis indicates that these firms...... are relatively smaller enterprises and their high growth rates are not restricted to a particular location, industrial region, size or time period. The findings of this analysis point to a population of high-growth enterprises with diverse locations, sizes and times with important implications for scholarly...

  8. Computer aided detection of suspicious regions on digital mammograms : rapid segmentation and feature extraction

    Energy Technology Data Exchange (ETDEWEB)

    Ruggiero, C; Giacomini, M; Sacile, R [DIST - Department of Communication Computer and System Sciences, University of Genova, Via Opera Pia 13, 16145 Genova (Italy); Rosselli Del Turco, M [Centro per lo studio e la prevenzione oncologica, Firenze (Italy)

    1999-12-31

    A method is presented for rapid detection of suspicious regions which consists of two steps. The first step is segmentation based on texture analysis consisting of : histogram equalization, Laws filtering for texture analysis, Gaussian blur and median filtering to enhance differences between tissues in different respects, histogram thresholding to obtain a binary image, logical masking in order to detect regions to be discarded from the analysis, edge detection. This method has been tested on 60 images, obtaining 93% successful detection of suspicious regions. (authors) 4 refs, 9 figs, 1 tabs.

  9. Segmental Vitiligo.

    Science.gov (United States)

    van Geel, Nanja; Speeckaert, Reinhart

    2017-04-01

    Segmental vitiligo is characterized by its early onset, rapid stabilization, and unilateral distribution. Recent evidence suggests that segmental and nonsegmental vitiligo could represent variants of the same disease spectrum. Observational studies with respect to its distribution pattern point to a possible role of cutaneous mosaicism, whereas the original stated dermatomal distribution seems to be a misnomer. Although the exact pathogenic mechanism behind the melanocyte destruction is still unknown, increasing evidence has been published on the autoimmune/inflammatory theory of segmental vitiligo. Copyright © 2016 Elsevier Inc. All rights reserved.

  10. Volumetric analysis of pelvic hematomas after blunt trauma using semi-automated seeded region growing segmentation: a method validation study.

    Science.gov (United States)

    Dreizin, David; Bodanapally, Uttam K; Neerchal, Nagaraj; Tirada, Nikki; Patlas, Michael; Herskovits, Edward

    2016-11-01

    Manually segmented traumatic pelvic hematoma volumes are strongly predictive of active bleeding at conventional angiography, but the method is time intensive, limiting its clinical applicability. We compared volumetric analysis using semi-automated region growing segmentation to manual segmentation and diameter-based size estimates in patients with pelvic hematomas after blunt pelvic trauma. A 14-patient cohort was selected in an anonymous randomized fashion from a dataset of patients with pelvic binders at MDCT, collected retrospectively as part of a HIPAA-compliant IRB-approved study from January 2008 to December 2013. To evaluate intermethod differences, one reader (R1) performed three volume measurements using the manual technique and three volume measurements using the semi-automated technique. To evaluate interobserver differences for semi-automated segmentation, a second reader (R2) performed three semi-automated measurements. One-way analysis of variance was used to compare differences in mean volumes. Time effort was also compared. Correlation between the two methods as well as two shorthand appraisals (greatest diameter, and the ABC/2 method for estimating ellipsoid volumes) was assessed with Spearman's rho (r). Intraobserver variability was lower for semi-automated compared to manual segmentation, with standard deviations ranging between ±5-32 mL and ±17-84 mL, respectively (p = 0.0003). There was no significant difference in mean volumes between the two readers' semi-automated measurements (p = 0.83); however, means were lower for the semi-automated compared with the manual technique (manual: mean and SD 309.6 ± 139 mL; R1 semi-auto: 229.6 ± 88.2 mL, p = 0.004; R2 semi-auto: 243.79 ± 99.7 mL, p = 0.021). Despite differences in means, the correlation between the two methods was very strong and highly significant (r = 0.91, p hematoma volumes correlate strongly with manually segmented volumes. Since semi-automated segmentation

  11. Automatic segmentation of meningioma from non-contrasted brain MRI integrating fuzzy clustering and region growing

    Directory of Open Access Journals (Sweden)

    Liao Chun-Chih

    2011-08-01

    Full Text Available Abstract Background In recent years, magnetic resonance imaging (MRI has become important in brain tumor diagnosis. Using this modality, physicians can locate specific pathologies by analyzing differences in tissue character presented in different types of MR images. This paper uses an algorithm integrating fuzzy-c-mean (FCM and region growing techniques for automated tumor image segmentation from patients with menigioma. Only non-contrasted T1 and T2 -weighted MR images are included in the analysis. The study's aims are to correctly locate tumors in the images, and to detect those situated in the midline position of the brain. Methods The study used non-contrasted T1- and T2-weighted MR images from 29 patients with menigioma. After FCM clustering, 32 groups of images from each patient group were put through the region-growing procedure for pixels aggregation. Later, using knowledge-based information, the system selected tumor-containing images from these groups and merged them into one tumor image. An alternative semi-supervised method was added at this stage for comparison with the automatic method. Finally, the tumor image was optimized by a morphology operator. Results from automatic segmentation were compared to the "ground truth" (GT on a pixel level. Overall data were then evaluated using a quantified system. Results The quantified parameters, including the "percent match" (PM and "correlation ratio" (CR, suggested a high match between GT and the present study's system, as well as a fair level of correspondence. The results were compatible with those from other related studies. The system successfully detected all of the tumors situated at the midline of brain. Six cases failed in the automatic group. One also failed in the semi-supervised alternative. The remaining five cases presented noticeable edema inside the brain. In the 23 successful cases, the PM and CR values in the two groups were highly related. Conclusions Results indicated

  12. Automatic Cell Segmentation in Fluorescence Images of Confluent Cell Monolayers Using Multi-object Geometric Deformable Model.

    Science.gov (United States)

    Yang, Zhen; Bogovic, John A; Carass, Aaron; Ye, Mao; Searson, Peter C; Prince, Jerry L

    2013-03-13

    With the rapid development of microscopy for cell imaging, there is a strong and growing demand for image analysis software to quantitatively study cell morphology. Automatic cell segmentation is an important step in image analysis. Despite substantial progress, there is still a need to improve the accuracy, efficiency, and adaptability to different cell morphologies. In this paper, we propose a fully automatic method for segmenting cells in fluorescence images of confluent cell monolayers. This method addresses several challenges through a combination of ideas. 1) It realizes a fully automatic segmentation process by first detecting the cell nuclei as initial seeds and then using a multi-object geometric deformable model (MGDM) for final segmentation. 2) To deal with different defects in the fluorescence images, the cell junctions are enhanced by applying an order-statistic filter and principal curvature based image operator. 3) The final segmentation using MGDM promotes robust and accurate segmentation results, and guarantees no overlaps and gaps between neighboring cells. The automatic segmentation results are compared with manually delineated cells, and the average Dice coefficient over all distinguishable cells is 0.88.

  13. Performance Analysis of Segmentation of Hyperspectral Images Based on Color Image Segmentation

    Directory of Open Access Journals (Sweden)

    Praveen Agarwal

    2017-06-01

    Full Text Available Image segmentation is a fundamental approach in the field of image processing and based on user’s application .This paper propose an original and simple segmentation strategy based on the EM approach that resolves many informatics problems about hyperspectral images which are observed by airborne sensors. In a first step, to simplify the input color textured image into a color image without texture. The final segmentation is simply achieved by a spatially color segmentation using feature vector with the set of color values contained around the pixel to be classified with some mathematical equations. The spatial constraint allows taking into account the inherent spatial relationships of any image and its color. This approach provides effective PSNR for the segmented image. These results have the better performance as the segmented images are compared with Watershed & Region Growing Algorithm and provide effective segmentation for the Spectral Images & Medical Images.

  14. A rapid Kano-based approach to identify optimal user segments

    DEFF Research Database (Denmark)

    Atlason, Reynir Smari; Stefansson, Arnaldur Smari; Wietz, Miriam

    2018-01-01

    The Kano model of customer satisfaction provides product developers valuable information about if, and then how much a given functional requirement (FR) will impact customer satisfaction if implemented within a product, system or a service. A limitation of the Kano model is that it does not allow...... developers to visualise which combined sets of FRs would provide the highest satisfaction between different customer segments. In this paper, a stepwise method to address this shortcoming is presented. First, a traditional Kano analysis is conducted for the different segments of interest. Second, for each FR...... to the biggest target group. The proposed extension should assist product developers within to more effectively evaluate which FRs should be implemented when considering more than one combined customer segment. It shows which segments provide the highest possibility for high satisfaction of combined FRs. We...

  15. Familial cerebral cavernous haemangioma diagnosed in an infant with a rapidly growing cerebral lesion

    International Nuclear Information System (INIS)

    Ng, B.H.K.; Pereira, J.K.; Ghedia, S.; Pinner, J.; Mowat, D.; Vonau, M.

    2006-01-01

    Cavernous haemangiomas of the central nervous system are vascular malformations best imaged by MRI. They may present at any age, but to our knowledge only 39 cases in the first year of life have previously been reported. A familial form has been described and some of the underlying genetic mutations have recently been discovered. We present the clinical features and serial MRI findings of an 8-week-old boy who presented with subacute intracranial haemorrhage followed by rapid growth of a surgically proven cavernous haemangioma, mimicking a tumour. He also developed new lesions. A strong family history of neurological disease was elucidated. A familial form of cavernous haemangioma was confirmed by identification of a KRIT 1 gene mutation and cavernous haemangiomas in the patient and other family members. We stress the importance of considering cavernous haemangiomas in the context of intracerebral haemorrhage and in the differential diagnosis of rapidly growing lesions in this age group. The family history is also important in screening for familial disease

  16. [Rapidly-growing nodular pseudoangiomatous stromal hyperplasia of the breast: case report].

    Science.gov (United States)

    Elıyatkin, Nuket; Karasu, Başak; Selek, Elif; Keçecı, Yavuz; Postaci, Hakan

    2011-01-01

    Pseudoangiomatous stromal hyperplasia is a benign proliferative lesion of the mammary stroma that rarely presents as a localized mass. Pseudoangiomatous stromal hyperplasia is characterized by a dense, collagenous proliferation of the mammary stroma, associated with capillary-like spaces. Pseudoangiomatous stromal hyperplasia can be mistaken with fibroadenoma on radiological examination or with low-grade angiosarcoma on histological examination. Its main importance is its distinction from angiosarcoma. The presented case was a 40-year-old woman who was admitted with a rapidly growing breast tumor. Physical examination revealed an elastic-firm, well-defined, mobile and painless mass in her right breast. Mammograms revealed a 6.7 x 3.7 cm, lobulated, well-circumscribed mass in her right breast but no calcification. Sonographic examination showed a well-defined and homogenous mass, not including any cyst. Based on these findings, a provisional diagnosis of fibroadenoma was made. Considering the rapid growth history of the mass, tumor excision was performed. The excised tumor was well demarcated and had a smooth external surface. Histological examination revealed the tumor to be composed of markedly increased fibrous stroma and scattered epithelial components (cystic dilatation of the ducts, blunt duct adenosis). The fibrous stroma contained numerous anastomosing slit-like spaces. Isolated spindle cells appeared intermittently at the margins of the spaces resembled endothelial cells. Immunohistochemical staining showed that the spindle cells were positive for CD34 and negative for Factor VIII-related antigen. The lesion was diagnosed as nodular pseudoangiomatous stromal hyperplasia.

  17. Objectness Supervised Merging Algorithm for Color Image Segmentation

    Directory of Open Access Journals (Sweden)

    Haifeng Sima

    2016-01-01

    Full Text Available Ideal color image segmentation needs both low-level cues and high-level semantic features. This paper proposes a two-hierarchy segmentation model based on merging homogeneous superpixels. First, a region growing strategy is designed for producing homogenous and compact superpixels in different partitions. Total variation smoothing features are adopted in the growing procedure for locating real boundaries. Before merging, we define a combined color-texture histogram feature for superpixels description and, meanwhile, a novel objectness feature is proposed to supervise the region merging procedure for reliable segmentation. Both color-texture histograms and objectness are computed to measure regional similarities between region pairs, and the mixed standard deviation of the union features is exploited to make stop criteria for merging process. Experimental results on the popular benchmark dataset demonstrate the better segmentation performance of the proposed model compared to other well-known segmentation algorithms.

  18. Pancreas and cyst segmentation

    Science.gov (United States)

    Dmitriev, Konstantin; Gutenko, Ievgeniia; Nadeem, Saad; Kaufman, Arie

    2016-03-01

    Accurate segmentation of abdominal organs from medical images is an essential part of surgical planning and computer-aided disease diagnosis. Many existing algorithms are specialized for the segmentation of healthy organs. Cystic pancreas segmentation is especially challenging due to its low contrast boundaries, variability in shape, location and the stage of the pancreatic cancer. We present a semi-automatic segmentation algorithm for pancreata with cysts. In contrast to existing automatic segmentation approaches for healthy pancreas segmentation which are amenable to atlas/statistical shape approaches, a pancreas with cysts can have even higher variability with respect to the shape of the pancreas due to the size and shape of the cyst(s). Hence, fine results are better attained with semi-automatic steerable approaches. We use a novel combination of random walker and region growing approaches to delineate the boundaries of the pancreas and cysts with respective best Dice coefficients of 85.1% and 86.7%, and respective best volumetric overlap errors of 26.0% and 23.5%. Results show that the proposed algorithm for pancreas and pancreatic cyst segmentation is accurate and stable.

  19. Parallelized Seeded Region Growing Using CUDA

    Directory of Open Access Journals (Sweden)

    Seongjin Park

    2014-01-01

    Full Text Available This paper presents a novel method for parallelizing the seeded region growing (SRG algorithm using Compute Unified Device Architecture (CUDA technology, with intention to overcome the theoretical weakness of SRG algorithm of its computation time being directly proportional to the size of a segmented region. The segmentation performance of the proposed CUDA-based SRG is compared with SRG implementations on single-core CPUs, quad-core CPUs, and shader language programming, using synthetic datasets and 20 body CT scans. Based on the experimental results, the CUDA-based SRG outperforms the other three implementations, advocating that it can substantially assist the segmentation during massive CT screening tests.

  20. Spatio-Temporal Video Segmentation with Shape Growth or Shrinkage Constraint

    Science.gov (United States)

    Tarabalka, Yuliya; Charpiat, Guillaume; Brucker, Ludovic; Menze, Bjoern H.

    2014-01-01

    We propose a new method for joint segmentation of monotonously growing or shrinking shapes in a time sequence of noisy images. The task of segmenting the image time series is expressed as an optimization problem using the spatio-temporal graph of pixels, in which we are able to impose the constraint of shape growth or of shrinkage by introducing monodirectional infinite links connecting pixels at the same spatial locations in successive image frames. The globally optimal solution is computed with a graph cut. The performance of the proposed method is validated on three applications: segmentation of melting sea ice floes and of growing burned areas from time series of 2D satellite images, and segmentation of a growing brain tumor from sequences of 3D medical scans. In the latter application, we impose an additional intersequences inclusion constraint by adding directed infinite links between pixels of dependent image structures.

  1. Hierarchical Image Segmentation of Remotely Sensed Data using Massively Parallel GNU-LINUX Software

    Science.gov (United States)

    Tilton, James C.

    2003-01-01

    A hierarchical set of image segmentations is a set of several image segmentations of the same image at different levels of detail in which the segmentations at coarser levels of detail can be produced from simple merges of regions at finer levels of detail. In [1], Tilton, et a1 describes an approach for producing hierarchical segmentations (called HSEG) and gave a progress report on exploiting these hierarchical segmentations for image information mining. The HSEG algorithm is a hybrid of region growing and constrained spectral clustering that produces a hierarchical set of image segmentations based on detected convergence points. In the main, HSEG employs the hierarchical stepwise optimization (HSWO) approach to region growing, which was described as early as 1989 by Beaulieu and Goldberg. The HSWO approach seeks to produce segmentations that are more optimized than those produced by more classic approaches to region growing (e.g. Horowitz and T. Pavlidis, [3]). In addition, HSEG optionally interjects between HSWO region growing iterations, merges between spatially non-adjacent regions (i.e., spectrally based merging or clustering) constrained by a threshold derived from the previous HSWO region growing iteration. While the addition of constrained spectral clustering improves the utility of the segmentation results, especially for larger images, it also significantly increases HSEG s computational requirements. To counteract this, a computationally efficient recursive, divide-and-conquer, implementation of HSEG (RHSEG) was devised, which includes special code to avoid processing artifacts caused by RHSEG s recursive subdivision of the image data. The recursive nature of RHSEG makes for a straightforward parallel implementation. This paper describes the HSEG algorithm, its recursive formulation (referred to as RHSEG), and the implementation of RHSEG using massively parallel GNU-LINUX software. Results with Landsat TM data are included comparing RHSEG with classic

  2. Reflection symmetry-integrated image segmentation.

    Science.gov (United States)

    Sun, Yu; Bhanu, Bir

    2012-09-01

    This paper presents a new symmetry-integrated region-based image segmentation method. The method is developed to obtain improved image segmentation by exploiting image symmetry. It is realized by constructing a symmetry token that can be flexibly embedded into segmentation cues. Interesting points are initially extracted from an image by the SIFT operator and they are further refined for detecting the global bilateral symmetry. A symmetry affinity matrix is then computed using the symmetry axis and it is used explicitly as a constraint in a region growing algorithm in order to refine the symmetry of the segmented regions. A multi-objective genetic search finds the segmentation result with the highest performance for both segmentation and symmetry, which is close to the global optimum. The method has been investigated experimentally in challenging natural images and images containing man-made objects. It is shown that the proposed method outperforms current segmentation methods both with and without exploiting symmetry. A thorough experimental analysis indicates that symmetry plays an important role as a segmentation cue, in conjunction with other attributes like color and texture.

  3. AUTOMATIC LUNG NODULE SEGMENTATION USING AUTOSEED REGION GROWING WITH MORPHOLOGICAL MASKING (ARGMM AND FEATURE EX-TRACTION THROUGH COMPLETE LOCAL BINARY PATTERN AND MICROSCOPIC INFORMATION PATTERN

    Directory of Open Access Journals (Sweden)

    Senthil Kumar

    2015-04-01

    Full Text Available An efficient Autoseed Region Growing with Morphological Masking(ARGMM is imple-mented in this paper on the Lung CT Slice to segment the 'Lung Nodules',which may be the potential indicator for the Lung Cancer. The segmentation of lung nodules car-ried out in this paper through Multi-Thresholding, ARGMM and Level Set Evolution. ARGMM takes twice the time compared to Level Set, but still the number of suspected segmented nodules are doubled, which make sure that no potential cancerous nodules go unnoticed at the earlier stages of diagnosis. It is very important not to panic the patient by finding the presence of nodules from Lung CT scan. Only 40 percent of nod-ules can be cancerous. Hence, in this paper an efficient Shape and Texture analysis is computed to quantitatively describe the segmented lung nodules. The Frequency spectrum of the lung nodules is developed and its frequency domain features are com-puted. The Complete Local binary pattern of lung nodules is computed in this paper by constructing the combine histogram of Sign and Magnitude Local Binary Patterns. Lo-cal Configuration Pattern is also determined in this work for lung nodules to numeri-cally model the microscopic information of nodules pattern.

  4. Market segmentation in tourism: An application of the Schwartz's value theory

    Directory of Open Access Journals (Sweden)

    Veljković Saša

    2015-01-01

    Full Text Available Tourism is one of the fastest growing economic sectors. As nowdays tourism market is characterized by rapid changes and strong competition, the struggle for tourists represents everyday issue which tourist entities face with. In the past few decades, tourism demand has significantly been changed. From the unified and mass, it has become highly informed, personalized, with different individual requirements and preferences. Market segmentation occurs as an inevitable process in delivering appropriate value to tourists. To achieve better business outcomes, tourism businesses are looking for ways to make their offer suitable for tourists needs. The aim of this paper is to show if there is an impact of the value system on the consumer decision-making in choosing travel arrangements. The survey was conducted on a sample of 168 respondents, who were primarily selected from the population of students of the University of Belgrade. In order to answer the research questions, Schwartz's system of values model was used. Thus defined value system was used as the basis for segmentation of the tourist market. The survey showed that based on such segmentation, tourist can be divided into four clusters: 'individualists', 'modest traditionalists', 'hedonists' and 'social adventurers'.

  5. Rapid urbanization and the growing threat of violence and conflict: a 21st century crisis.

    Science.gov (United States)

    Patel, Ronak B; Burkle, Frederick M

    2012-04-01

    As the global population is concentrated into complex environments, rapid urbanization increases the threat of conflict and insecurity. Many fast-growing cities create conditions of significant disparities in standards of living, which set up a natural environment for conflict over resources. As urban slums become a haven for criminal elements, youth gangs, and the arms trade, they also create insecurity for much of the population. Specific populations, such as women, migrants, and refugees, bear the brunt of this lack of security, with significant impacts on their livelihoods, health, and access to basic services. This lack of security and violence also has great costs to the general population, both economic and social. Cities have increasingly become the battlefield of recent conflicts as they serve as the seats of power and gateways to resources. International agencies, non-governmental organizations, and policy-makers must act to stem this tide of growing urban insecurity. Protecting urban populations and preventing future conflict will require better urban planning, investment in livelihood programs for youth, cooperation with local communities, enhanced policing, and strengthening the capacity of judicial systems.

  6. A state-of-the-art review on segmentation algorithms in intravascular ultrasound (IVUS) images.

    Science.gov (United States)

    Katouzian, Amin; Angelini, Elsa D; Carlier, Stéphane G; Suri, Jasjit S; Navab, Nassir; Laine, Andrew F

    2012-09-01

    Over the past two decades, intravascular ultrasound (IVUS) image segmentation has remained a challenge for researchers while the use of this imaging modality is rapidly growing in catheterization procedures and in research studies. IVUS provides cross-sectional grayscale images of the arterial wall and the extent of atherosclerotic plaques with high spatial resolution in real time. In this paper, we review recently developed image processing methods for the detection of media-adventitia and luminal borders in IVUS images acquired with different transducers operating at frequencies ranging from 20 to 45 MHz. We discuss methodological challenges, lack of diversity in reported datasets, and weaknesses of quantification metrics that make IVUS segmentation still an open problem despite all efforts. In conclusion, we call for a common reference database, validation metrics, and ground-truth definition with which new and existing algorithms could be benchmarked.

  7. Rapidly Growing Esophageal Carcinosarcoma Reduced by Neoadjuvant Radiotherapy Alone

    Directory of Open Access Journals (Sweden)

    Naotaka Ogasawara

    2014-06-01

    Full Text Available Esophageal carcinosarcoma is a rare malignant neoplasm consisting of both carcinomatous and sarcomatous components. It is generally treated by surgery, radiotherapy and chemotherapy according to the protocols used for other esophageal cancers. However, the treatment of esophageal carcinosarcoma by radiotherapy alone before surgery has not been previously described. We report a patient with a rapidly growing esophageal carcinosarcoma that was efficiently reduced by neoadjuvant radiotherapy alone. A previously healthy 69-year-old man was admitted with dysphagia. Initial esophagogastroduodenoscopy (EGD revealed a small nodular polypoid lesion of about 10 mm in the middle esophagus. A second EGD 1 month later showed that the tumor had expanded into a huge mass. A biopsy specimen revealed that the tumor comprised squamous cell carcinoma with spindle cell components, and the tumor was diagnosed as carcinosarcoma which was diagnosed as stage I (T1bN0M0. Due to renal dysfunction, the patient was treated with neoadjuvant radiotherapy (40 Gy without chemotherapy. A third EGD 1 month later revealed remarkable tumor reduction. He then underwent total esophagectomy with regional lymph node dissection (pStage 0, pT1aN0M0. After surgical operation, the patient was followed up without adjuvant therapy. Whole body computed tomography revealed lung metastasis 14 months after surgery, and the patient died 2 months later. The neoadjuvant radiotherapy for esophageal carcinosarcoma was considered to have contributed to the subsequent surgery and his prolonged survival time. Thus, radiotherapy alone might be a suitable neoadjuvant therapy for esophageal carcinosarcomas.

  8. Segmentation Technique for Image Indexing and Retrieval on Discrete Cosines Domain

    Directory of Open Access Journals (Sweden)

    Suhendro Yusuf Irianto

    2013-03-01

    Full Text Available This paper uses region growing segmentation technique to segment the Discrete Cosines (DC  image. The problem of content Based image retrieval (CBIR is the luck of accuracy in matching between image query and image in the database as it matches object and background in the same time.   This the reason previous CBIR techniques inaccurate and time consuming. The CBIR   based on the segmented region proposed in this work  separates object from background as CBIR need only match the object not the background.  By using region growing technique on DC image, it reduces the number of image       regions.    The proposed of recursive region growing is not new technique but its application on DC images to build    indexing keys is quite new and not yet presented by many     authors. The experimental results show  that the proposed methods on   segmented images present good precision which are higher than 0.60 on all classes . It can be concluded that  region growing segmented based CBIR more efficient    compare to DC images  in term of their precision 0.59 and 0.75, respectively. Moreover,  DC based CBIR  can save time and simplify algorithm compare to DCT images.

  9. Aquaculture: a rapidly growing and significant source of sustainable food? Status, transitions and potential.

    Science.gov (United States)

    Little, D C; Newton, R W; Beveridge, M C M

    2016-08-01

    The status and potential of aquaculture is considered as part of a broader food landscape of wild aquatic and terrestrial food sources. The rationale and resource base required for the development of aquaculture are considered in the context of broader societal development, cultural preferences and human needs. Attention is drawn to the uneven development and current importance of aquaculture globally as well as its considerable heterogeneity of form and function compared with established terrestrial livestock production. The recent drivers of growth in demand and production are examined and the persistent linkages between exploitation of wild stocks, full life cycle culture and the various intermediate forms explored. An emergent trend for sourcing aquaculture feeds from alternatives to marine ingredients is described and the implications for the sector with rapidly growing feed needs discussed. The rise of non-conventional and innovative feed ingredients, often shared with terrestrial livestock, are considered, including aquaculture itself becoming a major source of marine ingredients. The implications for the continued expected growth of aquaculture are set in the context of sustainable intensification, with the challenges that conventional intensification and emergent integration within, and between, value chains explored. The review concludes with a consideration of the implications for dependent livelihoods and projections for various futures based on limited resources but growing demand.

  10. ISOLATION AND ANTIBIOTIC SUSCEPTIBILITY TESTING OF RAPIDLY-GROWING MYCOBACTERIA FROM GRASSLAND SOILS

    Directory of Open Access Journals (Sweden)

    Martina Kyselková

    2013-08-01

    Full Text Available Rapidly growing mycobacteria (RGM are common soil saprophytes, but certain strains cause infections in human and animals. The infections due to RGM have been increasing in past decades and are often difficult to treat. The susceptibility to antibiotics is regularly evaluated in clinical isolates of RGM, but the data on soil RGM are missing. The objectives of this study was to isolate RGM from four grassland soils with different impact of manuring, and assess their resistance to antibiotics and the ability to grow at 37°C and 42°C. Since isolation of RGM from soil is a challenge, a conventional decontamination method (NaOH/malachite green/cycloheximide and a recent method based on olive oil/SDS demulsification were compared. The olive oil/SDS method was less efficient, mainly because of the emulsion instability and plate overgrowing with other bacteria. Altogether, 44 isolates were obtained and 23 representatives of different RGM genotypes were screened. The number of isolates per soil decreased with increasing soil pH, consistently with previous findings that mycobacteria were more abundant in low pH soils. Most of the isolates belonged to the Mycobacterium fortuitum group. The majority of isolates was resistant to 2-4 antibiotics. Multiresistant strains occurred also in a control soil that has a long history without the exposure to antibiotic-containing manure. Seven isolates grew at 37°C, including the species M. septicum and M. fortuitum known for infections in humans. This study shows that multiresistant RGM close to known human pathogens occur in grassland soils regardless the soil history of manuring.

  11. Segmentation of knee injury swelling on infrared images

    Science.gov (United States)

    Puentes, John; Langet, Hélène; Herry, Christophe; Frize, Monique

    2011-03-01

    Interpretation of medical infrared images is complex due to thermal noise, absence of texture, and small temperature differences in pathological zones. Acute inflammatory response is a characteristic symptom of some knee injuries like anterior cruciate ligament sprains, muscle or tendons strains, and meniscus tear. Whereas artificial coloring of the original grey level images may allow to visually assess the extent inflammation in the area, their automated segmentation remains a challenging problem. This paper presents a hybrid segmentation algorithm to evaluate the extent of inflammation after knee injury, in terms of temperature variations and surface shape. It is based on the intersection of rapid color segmentation and homogeneous region segmentation, to which a Laplacian of a Gaussian filter is applied. While rapid color segmentation enables to properly detect the observed core of swollen area, homogeneous region segmentation identifies possible inflammation zones, combining homogeneous grey level and hue area segmentation. The hybrid segmentation algorithm compares the potential inflammation regions partially detected by each method to identify overlapping areas. Noise filtering and edge segmentation are then applied to common zones in order to segment the swelling surfaces of the injury. Experimental results on images of a patient with anterior cruciate ligament sprain show the improved performance of the hybrid algorithm with respect to its separated components. The main contribution of this work is a meaningful automatic segmentation of abnormal skin temperature variations on infrared thermography images of knee injury swelling.

  12. Nosocomial rapidly growing mycobacterial infections following laparoscopic surgery: CT imaging findings

    Energy Technology Data Exchange (ETDEWEB)

    Volpato, Richard [Cassiano Antonio de Moraes University Hospital, Department of Diagnostic Radiology, Vitoria, ES (Brazil); Campi de Castro, Claudio [University of Sao Paulo Medical School, Department of Radiology, Cerqueira Cesar, Sao Paulo (Brazil); Hadad, David Jamil [Cassiano Antonio de Moraes University Hospital, Nucleo de Doencas Infecciosas, Department of Internal Medicine, Vitoria, ES (Brazil); Silva Souza Ribeiro, Flavya da [Laboratorio de Patologia PAT, Department of Diagnostic Radiology, Unit 1473, Vitoria, ES (Brazil); Filho, Ezequiel Leal [UNIMED Diagnostico, Department of Diagnostic Radiology, Unit 1473, Vitoria, ES (Brazil); Marcal, Leonardo P. [The University of Texas M D Anderson Cancer Center, Department of Diagnostic Radiology, Unit 1473, Houston, TX (United States)

    2015-09-15

    To identify the distribution and frequency of computed tomography (CT) findings in patients with nosocomial rapidly growing mycobacterial (RGM) infection after laparoscopic surgery. A descriptive retrospective study in patients with RGM infection after laparoscopic surgery who underwent CT imaging prior to initiation of therapy. The images were analyzed by two radiologists in consensus, who evaluated the skin/subcutaneous tissues, the abdominal wall, and intraperitoneal region separately. The patterns of involvement were tabulated as: densification, collections, nodules (≥1.0 cm), small nodules (<1.0 cm), pseudocavitated nodules, and small pseudocavitated nodules. Twenty-six patients met the established criteria. The subcutaneous findings were: densification (88.5 %), small nodules (61.5 %), small pseudocavitated nodules (23.1 %), nodules (38.5 %), pseudocavitated nodules (15.4 %), and collections (26.9 %). The findings in the abdominal wall were: densification (61.5 %), pseudocavitated nodules (3.8 %), and collections (15.4 %). The intraperitoneal findings were: densification (46.1 %), small nodules (42.3 %), nodules (15.4 %), and collections (11.5 %). Subcutaneous CT findings in descending order of frequency were: densification, small nodules, nodules, small pseudocavitated nodules, pseudocavitated nodules, and collections. The musculo-fascial plane CT findings were: densification, collections, and pseudocavitated nodules. The intraperitoneal CT findings were: densification, small nodules, nodules, and collections. (orig.)

  13. Nosocomial rapidly growing mycobacterial infections following laparoscopic surgery: CT imaging findings

    International Nuclear Information System (INIS)

    Volpato, Richard; Campi de Castro, Claudio; Hadad, David Jamil; Silva Souza Ribeiro, Flavya da; Filho, Ezequiel Leal; Marcal, Leonardo P.

    2015-01-01

    To identify the distribution and frequency of computed tomography (CT) findings in patients with nosocomial rapidly growing mycobacterial (RGM) infection after laparoscopic surgery. A descriptive retrospective study in patients with RGM infection after laparoscopic surgery who underwent CT imaging prior to initiation of therapy. The images were analyzed by two radiologists in consensus, who evaluated the skin/subcutaneous tissues, the abdominal wall, and intraperitoneal region separately. The patterns of involvement were tabulated as: densification, collections, nodules (≥1.0 cm), small nodules (<1.0 cm), pseudocavitated nodules, and small pseudocavitated nodules. Twenty-six patients met the established criteria. The subcutaneous findings were: densification (88.5 %), small nodules (61.5 %), small pseudocavitated nodules (23.1 %), nodules (38.5 %), pseudocavitated nodules (15.4 %), and collections (26.9 %). The findings in the abdominal wall were: densification (61.5 %), pseudocavitated nodules (3.8 %), and collections (15.4 %). The intraperitoneal findings were: densification (46.1 %), small nodules (42.3 %), nodules (15.4 %), and collections (11.5 %). Subcutaneous CT findings in descending order of frequency were: densification, small nodules, nodules, small pseudocavitated nodules, pseudocavitated nodules, and collections. The musculo-fascial plane CT findings were: densification, collections, and pseudocavitated nodules. The intraperitoneal CT findings were: densification, small nodules, nodules, and collections. (orig.)

  14. Hyperspectral image analysis for rapid and accurate discrimination of bacterial infections: A benchmark study.

    Science.gov (United States)

    Arrigoni, Simone; Turra, Giovanni; Signoroni, Alberto

    2017-09-01

    With the rapid diffusion of Full Laboratory Automation systems, Clinical Microbiology is currently experiencing a new digital revolution. The ability to capture and process large amounts of visual data from microbiological specimen processing enables the definition of completely new objectives. These include the direct identification of pathogens growing on culturing plates, with expected improvements in rapid definition of the right treatment for patients affected by bacterial infections. In this framework, the synergies between light spectroscopy and image analysis, offered by hyperspectral imaging, are of prominent interest. This leads us to assess the feasibility of a reliable and rapid discrimination of pathogens through the classification of their spectral signatures extracted from hyperspectral image acquisitions of bacteria colonies growing on blood agar plates. We designed and implemented the whole data acquisition and processing pipeline and performed a comprehensive comparison among 40 combinations of different data preprocessing and classification techniques. High discrimination performance has been achieved also thanks to improved colony segmentation and spectral signature extraction. Experimental results reveal the high accuracy and suitability of the proposed approach, driving the selection of most suitable and scalable classification pipelines and stimulating clinical validations. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. The evaluation of service delivery in the fast growing black diamond market / R. Venter

    OpenAIRE

    Venter, Raymano

    2010-01-01

    The black middle–class market segment also known as the black diamond market segment has shown immense growth in SA. It currently consists of approximately 3 million black middle–class South Africans with a buying power of approximately R200 billion. Despite the immense size and spending power of black diamonds, combined with its rapid growth over the past 15 years and expected future growth, little research has been conducted on this market segment. The rapid market growth ...

  16. Vessel-guided airway tree segmentation

    DEFF Research Database (Denmark)

    Lo, Pechin Chien Pau; Sporring, Jon; Ashraf, Haseem

    2010-01-01

    This paper presents a method for airway tree segmentation that uses a combination of a trained airway appearance model, vessel and airway orientation information, and region growing. We propose a voxel classification approach for the appearance model, which uses a classifier that is trained to di...

  17. A kind of color image segmentation algorithm based on super-pixel and PCNN

    Science.gov (United States)

    Xu, GuangZhu; Wang, YaWen; Zhang, Liu; Zhao, JingJing; Fu, YunXia; Lei, BangJun

    2018-04-01

    Image segmentation is a very important step in the low-level visual computing. Although image segmentation has been studied for many years, there are still many problems. PCNN (Pulse Coupled Neural network) has biological background, when it is applied to image segmentation it can be viewed as a region-based method, but due to the dynamics properties of PCNN, many connectionless neurons will pulse at the same time, so it is necessary to identify different regions for further processing. The existing PCNN image segmentation algorithm based on region growing is used for grayscale image segmentation, cannot be directly used for color image segmentation. In addition, the super-pixel can better reserve the edges of images, and reduce the influences resulted from the individual difference between the pixels on image segmentation at the same time. Therefore, on the basis of the super-pixel, the original PCNN algorithm based on region growing is improved by this paper. First, the color super-pixel image was transformed into grayscale super-pixel image which was used to seek seeds among the neurons that hadn't been fired. And then it determined whether to stop growing by comparing the average of each color channel of all the pixels in the corresponding regions of the color super-pixel image. Experiment results show that the proposed algorithm for the color image segmentation is fast and effective, and has a certain effect and accuracy.

  18. The spatial biology of transcription and translation in rapidly growing Escherichia coli

    Directory of Open Access Journals (Sweden)

    Somenath eBakshi

    2015-07-01

    Full Text Available Single-molecule fluorescence provides high resolution spatial distributions of ribosomes and RNA polymerase (RNAP in live, rapidly growing E. coli. Ribosomes are more strongly segregated from the nucleoids (chromosomal DNA than previous widefield fluorescence studies suggested. While most transcription may be co-translational, the evidence indicates that most translation occurs on free mRNA copies that have diffused from the nucleoids to a ribosome-rich region. Analysis of time-resolved images of the nucleoid spatial distribution after treatment with the transcription-halting drug rifampicin and the translation-halting drug chloramphenicol shows that both drugs cause nucleoid contraction on the 0-3 min timescale. This is consistent with the transertion hypothesis. We suggest that the longer-term (20-30 min nucleoid expansion after Rif treatment arises from conversion of 70S-polysomes to 30S and 50S subunits, which readily penetrate the nucleoids. Monte Carlo simulations of a polymer bead model built to mimic the chromosomal DNA and ribosomes (either 70S-polysomes or 30S and 50S subunits explain spatial segregation or mixing of ribosomes and nucleoids in terms of excluded volume and entropic effects alone. A comprehensive model of the transcription-translation-transertion system incorporates this new information about the spatial organization of the E. coli cytoplasm. We propose that transertion, which radially expands the nucleoids, is essential for recycling of 30S and 50S subunits from ribosome-rich regions back into the nucleoids. There they initiate co-transcriptional translation, which is an important mechanism for maintaining RNAP forward progress and protecting the nascent mRNA chain. Segregation of 70S-polysomes from the nucleoid may facilitate rapid growth by shortening the search time for ribosomes to find free mRNA concentrated outside the nucleoid and the search time for RNAP concentrated within the nucleoid to find transcription

  19. Reducing the random seed effect on segmentation by applying an edge-preserving filter

    NARCIS (Netherlands)

    Addink, E.A.

    2012-01-01

    In region-growing segmentation algorithms random seed locations are used (reference). To ensure that repeating the segmentation will produce the same result, the seed locations are following a fixed random pattern. Empirical studies show that when the image that is subjected to the segmentation is

  20. Leaf segmentation in plant phenotyping

    NARCIS (Netherlands)

    Scharr, Hanno; Minervini, Massimo; French, Andrew P.; Klukas, Christian; Kramer, David M.; Liu, Xiaoming; Luengo, Imanol; Pape, Jean Michel; Polder, Gerrit; Vukadinovic, Danijela; Yin, Xi; Tsaftaris, Sotirios A.

    2016-01-01

    Image-based plant phenotyping is a growing application area of computer vision in agriculture. A key task is the segmentation of all individual leaves in images. Here we focus on the most common rosette model plants, Arabidopsis and young tobacco. Although leaves do share appearance and shape

  1. Comparing Individual Tree Segmentation Based on High Resolution Multispectral Image and Lidar Data

    Science.gov (United States)

    Xiao, P.; Kelly, M.; Guo, Q.

    2014-12-01

    This study compares the use of high-resolution multispectral WorldView images and high density Lidar data for individual tree segmentation. The application focuses on coniferous and deciduous forests in the Sierra Nevada Mountains. The tree objects are obtained in two ways: a hybrid region-merging segmentation method with multispectral images, and a top-down and bottom-up region-growing method with Lidar data. The hybrid region-merging method is used to segment individual tree from multispectral images. It integrates the advantages of global-oriented and local-oriented region-merging strategies into a unified framework. The globally most-similar pair of regions is used to determine the starting point of a growing region. The merging iterations are constrained within the local vicinity, thus the segmentation is accelerated and can reflect the local context. The top-down region-growing method is adopted in coniferous forest to delineate individual tree from Lidar data. It exploits the spacing between the tops of trees to identify and group points into a single tree based on simple rules of proximity and likely tree shape. The bottom-up region-growing method based on the intensity and 3D structure of Lidar data is applied in deciduous forest. It segments tree trunks based on the intensity and topological relationships of the points, and then allocate other points to exact tree crowns according to distance. The accuracies for each method are evaluated with field survey data in several test sites, covering dense and sparse canopy. Three types of segmentation results are produced: true positive represents a correctly segmented individual tree, false negative represents a tree that is not detected and assigned to a nearby tree, and false positive represents that a point or pixel cluster is segmented as a tree that does not in fact exist. They respectively represent correct-, under-, and over-segmentation. Three types of index are compared for segmenting individual tree

  2. Automated grain extraction and classification by combining improved region growing segmentation and shape descriptors in electromagnetic mill classification system

    Science.gov (United States)

    Budzan, Sebastian

    2018-04-01

    In this paper, the automatic method of grain detection and classification has been presented. As input, it uses a single digital image obtained from milling process of the copper ore with an high-quality digital camera. The grinding process is an extremely energy and cost consuming process, thus granularity evaluation process should be performed with high efficiency and time consumption. The method proposed in this paper is based on the three-stage image processing. First, using Seeded Region Growing (SRG) segmentation with proposed adaptive thresholding based on the calculation of Relative Standard Deviation (RSD) all grains are detected. In the next step results of the detection are improved using information about the shape of the detected grains using distance map. Finally, each grain in the sample is classified into one of the predefined granularity class. The quality of the proposed method has been obtained by using nominal granularity samples, also with a comparison to the other methods.

  3. Superpixel-based segmentation of glottal area from videolaryngoscopy images

    Science.gov (United States)

    Turkmen, H. Irem; Albayrak, Abdulkadir; Karsligil, M. Elif; Kocak, Ismail

    2017-11-01

    Segmentation of the glottal area with high accuracy is one of the major challenges for the development of systems for computer-aided diagnosis of vocal-fold disorders. We propose a hybrid model combining conventional methods with a superpixel-based segmentation approach. We first employed a superpixel algorithm to reveal the glottal area by eliminating the local variances of pixels caused by bleedings, blood vessels, and light reflections from mucosa. Then, the glottal area was detected by exploiting a seeded region-growing algorithm in a fully automatic manner. The experiments were conducted on videolaryngoscopy images obtained from both patients having pathologic vocal folds as well as healthy subjects. Finally, the proposed hybrid approach was compared with conventional region-growing and active-contour model-based glottal area segmentation algorithms. The performance of the proposed method was evaluated in terms of segmentation accuracy and elapsed time. The F-measure, true negative rate, and dice coefficients of the hybrid method were calculated as 82%, 93%, and 82%, respectively, which are superior to the state-of-art glottal-area segmentation methods. The proposed hybrid model achieved high success rates and robustness, making it suitable for developing a computer-aided diagnosis system that can be used in clinical routines.

  4. Active Mask Segmentation of Fluorescence Microscope Images

    OpenAIRE

    Srinivasa, Gowri; Fickus, Matthew C.; Guo, Yusong; Linstedt, Adam D.; Kovačević, Jelena

    2009-01-01

    We propose a new active mask algorithm for the segmentation of fluorescence microscope images of punctate patterns. It combines the (a) flexibility offered by active-contour methods, (b) speed offered by multiresolution methods, (c) smoothing offered by multiscale methods, and (d) statistical modeling offered by region-growing methods into a fast and accurate segmentation tool. The framework moves from the idea of the “contour” to that of “inside and outside”, or, masks, allowing for easy mul...

  5. Segmentasi Pembuluh Darah Retina Pada Citra Fundus Menggunakan Gradient Based Adaptive Thresholding Dan Region Growing

    Directory of Open Access Journals (Sweden)

    Deni Sutaji

    2016-07-01

    , segmentasi. AbstractSegmentation of blood vessels in the retina fundus image becomes substantial in the medical, because it can be used to detect diseases, such as diabetic retinopathy, hypertension, and cardiovascular. Doctor takes about two hours to detect the blood vessels of the retina, so screening methods are needed to make it faster. The previous methods are able to segment the blood vessels that are sensitive to variations in the size of the width of blood vessels, but there is over-segmentation in the area of pathology. Therefore, this study aims to develop a segmentation method of blood vessels in retinal fundus images which can reduce over-segmentation in the area of pathology using Gradient Based Adaptive Thresholding and Region Growing. The proposed method consists of three stages, namely the segmentation of the main blood vessels, detection area of pathology and segmentation thin blood vessels. Main blood vessels segmentation using high-pass filtering and tophat reconstruction on the green channel which adjusted of contras image that results the clearly between object and background. Detection area of pathology using Gradient Based Adaptive thresholding method. Thin blood vessels segmentation using Region Growing based on the information main blood vessel segmentation and detection of pathology area. Output of the main blood vessel segmentation and thin blood vessels are then combined to reconstruct an image of the blood vessels as output system.This method is able to segment the blood vessels in retinal fundus images DRIVE with an accuracy of 95.25% and the value of Area Under Curve (AUC in the relative operating characteristic curve (ROC of 74.28%.Keywords: Blood vessel, fundus retina image, gradient based adaptive thresholding, pathology, region growing, segmentation.

  6. User Interaction in Semi-Automatic Segmentation of Organs at Risk: a Case Study in Radiotherapy

    NARCIS (Netherlands)

    A. Ramkumar (Anjana); J. Dolz (Jose); H.A. Kirisli (Hortense); S. Adebahr (Sonja); T. Schimek-Jasch (Tanja); U. Nestle (Ursula); L. Massoptier (Laurent); E. Varga (Edit); P.J. Stappers (P.); W.J. Niessen (Wiro); Y. Song (Yu)

    2016-01-01

    textabstractAccurate segmentation of organs at risk is an important step in radiotherapy planning. Manual segmentation being a tedious procedure and prone to inter- and intra-observer variability, there is a growing interest in automated segmentation methods. However, automatic methods frequently

  7. Multiscale Vessel-guided Airway Tree Segmentation

    DEFF Research Database (Denmark)

    Lo, Pechin Chien Pau; Sporring, Jon; de Bruijne, Marleen

    2009-01-01

    This paper presents a method for airway tree segmentation that uses a combination of a trained airway appearance model, vessel and airway orientation information, and region growing. The method uses a voxel classification based appearance model, which involves the use of a classifier that is trai...

  8. User Interaction in Semi-Automatic Segmentation of Organs at Risk : A Case Study in Radiotherapy

    NARCIS (Netherlands)

    Ramkumar, A.; Dolz, J.; Kirisli, H.A.; Adebahr, S.; Schimek-Jasch, T.; Nestle, U.; Massoptier, L.; Varga, E.; Stappers, P.J.; Niessen, W.J.; Song, Y.

    2015-01-01

    Accurate segmentation of organs at risk is an important step in radiotherapy planning. Manual segmentation being a tedious procedure and prone to inter- and intra-observer variability, there is a growing interest in automated segmentation methods. However, automatic methods frequently fail to

  9. An Ensemble of 2D Convolutional Neural Networks for Tumor Segmentation

    DEFF Research Database (Denmark)

    Lyksborg, Mark; Puonti, Oula; Agn, Mikael

    2015-01-01

    Accurate tumor segmentation plays an important role in radiosurgery planning and the assessment of radiotherapy treatment efficacy. In this paper we propose a method combining an ensemble of 2D convolutional neural networks for doing a volumetric segmentation of magnetic resonance images....... The segmentation is done in three steps; first the full tumor region, is segmented from the background by a voxel-wise merging of the decisions of three networks learned from three orthogonal planes, next the segmentation is refined using a cellular automaton-based seed growing method known as growcut. Finally......, within-tumor sub-regions are segmented using an additional ensemble of networks trained for the task. We demonstrate the method on the MICCAI Brain Tumor Segmentation Challenge dataset of 2014, and show improved segmentation accuracy compared to an axially trained 2D network and an ensemble segmentation...

  10. A three-dimensional image processing program for accurate, rapid, and semi-automated segmentation of neuronal somata with dense neurite outgrowth

    Science.gov (United States)

    Ross, James D.; Cullen, D. Kacy; Harris, James P.; LaPlaca, Michelle C.; DeWeerth, Stephen P.

    2015-01-01

    Three-dimensional (3-D) image analysis techniques provide a powerful means to rapidly and accurately assess complex morphological and functional interactions between neural cells. Current software-based identification methods of neural cells generally fall into two applications: (1) segmentation of cell nuclei in high-density constructs or (2) tracing of cell neurites in single cell investigations. We have developed novel methodologies to permit the systematic identification of populations of neuronal somata possessing rich morphological detail and dense neurite arborization throughout thick tissue or 3-D in vitro constructs. The image analysis incorporates several novel automated features for the discrimination of neurites and somata by initially classifying features in 2-D and merging these classifications into 3-D objects; the 3-D reconstructions automatically identify and adjust for over and under segmentation errors. Additionally, the platform provides for software-assisted error corrections to further minimize error. These features attain very accurate cell boundary identifications to handle a wide range of morphological complexities. We validated these tools using confocal z-stacks from thick 3-D neural constructs where neuronal somata had varying degrees of neurite arborization and complexity, achieving an accuracy of ≥95%. We demonstrated the robustness of these algorithms in a more complex arena through the automated segmentation of neural cells in ex vivo brain slices. These novel methods surpass previous techniques by improving the robustness and accuracy by: (1) the ability to process neurites and somata, (2) bidirectional segmentation correction, and (3) validation via software-assisted user input. This 3-D image analysis platform provides valuable tools for the unbiased analysis of neural tissue or tissue surrogates within a 3-D context, appropriate for the study of multi-dimensional cell-cell and cell-extracellular matrix interactions. PMID

  11. Segmenting high-frequency intracardiac ultrasound images of myocardium into infarcted, ischemic, and normal regions.

    Science.gov (United States)

    Hao, X; Bruce, C J; Pislaru, C; Greenleaf, J F

    2001-12-01

    Segmenting abnormal from normal myocardium using high-frequency intracardiac echocardiography (ICE) images presents new challenges for image processing. Gray-level intensity and texture features of ICE images of myocardium with the same structural/perfusion properties differ. This significant limitation conflicts with the fundamental assumption on which existing segmentation techniques are based. This paper describes a new seeded region growing method to overcome the limitations of the existing segmentation techniques. Three criteria are used for region growing control: 1) Each pixel is merged into the globally closest region in the multifeature space. 2) "Geographic similarity" is introduced to overcome the problem that myocardial tissue, despite having the same property (i.e., perfusion status), may be segmented into several different regions using existing segmentation methods. 3) "Equal opportunity competence" criterion is employed making results independent of processing order. This novel segmentation method is applied to in vivo intracardiac ultrasound images using pathology as the reference method for the ground truth. The corresponding results demonstrate that this method is reliable and effective.

  12. Compound image segmentation of published biomedical figures.

    Science.gov (United States)

    Li, Pengyuan; Jiang, Xiangying; Kambhamettu, Chandra; Shatkay, Hagit

    2018-04-01

    Images convey essential information in biomedical publications. As such, there is a growing interest within the bio-curation and the bio-databases communities, to store images within publications as evidence for biomedical processes and for experimental results. However, many of the images in biomedical publications are compound images consisting of multiple panels, where each individual panel potentially conveys a different type of information. Segmenting such images into constituent panels is an essential first step toward utilizing images. In this article, we develop a new compound image segmentation system, FigSplit, which is based on Connected Component Analysis. To overcome shortcomings typically manifested by existing methods, we develop a quality assessment step for evaluating and modifying segmentations. Two methods are proposed to re-segment the images if the initial segmentation is inaccurate. Experimental results show the effectiveness of our method compared with other methods. The system is publicly available for use at: https://www.eecis.udel.edu/~compbio/FigSplit. The code is available upon request. shatkay@udel.edu. Supplementary data are available online at Bioinformatics.

  13. Contour tracing for segmentation of mammographic masses

    International Nuclear Information System (INIS)

    Elter, Matthias; Held, Christian; Wittenberg, Thomas

    2010-01-01

    CADx systems have the potential to support radiologists in the difficult task of discriminating benign and malignant mammographic lesions. The segmentation of mammographic masses from the background tissue is an important module of CADx systems designed for the characterization of mass lesions. In this work, a novel approach to this task is presented. The segmentation is performed by automatically tracing the mass' contour in-between manually provided landmark points defined on the mass' margin. The performance of the proposed approach is compared to the performance of implementations of three state-of-the-art approaches based on region growing and dynamic programming. For an unbiased comparison of the different segmentation approaches, optimal parameters are selected for each approach by means of tenfold cross-validation and a genetic algorithm. Furthermore, segmentation performance is evaluated on a dataset of ROI and ground-truth pairs. The proposed method outperforms the three state-of-the-art methods. The benchmark dataset will be made available with publication of this paper and will be the first publicly available benchmark dataset for mass segmentation.

  14. Mycobacterium grossiae sp. nov., a rapidly growing, scotochromogenic species isolated from human clinical respiratory and blood culture specimens.

    Science.gov (United States)

    Paniz-Mondolfi, Alberto Enrique; Greninger, Alexander L; Ladutko, Lynn; Brown-Elliott, Barbara A; Vasireddy, Ravikiran; Jakubiec, Wesley; Vasireddy, Sruthi; Wallace, Richard J; Simmon, Keith E; Dunn, Bruce E; Jackoway, Gary; Vora, Surabhi B; Quinn, Kevin K; Qin, Xuan; Campbell, Sheldon

    2017-11-01

    A previously undescribed, rapidly growing, scotochromogenic species of the genus Mycobacterium (represented by strains PB739 T and GK) was isolated from two clinical sources - the sputum of a 76-year-old patient with severe chronic obstructive pulmonary disease, history of tuberculosis exposure and Mycobacterium avium complex isolated years prior; and the blood of a 15-year-old male with B-cell acute lymphoblastic leukaemia status post bone marrow transplant. The isolates grew as dark orange colonies at 25-37 °C after 5 days, sharing features in common with other closely related species. Analysis of the complete 16S rRNA gene sequence (1492 bp) of strain PB739 T demonstrated that the isolate shared 98.8 % relatedness with Mycobacterium wolinskyi. Partial 429 bp hsp65 and 744 bp rpoB region V sequence analyses revealed that the sequences of the novel isolate shared 94.8 and 92.1 % similarity with those of Mycobacterium neoaurum and Mycobacterium aurum, respectively. Biochemical profiling, antimicrobial susceptibility testing, HPLC/gas-liquid chromatography analyses and multilocus sequence typing support the taxonomic status of these isolates (PB739 T and GK) as representatives of a novel species. Both isolates were susceptible to the Clinical and Laboratory Standards Institute recommended antimicrobials for susceptibility testing of rapidly growing mycobacteria including amikacin, ciprofloxacin, moxifloxacin, doxycycline/minocycline, imipenem, linezolid, clarithromycin and trimethropin/sulfamethoxazole. Both isolates PB739 T and GK showed intermediate susceptibility to cefoxitin. We propose the name Mycobacterium grossiae sp. nov. for this novel species and have deposited the type strain in the DSMZ and CIP culture collections. The type strain is PB739 T (=DSM 104744 T =CIP 111318 T ).

  15. Natural color image segmentation using integrated mechanism

    Institute of Scientific and Technical Information of China (English)

    Jie Xu (徐杰); Pengfei Shi (施鹏飞)

    2003-01-01

    A new method for natural color image segmentation using integrated mechanism is proposed in this paper.Edges are first detected in term of the high phase congruency in the gray-level image. K-mean cluster is used to label long edge lines based on the global color information to estimate roughly the distribution of objects in the image, while short ones are merged based on their positions and local color differences to eliminate the negative affection caused by texture or other trivial features in image. Region growing technique is employed to achieve final segmentation results. The proposed method unifies edges, whole and local color distributions, as well as spatial information to solve the natural image segmentation problem.The feasibility and effectiveness of this method have been demonstrated by various experiments.

  16. A modified Seeded Region Growing algorithm for vessel segmentation in breast MRI images for investigating the nature of potential lesions

    Science.gov (United States)

    Glotsos, D.; Vassiou, K.; Kostopoulos, S.; Lavdas, El; Kalatzis, I.; Asvestas, P.; Arvanitis, D. L.; Fezoulidis, I. V.; Cavouras, D.

    2014-03-01

    The role of Magnetic Resonance Imaging (MRI) as an alternative protocol for screening of breast cancer has been intensively investigated during the past decade. Preliminary research results have indicated that gadolinium-agent administrative MRI scans may reveal the nature of breast lesions by analyzing the contrast-agent's uptake time. In this study, we attempt to deduce the same conclusion, however, from a different perspective by investigating, using image processing, the vascular network of the breast at two different time intervals following the administration of gadolinium. Twenty cases obtained from a 3.0-T MRI system (SIGNA HDx; GE Healthcare) were included in the study. A new modification of the Seeded Region Growing (SRG) algorithm was used to segment vessels from surrounding background. Delineated vessels were investigated by means of their topology, morphology and texture. Results have shown that it is possible to estimate the nature of the lesions with approximately 94.4% accuracy, thus, it may be claimed that the breast vascular network does encodes useful, patterned, information, which can be used for characterizing breast lesions.

  17. Mycobacterium oryzae sp. nov., a scotochromogenic, rapidly growing species is able to infect human macrophage cell line.

    Science.gov (United States)

    Ramaprasad, E V V; Rizvi, A; Banerjee, S; Sasikala, Ch; Ramana, Ch V

    2016-11-01

    Gram-stain-positive, acid-fast-positive, rapidly growing, rod-shaped bacteria (designated as strains JC290T, JC430 and JC431) were isolated from paddy cultivated soils on the Western Ghats of India. Phylogenetic analysis placed the three strains among the rapidly growing mycobacteria, being most closely related to Mycobacterium tokaiense 47503T (98.8 % 16S rRNA gene sequence similarity), Mycobacterium murale MA112/96T (98.8 %) and a few other Mycobacterium species. The level of DNA-DNA reassociation of the three strains with M. tokaiense DSM 44635T was 23.4±4 % (26.1±3 %, reciprocal analysis) and 21.4±2 % (22.1±4 %, reciprocal analysis). The three novel strains shared >99.9 % 16S rRNA gene sequence similarity and DNA-DNA reassociation values >85 %. Furthermore, phylogenetic analysis based on concatenated sequences (3071 bp) of four housekeeping genes (16S rRNA, hsp65, rpoB and sodA) revealed that strain JC290T is clearly distinct from all other Mycobacteriumspecies. The three strains had diphosphatidylglycerol, phosphatidylethanolamine, phosphatidylinositol, phosphatidylinositolmannosides, unidentified phospholipids, unidentified glycolipids and an unidentified lipid as polar lipids. The predominant isoprenoid quinone for all three strains was MK-9(H2). Fatty acids were C17 : 1ω7c, C16 : 0, C18 : 1ω9c, C16 : 1ω7c/C16 : 1ω6c and C19 : 1ω7c/C19 : 1ω6c for all the three strains. On the basis of phenotypic, chemotaxonomic and phylogenetic data, it was concluded that strains JC290T, JC430 and JC431 are members of a novel species within the genus Mycobacterium and for which the name Mycobacterium oryzae sp. nov. is proposed. The type strain is JC290T (=KCTC 39560T=LMG 28809T).

  18. Diversity, Community Composition, and Dynamics of Nonpigmented and Late-Pigmenting Rapidly Growing Mycobacteria in an Urban Tap Water Production and Distribution System

    OpenAIRE

    Dubrou, S.; Konjek, J.; Macheras, E.; Welté, B.; Guidicelli, L.; Chignon, E.; Joyeux, M.; Gaillard, J. L.; Heym, B.; Tully, T.; Sapriel, G.

    2013-01-01

    Nonpigmented and late-pigmenting rapidly growing mycobacteria (RGM) have been reported to commonly colonize water production and distribution systems. However, there is little information about the nature and distribution of RGM species within the different parts of such complex networks or about their clustering into specific RGM species communities. We conducted a large-scale survey between 2007 and 2009 in the Parisian urban tap water production and distribution system. We analyzed 1,418 w...

  19. SU-E-J-252: Reproducibility of Radiogenomic Image Features: Comparison of Two Semi-Automated Segmentation Methods

    Energy Technology Data Exchange (ETDEWEB)

    Lee, M; Woo, B; Kim, J [Seoul National University, Seoul (Korea, Republic of); Jamshidi, N; Kuo, M [UCLA School of Medicine, Los Angeles, CA (United States)

    2015-06-15

    Purpose: Objective and reliable quantification of imaging phenotype is an essential part of radiogenomic studies. We compared the reproducibility of two semi-automatic segmentation methods for quantitative image phenotyping in magnetic resonance imaging (MRI) of glioblastoma multiforme (GBM). Methods: MRI examinations with T1 post-gadolinium and FLAIR sequences of 10 GBM patients were downloaded from the Cancer Image Archive site. Two semi-automatic segmentation tools with different algorithms (deformable model and grow cut method) were used to segment contrast enhancement, necrosis and edema regions by two independent observers. A total of 21 imaging features consisting of area and edge groups were extracted automatically from the segmented tumor. The inter-observer variability and coefficient of variation (COV) were calculated to evaluate the reproducibility. Results: Inter-observer correlations and coefficient of variation of imaging features with the deformable model ranged from 0.953 to 0.999 and 2.1% to 9.2%, respectively, and the grow cut method ranged from 0.799 to 0.976 and 3.5% to 26.6%, respectively. Coefficient of variation for especially important features which were previously reported as predictive of patient survival were: 3.4% with deformable model and 7.4% with grow cut method for the proportion of contrast enhanced tumor region; 5.5% with deformable model and 25.7% with grow cut method for the proportion of necrosis; and 2.1% with deformable model and 4.4% with grow cut method for edge sharpness of tumor on CE-T1W1. Conclusion: Comparison of two semi-automated tumor segmentation techniques shows reliable image feature extraction for radiogenomic analysis of GBM patients with multiparametric Brain MRI.

  20. SU-E-J-252: Reproducibility of Radiogenomic Image Features: Comparison of Two Semi-Automated Segmentation Methods

    International Nuclear Information System (INIS)

    Lee, M; Woo, B; Kim, J; Jamshidi, N; Kuo, M

    2015-01-01

    Purpose: Objective and reliable quantification of imaging phenotype is an essential part of radiogenomic studies. We compared the reproducibility of two semi-automatic segmentation methods for quantitative image phenotyping in magnetic resonance imaging (MRI) of glioblastoma multiforme (GBM). Methods: MRI examinations with T1 post-gadolinium and FLAIR sequences of 10 GBM patients were downloaded from the Cancer Image Archive site. Two semi-automatic segmentation tools with different algorithms (deformable model and grow cut method) were used to segment contrast enhancement, necrosis and edema regions by two independent observers. A total of 21 imaging features consisting of area and edge groups were extracted automatically from the segmented tumor. The inter-observer variability and coefficient of variation (COV) were calculated to evaluate the reproducibility. Results: Inter-observer correlations and coefficient of variation of imaging features with the deformable model ranged from 0.953 to 0.999 and 2.1% to 9.2%, respectively, and the grow cut method ranged from 0.799 to 0.976 and 3.5% to 26.6%, respectively. Coefficient of variation for especially important features which were previously reported as predictive of patient survival were: 3.4% with deformable model and 7.4% with grow cut method for the proportion of contrast enhanced tumor region; 5.5% with deformable model and 25.7% with grow cut method for the proportion of necrosis; and 2.1% with deformable model and 4.4% with grow cut method for edge sharpness of tumor on CE-T1W1. Conclusion: Comparison of two semi-automated tumor segmentation techniques shows reliable image feature extraction for radiogenomic analysis of GBM patients with multiparametric Brain MRI

  1. Coronary arteries segmentation based on the 3D discrete wavelet transform and 3D neutrosophic transform.

    Science.gov (United States)

    Chen, Shuo-Tsung; Wang, Tzung-Dau; Lee, Wen-Jeng; Huang, Tsai-Wei; Hung, Pei-Kai; Wei, Cheng-Yu; Chen, Chung-Ming; Kung, Woon-Man

    2015-01-01

    Most applications in the field of medical image processing require precise estimation. To improve the accuracy of segmentation, this study aimed to propose a novel segmentation method for coronary arteries to allow for the automatic and accurate detection of coronary pathologies. The proposed segmentation method included 2 parts. First, 3D region growing was applied to give the initial segmentation of coronary arteries. Next, the location of vessel information, HHH subband coefficients of the 3D DWT, was detected by the proposed vessel-texture discrimination algorithm. Based on the initial segmentation, 3D DWT integrated with the 3D neutrosophic transformation could accurately detect the coronary arteries. Each subbranch of the segmented coronary arteries was segmented correctly by the proposed method. The obtained results are compared with those ground truth values obtained from the commercial software from GE Healthcare and the level-set method proposed by Yang et al., 2007. Results indicate that the proposed method is better in terms of efficiency analyzed. Based on the initial segmentation of coronary arteries obtained from 3D region growing, one-level 3D DWT and 3D neutrosophic transformation can be applied to detect coronary pathologies accurately.

  2. Lung tumor segmentation in PET images using graph cuts.

    Science.gov (United States)

    Ballangan, Cherry; Wang, Xiuying; Fulham, Michael; Eberl, Stefan; Feng, David Dagan

    2013-03-01

    The aim of segmentation of tumor regions in positron emission tomography (PET) is to provide more accurate measurements of tumor size and extension into adjacent structures, than is possible with visual assessment alone and hence improve patient management decisions. We propose a segmentation energy function for the graph cuts technique to improve lung tumor segmentation with PET. Our segmentation energy is based on an analysis of the tumor voxels in PET images combined with a standardized uptake value (SUV) cost function and a monotonic downhill SUV feature. The monotonic downhill feature avoids segmentation leakage into surrounding tissues with similar or higher PET tracer uptake than the tumor and the SUV cost function improves the boundary definition and also addresses situations where the lung tumor is heterogeneous. We evaluated the method in 42 clinical PET volumes from patients with non-small cell lung cancer (NSCLC). Our method improves segmentation and performs better than region growing approaches, the watershed technique, fuzzy-c-means, region-based active contour and tumor customized downhill. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  3. Active mask segmentation of fluorescence microscope images.

    Science.gov (United States)

    Srinivasa, Gowri; Fickus, Matthew C; Guo, Yusong; Linstedt, Adam D; Kovacević, Jelena

    2009-08-01

    We propose a new active mask algorithm for the segmentation of fluorescence microscope images of punctate patterns. It combines the (a) flexibility offered by active-contour methods, (b) speed offered by multiresolution methods, (c) smoothing offered by multiscale methods, and (d) statistical modeling offered by region-growing methods into a fast and accurate segmentation tool. The framework moves from the idea of the "contour" to that of "inside and outside," or masks, allowing for easy multidimensional segmentation. It adapts to the topology of the image through the use of multiple masks. The algorithm is almost invariant under initialization, allowing for random initialization, and uses a few easily tunable parameters. Experiments show that the active mask algorithm matches the ground truth well and outperforms the algorithm widely used in fluorescence microscopy, seeded watershed, both qualitatively, as well as quantitatively.

  4. A new 2D segmentation method based on dynamic programming applied to computer aided detection in mammography

    International Nuclear Information System (INIS)

    Timp, Sheila; Karssemeijer, Nico

    2004-01-01

    Mass segmentation plays a crucial role in computer-aided diagnosis (CAD) systems for classification of suspicious regions as normal, benign, or malignant. In this article we present a robust and automated segmentation technique--based on dynamic programming--to segment mass lesions from surrounding tissue. In addition, we propose an efficient algorithm to guarantee resulting contours to be closed. The segmentation method based on dynamic programming was quantitatively compared with two other automated segmentation methods (region growing and the discrete contour model) on a dataset of 1210 masses. For each mass an overlap criterion was calculated to determine the similarity with manual segmentation. The mean overlap percentage for dynamic programming was 0.69, for the other two methods 0.60 and 0.59, respectively. The difference in overlap percentage was statistically significant. To study the influence of the segmentation method on the performance of a CAD system two additional experiments were carried out. The first experiment studied the detection performance of the CAD system for the different segmentation methods. Free-response receiver operating characteristics analysis showed that the detection performance was nearly identical for the three segmentation methods. In the second experiment the ability of the classifier to discriminate between malignant and benign lesions was studied. For region based evaluation the area A z under the receiver operating characteristics curve was 0.74 for dynamic programming, 0.72 for the discrete contour model, and 0.67 for region growing. The difference in A z values obtained by the dynamic programming method and region growing was statistically significant. The differences between other methods were not significant

  5. Clinical and taxonomic status of pathogenic nonpigmented or late-pigmenting rapidly growing mycobacteria.

    Science.gov (United States)

    Brown-Elliott, Barbara A; Wallace, Richard J

    2002-10-01

    The history, taxonomy, geographic distribution, clinical disease, and therapy of the pathogenic nonpigmented or late-pigmenting rapidly growing mycobacteria (RGM) are reviewed. Community-acquired disease and health care-associated disease are highlighted for each species. The latter grouping includes health care-associated outbreaks and pseudo-outbreaks as well as sporadic disease cases. Treatment recommendations for each species and type of disease are also described. Special emphasis is on the Mycobacterium fortuitum group, including M. fortuitum, M. peregrinum, and the unnamed third biovariant complex with its recent taxonomic changes and newly recognized species (including M. septicum, M. mageritense, and proposed species M. houstonense and M. bonickei). The clinical and taxonomic status of M. chelonae, M. abscessus, and M. mucogenicum is also detailed, along with that of the closely related new species, M. immunogenum. Additionally, newly recognized species, M. wolinskyi and M. goodii, as well as M. smegmatis sensu stricto, are included in a discussion of the M. smegmatis group. Laboratory diagnosis of RGM using phenotypic methods such as biochemical testing and high-performance liquid chromatography and molecular methods of diagnosis are also discussed. The latter includes PCR-restriction fragment length polymorphism analysis, hybridization, ribotyping, and sequence analysis. Susceptibility testing and antibiotic susceptibility patterns of the RGM are also annotated, along with the current recommendations from the National Committee for Clinical Laboratory Standards (NCCLS) for mycobacterial susceptibility testing.

  6. Rapidly-growing mycobacterial infection: a recognized cause of early-onset prosthetic joint infection.

    Science.gov (United States)

    Jitmuang, Anupop; Yuenyongviwat, Varah; Charoencholvanich, Keerati; Chayakulkeeree, Methee

    2017-12-28

    Prosthetic joint infection (PJI) is a major complication of total hip and total knee arthroplasty (THA, TKA). Although mycobacteria are rarely the causative pathogens, it is important to recognize and treat them differently from non-mycobacterial infections. This study aimed to compare the clinical characteristics, associated factors and long-term outcomes of mycobacterial and non-mycobacterial PJI. We conducted a retrospective case-control study of patients aged ≥18 years who were diagnosed with PJI of the hip or knee at Siriraj Hospital from January 2000 to December 2012. Patient characteristics, clinical data, treatments and outcomes were evaluated. A total of 178 patients were included, among whom 162 had non-mycobacterial PJI and 16 had mycobacterial PJI. Rapidly growing mycobacteria (RGM) (11) and M. tuberculosis (MTB) (5) were the causative pathogens of mycobacterial PJI. PJI duration and time until onset were significantly different between mycobacterial and non-mycobacterial PJI. Infection within 90 days of arthroplasty was significantly associated with RGM infection (OR 21.86; 95% CI 4.25-112.30; p infection. RGM were the major pathogens of early onset PJI after THA and TKA. Both a high clinical index of suspicion and mycobacterial cultures are recommended when medically managing PJI with negative cultures or non-response to antibiotics. Removal of infected implants was associated with favorable outcomes.

  7. Multi-Class Simultaneous Adaptive Segmentation and Quality Control of Point Cloud Data

    Directory of Open Access Journals (Sweden)

    Ayman Habib

    2016-01-01

    Full Text Available 3D modeling of a given site is an important activity for a wide range of applications including urban planning, as-built mapping of industrial sites, heritage documentation, military simulation, and outdoor/indoor analysis of airflow. Point clouds, which could be either derived from passive or active imaging systems, are an important source for 3D modeling. Such point clouds need to undergo a sequence of data processing steps to derive the necessary information for the 3D modeling process. Segmentation is usually the first step in the data processing chain. This paper presents a region-growing multi-class simultaneous segmentation procedure, where planar, pole-like, and rough regions are identified while considering the internal characteristics (i.e., local point density/spacing and noise level of the point cloud in question. The segmentation starts with point cloud organization into a kd-tree data structure and characterization process to estimate the local point density/spacing. Then, proceeding from randomly-distributed seed points, a set of seed regions is derived through distance-based region growing, which is followed by modeling of such seed regions into planar and pole-like features. Starting from optimally-selected seed regions, planar and pole-like features are then segmented. The paper also introduces a list of hypothesized artifacts/problems that might take place during the region-growing process. Finally, a quality control process is devised to detect, quantify, and mitigate instances of partially/fully misclassified planar and pole-like features. Experimental results from airborne and terrestrial laser scanning as well as image-based point clouds are presented to illustrate the performance of the proposed segmentation and quality control framework.

  8. US-Cut: interactive algorithm for rapid detection and segmentation of liver tumors in ultrasound acquisitions

    Science.gov (United States)

    Egger, Jan; Voglreiter, Philip; Dokter, Mark; Hofmann, Michael; Chen, Xiaojun; Zoller, Wolfram G.; Schmalstieg, Dieter; Hann, Alexander

    2016-04-01

    Ultrasound (US) is the most commonly used liver imaging modality worldwide. It plays an important role in follow-up of cancer patients with liver metastases. We present an interactive segmentation approach for liver tumors in US acquisitions. Due to the low image quality and the low contrast between the tumors and the surrounding tissue in US images, the segmentation is very challenging. Thus, the clinical practice still relies on manual measurement and outlining of the tumors in the US images. We target this problem by applying an interactive segmentation algorithm to the US data, allowing the user to get real-time feedback of the segmentation results. The algorithm has been developed and tested hand-in-hand by physicians and computer scientists to make sure a future practical usage in a clinical setting is feasible. To cover typical acquisitions from the clinical routine, the approach has been evaluated with dozens of datasets where the tumors are hyperechoic (brighter), hypoechoic (darker) or isoechoic (similar) in comparison to the surrounding liver tissue. Due to the interactive real-time behavior of the approach, it was possible even in difficult cases to find satisfying segmentations of the tumors within seconds and without parameter settings, and the average tumor deviation was only 1.4mm compared with manual measurements. However, the long term goal is to ease the volumetric acquisition of liver tumors in order to evaluate for treatment response. Additional aim is the registration of intraoperative US images via the interactive segmentations to the patient's pre-interventional CT acquisitions.

  9. E-cigarettes: a rapidly growing Internet phenomenon.

    Science.gov (United States)

    Yamin, Cyrus K; Bitton, Asaf; Bates, David W

    2010-11-02

    Electronic cigarettes (e-cigarettes) aerosolize nicotine and produce a vapor that emulates that of cigarettes but purportedly has fewer traditional toxins than secondhand smoke. Although e-cigarettes are widely sold online and by retailers, new research suggests that they may contain unexpected toxins and may provide unreliable nicotine delivery. Many countries have already banned or strictly regulated e-cigarettes. Currently in the United States, e-cigarettes are exempt from regulation as drug-delivery devices. Meanwhile, the presence of e-cigarettes on the Internet, including in Web searches, virtual user communities, and online stores where people sell e-cigarettes on commission, is increasing rapidly. Physicians should be aware of the popularity, questionable efficacy claims, and safety concerns of e-cigarettes so that they may counsel patients against use and advocate for research to inform an evidence-based regulatory approach.

  10. Image segmentation evaluation for very-large datasets

    Science.gov (United States)

    Reeves, Anthony P.; Liu, Shuang; Xie, Yiting

    2016-03-01

    With the advent of modern machine learning methods and fully automated image analysis there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. Current approaches of visual inspection and manual markings do not scale well to big data. We present a new approach that depends on fully automated algorithm outcomes for segmentation documentation, requires no manual marking, and provides quantitative evaluation for computer algorithms. The documentation of new image segmentations and new algorithm outcomes are achieved by visual inspection. The burden of visual inspection on large datasets is minimized by (a) customized visualizations for rapid review and (b) reducing the number of cases to be reviewed through analysis of quantitative segmentation evaluation. This method has been applied to a dataset of 7,440 whole-lung CT images for 6 different segmentation algorithms designed to fully automatically facilitate the measurement of a number of very important quantitative image biomarkers. The results indicate that we could achieve 93% to 99% successful segmentation for these algorithms on this relatively large image database. The presented evaluation method may be scaled to much larger image databases.

  11. Coronary Arteries Segmentation Based on the 3D Discrete Wavelet Transform and 3D Neutrosophic Transform

    Directory of Open Access Journals (Sweden)

    Shuo-Tsung Chen

    2015-01-01

    Full Text Available Purpose. Most applications in the field of medical image processing require precise estimation. To improve the accuracy of segmentation, this study aimed to propose a novel segmentation method for coronary arteries to allow for the automatic and accurate detection of coronary pathologies. Methods. The proposed segmentation method included 2 parts. First, 3D region growing was applied to give the initial segmentation of coronary arteries. Next, the location of vessel information, HHH subband coefficients of the 3D DWT, was detected by the proposed vessel-texture discrimination algorithm. Based on the initial segmentation, 3D DWT integrated with the 3D neutrosophic transformation could accurately detect the coronary arteries. Results. Each subbranch of the segmented coronary arteries was segmented correctly by the proposed method. The obtained results are compared with those ground truth values obtained from the commercial software from GE Healthcare and the level-set method proposed by Yang et al., 2007. Results indicate that the proposed method is better in terms of efficiency analyzed. Conclusion. Based on the initial segmentation of coronary arteries obtained from 3D region growing, one-level 3D DWT and 3D neutrosophic transformation can be applied to detect coronary pathologies accurately.

  12. Optical Character Recognition Using Active Contour Segmentation

    Directory of Open Access Journals (Sweden)

    Nabeel Oudah

    2018-01-01

    Full Text Available Document analysis of images snapped by camera is a growing challenge. These photos are often poor-quality compound images, composed of various objects and text; this makes automatic analysis complicated. OCR is one of the image processing techniques which is used to perform automatic identification of texts. Existing image processing techniques need to manage many parameters in order to clearly recognize the text in such pictures. Segmentation is regarded one of these essential parameters. This paper discusses the accuracy of segmentation process and its effect over the recognition process. According to the proposed method, the images were firstly filtered using the wiener filter then the active contour algorithm could be applied in the segmentation process. The Tesseract OCR Engine was selected in order to evaluate the performance and identification accuracy of the proposed method. The results showed that a more accurate segmentation process shall lead to a more accurate recognition results. The rate of recognition accuracy was 0.95 for the proposed algorithm compared with 0.85 for the Tesseract OCR Engine.

  13. Automatic lung segmentation in the presence of alveolar collapse

    Directory of Open Access Journals (Sweden)

    Noshadi Areg

    2017-09-01

    Full Text Available Lung ventilation and perfusion analyses using chest imaging methods require a correct segmentation of the lung to offer anatomical landmarks for the physiological data. An automatic segmentation approach simplifies and accelerates the analysis. However, the segmentation of the lungs has shown to be difficult if collapsed areas are present that tend to share similar gray values with surrounding non-pulmonary tissue. Our goal was to develop an automatic segmentation algorithm that is able to approximate dorsal lung boundaries even if alveolar collapse is present in the dependent lung areas adjacent to the pleura. Computed tomography data acquired in five supine pigs with injured lungs were used for this purpose. First, healthy lung tissue was segmented using a standard 3D region growing algorithm. Further, the bones in the chest wall surrounding the lungs were segmented to find the contact points of ribs and pleura. Artificial boundaries of the dorsal lung were set by spline interpolation through these contact points. Segmentation masks of the entire lung including the collapsed regions were created by combining the splines with the segmentation masks of the healthy lung tissue through multiple morphological operations. The automatically segmented images were then evaluated by comparing them to manual segmentations and determining the Dice similarity coefficients (DSC as a similarity measure. The developed method was able to accurately segment the lungs including the collapsed regions (DSCs over 0.96.

  14. Coronary Arteries Segmentation Based on the 3D Discrete Wavelet Transform and 3D Neutrosophic Transform

    OpenAIRE

    Shuo-Tsung Chen; Tzung-Dau Wang; Wen-Jeng Lee; Tsai-Wei Huang; Pei-Kai Hung; Cheng-Yu Wei; Chung-Ming Chen; Woon-Man Kung

    2015-01-01

    Purpose. Most applications in the field of medical image processing require precise estimation. To improve the accuracy of segmentation, this study aimed to propose a novel segmentation method for coronary arteries to allow for the automatic and accurate detection of coronary pathologies. Methods. The proposed segmentation method included 2 parts. First, 3D region growing was applied to give the initial segmentation of coronary arteries. Next, the location of vessel information, HHH subband c...

  15. Tetracycline resistance and presence of tetracycline resistance determinants .i.tet./i.(V) and .i.tap./i. in rapidly growing mycobacteria from agricultural soils and clinical isolates

    Czech Academy of Sciences Publication Activity Database

    Kyselková, Martina; Chroňáková, Alica; Volná, Lucie; Němec, Jan; Ulmann, V.; Scharfen, J.; Elhottová, Dana

    2012-01-01

    Roč. 27, č. 4 (2012), s. 413-422 ISSN 1342-6311 R&D Projects: GA ČR GAP504/10/2077; GA MŠk LC06066 Institutional support: RVO:60077344 Keywords : efflux pump * rapidly growing Mycobacterium * tetracycline resistance * tap * tet (V) Subject RIV: EH - Ecology, Behaviour Impact factor: 2.444, year: 2012

  16. Drug Susceptibility Testing of 31 Antimicrobial Agents on Rapidly Growing Mycobacteria Isolates from China.

    Science.gov (United States)

    Pang, Hui; Li, Guilian; Zhao, Xiuqin; Liu, Haican; Wan, Kanglin; Yu, Ping

    2015-01-01

    Several species of rapidly growing mycobacteria (RGM) are now recognized as human pathogens. However, limited data on effective drug treatments against these organisms exists. Here, we describe the species distribution and drug susceptibility profiles of RGM clinical isolates collected from four southern Chinese provinces from January 2005 to December 2012. Clinical isolates (73) were subjected to in vitro testing with 31 antimicrobial agents using the cation-adjusted Mueller-Hinton broth microdilution method. The isolates included 55 M. abscessus, 11 M. fortuitum, 3 M. chelonae, 2 M. neoaurum, and 2 M. septicum isolates. M. abscessus (75.34%) and M. fortuitum (15.07%), the most common species, exhibited greater antibiotic resistance than the other three species. The isolates had low resistance to amikacin, linezolid, and tigecycline, and high resistance to first-line antituberculous agents, amoxicillin-clavulanic acid, rifapentine, dapsone, thioacetazone, and pasiniazid. M. abscessus and M. fortuitum were highly resistant to ofloxacin and rifabutin, respectively. The isolates showed moderate resistance to the other antimicrobial agents. Our results suggest that tigecycline, linezolid, clofazimine, and cefmetazole are appropriate choices for M. abscessus infections. Capreomycin, sulfamethoxazole, tigecycline, clofazimine, and cefmetazole are potentially good choices for M. fortuitum infections. Our drug susceptibility data should be useful to clinicians.

  17. Drug Susceptibility Testing of 31 Antimicrobial Agents on Rapidly Growing Mycobacteria Isolates from China

    Directory of Open Access Journals (Sweden)

    Hui Pang

    2015-01-01

    Full Text Available Objectives. Several species of rapidly growing mycobacteria (RGM are now recognized as human pathogens. However, limited data on effective drug treatments against these organisms exists. Here, we describe the species distribution and drug susceptibility profiles of RGM clinical isolates collected from four southern Chinese provinces from January 2005 to December 2012. Methods. Clinical isolates (73 were subjected to in vitro testing with 31 antimicrobial agents using the cation-adjusted Mueller-Hinton broth microdilution method. The isolates included 55 M. abscessus, 11 M. fortuitum, 3 M. chelonae, 2 M. neoaurum, and 2 M. septicum isolates. Results. M. abscessus (75.34% and M. fortuitum (15.07%, the most common species, exhibited greater antibiotic resistance than the other three species. The isolates had low resistance to amikacin, linezolid, and tigecycline, and high resistance to first-line antituberculous agents, amoxicillin-clavulanic acid, rifapentine, dapsone, thioacetazone, and pasiniazid. M. abscessus and M. fortuitum were highly resistant to ofloxacin and rifabutin, respectively. The isolates showed moderate resistance to the other antimicrobial agents. Conclusions. Our results suggest that tigecycline, linezolid, clofazimine, and cefmetazole are appropriate choices for M. abscessus infections. Capreomycin, sulfamethoxazole, tigecycline, clofazimine, and cefmetazole are potentially good choices for M. fortuitum infections. Our drug susceptibility data should be useful to clinicians.

  18. A segmentation algorithm based on image projection for complex text layout

    Science.gov (United States)

    Zhu, Wangsheng; Chen, Qin; Wei, Chuanyi; Li, Ziyang

    2017-10-01

    Segmentation algorithm is an important part of layout analysis, considering the efficiency advantage of the top-down approach and the particularity of the object, a breakdown of projection layout segmentation algorithm. Firstly, the algorithm will algorithm first partitions the text image, and divided into several columns, then for each column scanning projection, the text image is divided into several sub regions through multiple projection. The experimental results show that, this method inherits the projection itself and rapid calculation speed, but also can avoid the effect of arc image information page segmentation, and also can accurate segmentation of the text image layout is complex.

  19. A NDVI assisted remote sensing image adaptive scale segmentation method

    Science.gov (United States)

    Zhang, Hong; Shen, Jinxiang; Ma, Yanmei

    2018-03-01

    Multiscale segmentation of images can effectively form boundaries of different objects with different scales. However, for the remote sensing image which widely coverage with complicated ground objects, the number of suitable segmentation scales, and each of the scale size is still difficult to be accurately determined, which severely restricts the rapid information extraction of the remote sensing image. A great deal of experiments showed that the normalized difference vegetation index (NDVI) can effectively express the spectral characteristics of a variety of ground objects in remote sensing images. This paper presents a method using NDVI assisted adaptive segmentation of remote sensing images, which segment the local area by using NDVI similarity threshold to iteratively select segmentation scales. According to the different regions which consist of different targets, different segmentation scale boundaries could be created. The experimental results showed that the adaptive segmentation method based on NDVI can effectively create the objects boundaries for different ground objects of remote sensing images.

  20. Epidermal segmentation in high-definition optical coherence tomography.

    Science.gov (United States)

    Li, Annan; Cheng, Jun; Yow, Ai Ping; Wall, Carolin; Wong, Damon Wing Kee; Tey, Hong Liang; Liu, Jiang

    2015-01-01

    Epidermis segmentation is a crucial step in many dermatological applications. Recently, high-definition optical coherence tomography (HD-OCT) has been developed and applied to imaging subsurface skin tissues. In this paper, a novel epidermis segmentation method using HD-OCT is proposed in which the epidermis is segmented by 3 steps: the weighted least square-based pre-processing, the graph-based skin surface detection and the local integral projection-based dermal-epidermal junction detection respectively. Using a dataset of five 3D volumes, we found that this method correlates well with the conventional method of manually marking out the epidermis. This method can therefore serve to effectively and rapidly delineate the epidermis for study and clinical management of skin diseases.

  1. An automated, high-throughput plant phenotyping system using machine learning-based plant segmentation and image analysis.

    Science.gov (United States)

    Lee, Unseok; Chang, Sungyul; Putra, Gian Anantrio; Kim, Hyoungseok; Kim, Dong Hwan

    2018-01-01

    A high-throughput plant phenotyping system automatically observes and grows many plant samples. Many plant sample images are acquired by the system to determine the characteristics of the plants (populations). Stable image acquisition and processing is very important to accurately determine the characteristics. However, hardware for acquiring plant images rapidly and stably, while minimizing plant stress, is lacking. Moreover, most software cannot adequately handle large-scale plant imaging. To address these problems, we developed a new, automated, high-throughput plant phenotyping system using simple and robust hardware, and an automated plant-imaging-analysis pipeline consisting of machine-learning-based plant segmentation. Our hardware acquires images reliably and quickly and minimizes plant stress. Furthermore, the images are processed automatically. In particular, large-scale plant-image datasets can be segmented precisely using a classifier developed using a superpixel-based machine-learning algorithm (Random Forest), and variations in plant parameters (such as area) over time can be assessed using the segmented images. We performed comparative evaluations to identify an appropriate learning algorithm for our proposed system, and tested three robust learning algorithms. We developed not only an automatic analysis pipeline but also a convenient means of plant-growth analysis that provides a learning data interface and visualization of plant growth trends. Thus, our system allows end-users such as plant biologists to analyze plant growth via large-scale plant image data easily.

  2. Rapid-Growing Mycobacteria Infections in Medical Tourists: Our Experience and Literature Review.

    Science.gov (United States)

    Singh, Mansher; Dugdale, Caitlin M; Solomon, Isaac H; Huang, Anne; Montgomery, Mary W; Pomahac, Bohdan; Yawetz, Sigal; Maguire, James H; Talbot, Simon G

    2016-09-01

    "Medical tourism" has gained popularity over the past few decades. This is particularly common with patients seeking elective cosmetic surgery in the developing world. However, the risk of severe and unusual infectious complications appears to be higher than for patients undergoing similar procedures in the United States. The authors describe their experience with atypical mycobacterial infections in cosmetic surgical patients returning to the United States postoperatively. A review of patient medical records presenting with infectious complications after cosmetic surgery between January 2010 and July 2015 was performed. Patients presenting with mycobacterial infections following cosmetic surgery were reviewed in detail. An extensive literature review was performed for rapid-growing mycobacteria (RGM) related to cosmetic procedures. Between January 2010 and July 2015, three patients presented to our institution with culture-proven Mycobacterium abscessus at the sites of recent cosmetic surgery. All had surgery performed in the developing world. The mean age of these patients was 36 years (range, 29-44 years). There was a delay of up to 16 weeks between the initial presentation and correct diagnosis. All patients were treated with surgical drainage and combination antibiotics with complete resolution. We present series of patients with mycobacterial infections after cosmetic surgery in the developing world. This may be related to the endemic nature of these bacteria and/or inadequate sterilization or sterile technique. Due to low domestic incidence of these infections, diagnosis may be difficult and/or delayed. Consulting physicians should have a low threshold to consider atypical etiologies in such scenarios. 5 Therapeutic. © 2016 The American Society for Aesthetic Plastic Surgery, Inc. Reprints and permission: journals.permissions@oup.com.

  3. Urban cyclist exposure to fine particle pollution in a rapidly growing city

    Science.gov (United States)

    Luce, B. W.; Barrett, T. E.; Ponette-González, A.

    2017-12-01

    Urban cyclists are exposed to elevated atmospheric concentrations of fine particulate matter (particles vehicle exhaust, which is emitted directly into cyclists' "breathing zone." In cities, human exposure to PM2.5 is a concern because its small size allows it to be inhaled deeper into the lungs than most particles. The aim of this research is to determine "hotspots" (locations with high PM2.5 concentrations) within the Dallas-Fort Worth Metroplex, Texas, where urban cyclists are most exposed to fine particle pollution. Recent research indicates that common exposure hotspots include traffic signals, junctions, bus stations, parking lots, and inclined streets. To identify these and other hotspots, a bicycle equipped with a low-cost, portable, battery-powered particle counter (Dylos 1700) coupled with a Trimble Geo 5T handheld Global Positioning System (GPS; ≤1 m ± resolution) will be used to map and measure particle mass concentrations along predetermined routes. Measurements will be conducted during a consecutive four-month period (Sep-Dec) during morning and evening rush hours when PM2.5 levels are generally highest, as well as during non-rush hour times to determine background concentrations. PM2.5 concentrations will be calculated from particle counts using an equation developed by Steinle et al. (2015). In addition, traffic counts will be conducted along the routes coinciding with the mobile monitoring times. We will present results on identified "hotspots" of high fine particle concentrations and PM2.5 exposure in the City of Denton, where particle pollution puts urban commuters most at risk, as well as average traffic counts from monitoring times. These data can be used to determine pollution mitigation strategies in rapidly growing urban areas.

  4. Rapidly growing non-tuberculous mycobacteria infection of prosthetic knee joints: A report of two cases.

    Science.gov (United States)

    Kim, Manyoung; Ha, Chul-Won; Jang, Jae Won; Park, Yong-Beom

    2017-08-01

    Non-tuberculous mycobacteria (NTM) cause prosthetic knee joint infections in rare cases. Infections with rapidly growing non-tuberculous mycobacteria (RGNTM) are difficult to treat due to their aggressive clinical behavior and resistance to antibiotics. Infections of a prosthetic knee joint by RGNTM have rarely been reported. A standard of treatment has not yet been established because of the rarity of the condition. In previous reports, diagnoses of RGNTM infections in prosthetic knee joints took a long time to reach because the condition was not suspected, due to its rarity. In addition, it is difficult to identify RGNTM in the lab because special identification tests are needed. In previous reports, after treatment for RGNTM prosthetic infections, knee prostheses could not be re-implanted in all cases but one, resulting in arthrodesis or resection arthroplasty; this was most likely due to the aggressiveness of these organisms. In the present report, two cases of prosthetic knee joint infection caused by RGNTM (Mycobacterium abscessus) are described that were successfully treated, and in which prosthetic joints were finally reimplanted in two-stage revision surgery. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. Appearance Constrained Semi-Automatic Segmentation from DCE-MRI is Reproducible and Feasible for Breast Cancer Radiomics: A Feasibility Study.

    Science.gov (United States)

    Veeraraghavan, Harini; Dashevsky, Brittany Z; Onishi, Natsuko; Sadinski, Meredith; Morris, Elizabeth; Deasy, Joseph O; Sutton, Elizabeth J

    2018-03-19

    We present a segmentation approach that combines GrowCut (GC) with cancer-specific multi-parametric Gaussian Mixture Model (GCGMM) to produce accurate and reproducible segmentations. We evaluated GCGMM using a retrospectively collected 75 invasive ductal carcinoma with ERPR+ HER2- (n = 15), triple negative (TN) (n = 9), and ER-HER2+ (n = 57) cancers with variable presentation (mass and non-mass enhancement) and background parenchymal enhancement (mild and marked). Expert delineated manual contours were used to assess the segmentation performance using Dice coefficient (DSC), mean surface distance (mSD), Hausdorff distance, and volume ratio (VR). GCGMM segmentations were significantly more accurate than GrowCut (GC) and fuzzy c-means clustering (FCM). GCGMM's segmentations and the texture features computed from those segmentations were the most reproducible compared with manual delineations and other analyzed segmentation methods. Finally, random forest (RF) classifier trained with leave-one-out cross-validation using features extracted from GCGMM segmentation resulted in the best accuracy for ER-HER2+ vs. ERPR+/TN (GCGMM 0.95, expert 0.95, GC 0.90, FCM 0.92) and for ERPR + HER2- vs. TN (GCGMM 0.92, expert 0.91, GC 0.77, FCM 0.83).

  6. A Hybrid 3D Colon Segmentation Method Using Modified Geometric Deformable Models

    Directory of Open Access Journals (Sweden)

    S. Falahieh Hamidpour

    2007-06-01

    Full Text Available Introduction: Nowadays virtual colonoscopy has become a reliable and efficient method of detecting primary stages of colon cancer such as polyp detection. One of the most important and crucial stages of virtual colonoscopy is colon segmentation because an incorrect segmentation may lead to a misdiagnosis.  Materials and Methods: In this work, a hybrid method based on Geometric Deformable Models (GDM in combination with an advanced region growing and thresholding methods is proposed. GDM are found to be an attractive tool for structural based image segmentation particularly for extracting the objects with complicated topology. There are two main parameters influencing the overall performance of GDM algorithm; the distance between the initial contour and the actual object’s contours and secondly the stopping term which controls the deformation. To overcome these limitations, a two stage hybrid based segmentation method is suggested to extract the rough but precise initial contours at the first stage of the segmentation. The extracted boundaries are smoothed and improved using a modified GDM algorithm by improving the stopping terms of the algorithm based on the gradient value of image voxels. Results: The proposed algorithm was implemented on forty data sets each containing 400-480 slices. The results show an improvement in the accuracy and smoothness of the extracted boundaries. The improvement obtained for the accuracy of segmentation is about 6% in comparison to the one achieved by the methods based on thresholding and region growing only. Discussion and Conclusion: The extracted contours using modified GDM are smoother and finer. The improvement achieved in this work on the performance of stopping function of GDM model together with applying two stage segmentation of boundaries have resulted in a great improvement on the computational efficiency of GDM algorithm while making smoother and finer colon borders.

  7. SUPERVISED AUTOMATIC HISTOGRAM CLUSTERING AND WATERSHED SEGMENTATION. APPLICATION TO MICROSCOPIC MEDICAL COLOR IMAGES

    Directory of Open Access Journals (Sweden)

    Olivier Lezoray

    2011-05-01

    Full Text Available In this paper, an approach to the segmentation of microscopic color images is addressed, and applied to medical images. The approach combines a clustering method and a region growing method. Each color plane is segmented independently relying on a watershed based clustering of the plane histogram. The marginal segmentation maps intersect in a label concordance map. The latter map is simplified based on the assumption that the color planes are correlated. This produces a simplified label concordance map containing labeled and unlabeled pixels. The formers are used as an image of seeds for a color watershed. This fast and robust segmentation scheme is applied to several types of medical images.

  8. Segmentation of the tissues from MR images using basic anatomical information

    International Nuclear Information System (INIS)

    Yamazaki, Nobutoshi; Notoya, Yoshiaki; Nakamura, Toshiyasu; Mochimaru, Masaaki.

    1994-01-01

    Automatic segmentation methods of MR images have been developed for the cardiac surgery and the brain surgery. In these fields, Region Growing method has been used mainly. In this method, the core was inserted manually, and the pixel adjoining the core was judged whether it was homogeneous or not from its features based on image information. The core grew adding the homogeneous pixels, and the region of interest was obtained as the grown core. It is available for orthopedic surgery and biomechanics to obtain the location and the orientation of bones and soft tissues in vivo. However, MR images including them could not be segmented by the former region growing method based on only image information. This is because those tissues had fuzzy boundaries on the image. Thus, we used not only intensity and spatial gradient as image information but also location, size and complexity of the tissue to segment the MR images. The pixel adjoining the core was judged from three local features of the pixel ; its intensity, gradient and location, and two global features of the core region ; its size and complexity. Judgment was performed by Fuzzy Reasoning to allow their fuzzy boundaries. The homogeneous pixel was added into the core region. It grew into normal size and smooth shape under constraint of global anatomical features. Using the present method, as an example, radius, ulna and interosseous membrane were segmented from the multi-sliced MR images of forearm. Segmented tissues agreed with the shape inserted manually by a medical doctor. As s result, three tissues containing different features on the MR image could be segmented by a single algorithm. It takes about 10 sec per slice by using an engineering workstation. (author)

  9. Segmentation of the tissues from MR images using basic anatomical information

    Energy Technology Data Exchange (ETDEWEB)

    Yamazaki, Nobutoshi; Notoya, Yoshiaki [Keio Univ., Yokohama (Japan). Faculty of Science and Technology; Nakamura, Toshiyasu; Mochimaru, Masaaki

    1994-11-01

    Automatic segmentation methods of MR images have been developed for the cardiac surgery and the brain surgery. In these fields, Region Growing method has been used mainly. In this method, the core was inserted manually, and the pixel adjoining the core was judged whether it was homogeneous or not from its features based on image information. The core grew adding the homogeneous pixels, and the region of interest was obtained as the grown core. It is available for orthopedic surgery and biomechanics to obtain the location and the orientation of bones and soft tissues in vivo. However, MR images including them could not be segmented by the former region growing method based on only image information. This is because those tissues had fuzzy boundaries on the image. Thus, we used not only intensity and spatial gradient as image information but also location, size and complexity of the tissue to segment the MR images. The pixel adjoining the core was judged from three local features of the pixel ; its intensity, gradient and location, and two global features of the core region ; its size and complexity. Judgment was performed by Fuzzy Reasoning to allow their fuzzy boundaries. The homogeneous pixel was added into the core region. It grew into normal size and smooth shape under constraint of global anatomical features. Using the present method, as an example, radius, ulna and interosseous membrane were segmented from the multi-sliced MR images of forearm. Segmented tissues agreed with the shape inserted manually by a medical doctor. As s result, three tissues containing different features on the MR image could be segmented by a single algorithm. It takes about 10 sec per slice by using an engineering workstation. (author).

  10. Segmentation of Residential Gas Consumers Using Clustering Analysis

    Directory of Open Access Journals (Sweden)

    Marta P. Fernandes

    2017-12-01

    Full Text Available The growing environmental concerns and liberalization of energy markets have resulted in an increased competition between utilities and a strong focus on efficiency. To develop new energy efficiency measures and optimize operations, utilities seek new market-related insights and customer engagement strategies. This paper proposes a clustering-based methodology to define the segmentation of residential gas consumers. The segments of gas consumers are obtained through a detailed clustering analysis using smart metering data. Insights are derived from the segmentation, where the segments result from the clustering process and are characterized based on the consumption profiles, as well as according to information regarding consumers’ socio-economic and household key features. The study is based on a sample of approximately one thousand households over one year. The representative load profiles of consumers are essentially characterized by two evident consumption peaks, one in the morning and the other in the evening, and an off-peak consumption. Significant insights can be derived from this methodology regarding typical consumption curves of the different segments of consumers in the population. This knowledge can assist energy utilities and policy makers in the development of consumer engagement strategies, demand forecasting tools and in the design of more sophisticated tariff systems.

  11. Fostering and sustaining innovation in a Fast Growing Agile Company

    OpenAIRE

    Moe, NilsBrede; Barney, Sebastian; Aurum, Aybüe; Khurum, Mahvish; Wohlin, Claes; Barney, Hamish; Gorschek, Tony; Winata, Martha

    2012-01-01

    Sustaining innovation in a fast growing software development company is difficult. As organisations grow, peoples' focus often changes from the big picture of the product being developed to the specific role they fill. This paper presents two complementary approaches that were successfully used to support continued developer-driven innovation in a rapidly growing Australian agile software development company. The method "FedEx TM Day" gives developers one day to showcase a proof of concept th...

  12. Automatic 2D segmentation of airways in thorax computed tomography images

    International Nuclear Information System (INIS)

    Cavalcante, Tarique da Silveira; Cortez, Paulo Cesar; Almeida, Thomaz Maia de; Felix, John Hebert da Silva; Holanda, Marcelo Alcantara

    2013-01-01

    Introduction: much of the world population is affected by pulmonary diseases, such as the bronchial asthma, bronchitis and bronchiectasis. The bronchial diagnosis is based on the airways state. In this sense, the automatic segmentation of the airways in Computed Tomography (CT) scans is a critical step in the aid to diagnosis of these diseases. Methods: this paper evaluates algorithms for airway automatic segmentation, using Neural Network Multilayer Perceptron (MLP) and Lung Densities Analysis (LDA) for detecting airways, along with Region Growing (RG), Active Contour Method (ACM) Balloon and Topology Adaptive to segment them. Results: we obtained results in three stages: comparative analysis of the detection algorithms MLP and LDA, with a gold standard acquired by three physicians with expertise in CT imaging of the chest; comparative analysis of segmentation algorithms ACM Balloon, ACM Topology Adaptive, MLP and RG; and evaluation of possible combinations between segmentation and detection algorithms, resulting in the complete method for automatic segmentation of the airways in 2D. Conclusion: the low incidence of false negative and the significant reduction of false positive, results in similarity coefficient and sensitivity exceeding 91% and 87% respectively, for a combination of algorithms with satisfactory segmentation quality. (author)

  13. Safety dose of three commercially used growth promoters: nuricell- aqua, hepaprotect-aqua and rapid-grow on growth and survival of Thai pangas (Pangasianodon hypophthalmus

    Directory of Open Access Journals (Sweden)

    Md. Ariful Islam

    2014-02-01

    Full Text Available Objective: To optimize the dose of 3 commonly used growth promoters, viz., Nuricell-Aqua (composition: glucomannan complex and mannose polymer, Hepaprotect-Aqua (composition: β-glucan, mannose polymer and essential oil and Rapid-Grow (composition: organic acid and their salt, β-glucan, mannose oligosaccharide and essential oil, using Thai pangas (Pangasiandon hypophthalmus as cultured species. Methods: Thai pangas fingerlings with an average length and weight of 11 cm and 10 g were reared under laboratory condition and growth promoters were fed after incorporating them with a test diet at a ratio of 10% of their body weight for a period of 28 d. Estimation of data on growth such as weight gain (g, specific growth rate, survivability (% test in each aquarium were conducted and data were analyzed using statistical software. Results: After 28 d of feeding with Nutricell-Aqua, 10 mg/(20 g feed·day, which was the dose recommended by the manufacturer, was found better. When Hepaprotect-Aqua and Rapid-Grow were employed, performance was found to be better with the dose of 60 mg/(20 g feed·day which was 1.5 times higher than the dose recommended by the corresponding manufacturer. Conclusions: These results suggest that chemicals and feed additives marketed in Bangladesh Fish Feed Market need further testing under Bangladesh climatic condition before being marketed.

  14. Addressing the path-length-dependency confound in white matter tract segmentation

    DEFF Research Database (Denmark)

    Liptrot, Matthew George; Sidaros, Karam; Dyrby, Tim B.

    2014-01-01

    of streamlines emitted per voxel, and a threshold applied at each iteration. As few as 20 streamlines per seed-voxel, and a robust range of ICE-T thresholds, were shown to sufficiently segment the desired tract network. Outside this range, the tract network either approximated the complete white-matter...... complexity, and therefore cannot be handled using linear correction methods. ICE-T is an easy-to-implement framework that acts as a wrapper around most probabilistic streamline tractography methods, iteratively growing the tractography seed regions. Tract networks segmented with ICE-T can subsequently...... consider this or a similar approach when using tractography to provide tract segmentations for tract based analysis, or for brain network analysis....

  15. Watch it! The Influence of Forced Pre-roll Video Ads on Consumer Perceptions

    NARCIS (Netherlands)

    Hegner, Sabrina; Hegner, Sabrina M.; Kusse, Daniel C.; Pruyn, Adriaan T.H.; Verlegh, Peeter; Voorveld, Hilde; Eisend, Martin

    2016-01-01

    The internet is the fastest growing advertising segment in the world (Gambaro and Puglisi, 2012). One specific online advertising format that is growing very rapidly is online video advertising. This advertising format owes its explosive growth to the rapid acceleration of online video viewing and

  16. Rare Rapidly Growing Thumb Lesion in a 12-Year-Old Male

    Directory of Open Access Journals (Sweden)

    Alana J Arnold, MD, MBA

    2018-04-01

    t amenable to surgery.4 Surgery is the mainstay of care. The first medical treatment, denosumab, was approved by the FDA for use in adults and skeletally mature adolescents with surgically unresectable lesions.5 It is critical to obtain definitive imaging and biopsy of any rapidly growing lesions in patients presenting with masses and no history of trauma or constitutional symptoms. The best imaging study is MRI, to assess for bony and tissue involvement and surgical approach. Computed tomography may be used; however, it doesn’t delineate the soft tissue and bony connections as well. Standard oncology labs should be drawn as well, including: CBC with differential, LDH, uric acid, CMP, ESR. The growth of the tumor is insidious and therefore imaging should be done based on clinical concern. In the ED setting, if close follow up can be ensured, imaging can be done as an out-patient. Annual surveillance is recommended for at least 5 years in most patients, even after total resection, according to some studies.3 Our patient underwent GCTB resection with plastics surgery of the distal phalanx of thumb. He was seen in follow-up in the oncology clinic. Pathology of the tumor had negative margins, and he was told to follow-up in six months with plastics. Per hematology, no further follow-up was needed. Topics: Pediatrics, giant cell tumor, thumb lesion

  17. Segmentation: Identification of consumer segments

    DEFF Research Database (Denmark)

    Høg, Esben

    2005-01-01

    It is very common to categorise people, especially in the advertising business. Also traditional marketing theory has taken in consumer segments as a favorite topic. Segmentation is closely related to the broader concept of classification. From a historical point of view, classification has its...... origin in other sciences as for example biology, anthropology etc. From an economic point of view, it is called segmentation when specific scientific techniques are used to classify consumers to different characteristic groupings. What is the purpose of segmentation? For example, to be able to obtain...... a basic understanding of grouping people. Advertising agencies may use segmentation totarget advertisements, while food companies may usesegmentation to develop products to various groups of consumers. MAPP has for example investigated the positioning of fish in relation to other food products...

  18. Determination of the impact of RGB points cloud attribute quality on color-based segmentation process

    Directory of Open Access Journals (Sweden)

    Bartłomiej Kraszewski

    2015-06-01

    Full Text Available The article presents the results of research on the effect that radiometric quality of point cloud RGB attributes have on color-based segmentation. In the research, a point cloud with a resolution of 5 mm, received from FAROARO Photon 120 scanner, described the fragment of an office’s room and color images were taken by various digital cameras. The images were acquired by SLR Nikon D3X, and SLR Canon D200 integrated with the laser scanner, compact camera Panasonic TZ-30 and a mobile phone digital camera. Color information from images was spatially related to point cloud in FAROARO Scene software. The color-based segmentation of testing data was performed with the use of a developed application named “RGB Segmentation”. The application was based on public Point Cloud Libraries (PCL and allowed to extract subsets of points fulfilling the criteria of segmentation from the source point cloud using region growing method.Using the developed application, the segmentation of four tested point clouds containing different RGB attributes from various images was performed. Evaluation of segmentation process was performed based on comparison of segments acquired using the developed application and extracted manually by an operator. The following items were compared: the number of obtained segments, the number of correctly identified objects and the correctness of segmentation process. The best correctness of segmentation and most identified objects were obtained using the data with RGB attribute from Nikon D3X images. Based on the results it was found that quality of RGB attributes of point cloud had impact only on the number of identified objects. In case of correctness of the segmentation, as well as its error no apparent relationship between the quality of color information and the result of the process was found.[b]Keywords[/b]: terrestrial laser scanning, color-based segmentation, RGB attribute, region growing method, digital images, points cloud

  19. Host-Specific and Segment-Specific Evolutionary Dynamics of Avian and Human Influenza A Viruses: A Systematic Review

    KAUST Repository

    Kim, Kiyeon

    2016-01-13

    Understanding the evolutionary dynamics of influenza viruses is essential to control both avian and human influenza. Here, we analyze host-specific and segment-specific Tajima’s D trends of influenza A virus through a systematic review using viral sequences registered in the National Center for Biotechnology Information. To avoid bias from viral population subdivision, viral sequences were stratified according to their sampling locations and sampling years. As a result, we obtained a total of 580 datasets each of which consists of nucleotide sequences of influenza A viruses isolated from a single population of hosts at a single sampling site within a single year. By analyzing nucleotide sequences in the datasets, we found that Tajima’s D values of viral sequences were different depending on hosts and gene segments. Tajima’s D values of viruses isolated from chicken and human samples showed negative, suggesting purifying selection or a rapid population growth of the viruses. The negative Tajima’s D values in rapidly growing viral population were also observed in computer simulations. Tajima’s D values of PB2, PB1, PA, NP, and M genes of the viruses circulating in wild mallards were close to zero, suggesting that these genes have undergone neutral selection in constant-sized population. On the other hand, Tajima’s D values of HA and NA genes of these viruses were positive, indicating HA and NA have undergone balancing selection in wild mallards. Taken together, these results indicated the existence of unknown factors that maintain viral subtypes in wild mallards.

  20. Host-Specific and Segment-Specific Evolutionary Dynamics of Avian and Human Influenza A Viruses: A Systematic Review

    KAUST Repository

    Kim, Kiyeon; Omori, Ryosuke; Ueno, Keisuke; Iida, Sayaka; Ito, Kimihito

    2016-01-01

    Understanding the evolutionary dynamics of influenza viruses is essential to control both avian and human influenza. Here, we analyze host-specific and segment-specific Tajima’s D trends of influenza A virus through a systematic review using viral sequences registered in the National Center for Biotechnology Information. To avoid bias from viral population subdivision, viral sequences were stratified according to their sampling locations and sampling years. As a result, we obtained a total of 580 datasets each of which consists of nucleotide sequences of influenza A viruses isolated from a single population of hosts at a single sampling site within a single year. By analyzing nucleotide sequences in the datasets, we found that Tajima’s D values of viral sequences were different depending on hosts and gene segments. Tajima’s D values of viruses isolated from chicken and human samples showed negative, suggesting purifying selection or a rapid population growth of the viruses. The negative Tajima’s D values in rapidly growing viral population were also observed in computer simulations. Tajima’s D values of PB2, PB1, PA, NP, and M genes of the viruses circulating in wild mallards were close to zero, suggesting that these genes have undergone neutral selection in constant-sized population. On the other hand, Tajima’s D values of HA and NA genes of these viruses were positive, indicating HA and NA have undergone balancing selection in wild mallards. Taken together, these results indicated the existence of unknown factors that maintain viral subtypes in wild mallards.

  1. Pnrc2 regulates 3'UTR-mediated decay of segmentation clock-associated transcripts during zebrafish segmentation.

    Science.gov (United States)

    Gallagher, Thomas L; Tietz, Kiel T; Morrow, Zachary T; McCammon, Jasmine M; Goldrich, Michael L; Derr, Nicolas L; Amacher, Sharon L

    2017-09-01

    Vertebrate segmentation is controlled by the segmentation clock, a molecular oscillator that regulates gene expression and cycles rapidly. The expression of many genes oscillates during segmentation, including hairy/Enhancer of split-related (her or Hes) genes, which encode transcriptional repressors that auto-inhibit their own expression, and deltaC (dlc), which encodes a Notch ligand. We previously identified the tortuga (tor) locus in a zebrafish forward genetic screen for genes involved in cyclic transcript regulation and showed that cyclic transcripts accumulate post-splicing in tor mutants. Here we show that cyclic mRNA accumulation in tor mutants is due to loss of pnrc2, which encodes a proline-rich nuclear receptor co-activator implicated in mRNA decay. Using an inducible in vivo reporter system to analyze transcript stability, we find that the her1 3'UTR confers Pnrc2-dependent instability to a heterologous transcript. her1 mRNA decay is Dicer-independent and likely employs a Pnrc2-Upf1-containing mRNA decay complex. Surprisingly, despite accumulation of cyclic transcripts in pnrc2-deficient embryos, we find that cyclic protein is expressed normally. Overall, we show that Pnrc2 promotes 3'UTR-mediated decay of developmentally-regulated segmentation clock transcripts and we uncover an additional post-transcriptional regulatory layer that ensures oscillatory protein expression in the absence of cyclic mRNA decay. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. Robust medical image segmentation for hyperthermia treatment planning

    International Nuclear Information System (INIS)

    Neufeld, E.; Chavannes, N.; Kuster, N.; Samaras, T.

    2005-01-01

    Full text: This work is part of an ongoing effort to develop a comprehensive hyperthermia treatment planning (HTP) tool. The goal is to unify all the steps necessary to perform treatment planning - from image segmentation to optimization of the energy deposition pattern - in a single tool. The bases of the HTP software are the routines and know-how developed in our TRINTY project that resulted the commercial EM platform SEMCAD-X. It incorporates the non-uniform finite-difference time-domain (FDTD) method, permitting the simulation of highly detailed models. Subsequently, in order to create highly resolved patient models, a powerful and robust segmentation tool is needed. A toolbox has been created that allows the flexible combination of various segmentation methods as well as several pre-and postprocessing functions. It works primarily with CT and MRI images, which it can read in various formats. A wide variety of segmentation methods has been implemented. This includes thresholding techniques (k-means classification, expectation maximization and modal histogram analysis for automatic threshold detection, multi-dimensional if required), region growing methods (with hysteretic behavior and simultaneous competitive growing), an interactive marker based watershed transformation, level-set methods (homogeneity and edge based, fast-marching), a flexible live-wire implementation as well as fuzzy connectedness. Due to the large number of tissues that need to be segmented for HTP, no methods that rely on prior knowledge have been implemented. Various edge extraction routines, distance transforms, smoothing techniques (convolutions, anisotropic diffusion, sigma filter...), connected component analysis, topologically flexible interpolation, image algebra and morphological operations are available. Moreover, contours or surfaces can be extracted, simplified and exported. Using these different techniques on several samples, the following conclusions have been drawn: Due to the

  3. Calibrated Full-Waveform Airborne Laser Scanning for 3D Object Segmentation

    Directory of Open Access Journals (Sweden)

    Fanar M. Abed

    2014-05-01

    Full Text Available Segmentation of urban features is considered a major research challenge in the fields of photogrammetry and remote sensing. However, the dense datasets now readily available through airborne laser scanning (ALS offer increased potential for 3D object segmentation. Such potential is further augmented by the availability of full-waveform (FWF ALS data. FWF ALS has demonstrated enhanced performance in segmentation and classification through the additional physical observables which can be provided alongside standard geometric information. However, use of FWF information is not recommended without prior radiometric calibration, taking into account all parameters affecting the backscatter energy. This paper reports the implementation of a radiometric calibration workflow for FWF ALS data, and demonstrates how the resultant FWF information can be used to improve segmentation of an urban area. The developed segmentation algorithm presents a novel approach which uses the calibrated backscatter cross-section as a weighting function to estimate the segmentation similarity measure. The normal vector and the local Euclidian distance are used as criteria to segment the point clouds through a region growing approach. The paper demonstrates the potential to enhance 3D object segmentation in urban areas by integrating the FWF physical backscattered energy alongside geometric information. The method is demonstrated through application to an interest area sampled from a relatively dense FWF ALS dataset. The results are assessed through comparison to those delivered from utilising only geometric information. Validation against a manual segmentation demonstrates a successful automatic implementation, achieving a segmentation accuracy of 82%, and out-performs a purely geometric approach.

  4. Technetium-99 ({sup 99}Tc) in annual growth segments of knotted wrack (Ascophyllum nodosum)

    Energy Technology Data Exchange (ETDEWEB)

    Heldal, Hilde Elise, E-mail: Hilde.Heldal@imr.no [Institute of Marine Research (IMR), PO Box 1870 Nordnes, N-5817 Bergen (Norway); Sjotun, Kjersti, E-mail: Kjersti.Sjotun@bio.uib.no [University of Bergen (UoB), Department of Biology, PO Box 7803, N-5020 Bergen (Norway)

    2010-10-15

    The distribution of technetium-99 ({sup 99}Tc) in annual growth segments of the brown seaweed Ascophyllum nodosum (Fucales, Phaeophyceae) from the southwestern coast of Norway is examined in samples collected from January to November 2006. A twenty-fold increase in the {sup 99}Tc-concentration from the youngest to the oldest growth segments was found. The concentrations ranged from 42 to 98 Bq/kg dry weight (d.w.) and from 964 to 1000 Bq/kg d.w. in growth segments formed in 2006 and 1996, respectively. In addition, a seasonal variation in the {sup 99}Tc concentration was observed in the actively growing 2006-segments: concentrations decreased from 98 Bq/kg d.w. in April to 54 Bq/kg d.w. in June; there was a further reduction from June to August (42 Bq/kg d.w.); and, finally there was an increase from August to November (93 Bq/kg d.w.). In most of the segments formed between 2000 and 2005, there was a tendency of slightly decreasing {sup 99}Tc-concentrations between June and November but this pattern was not observed for the older growth segments. In order to find an explanation for the non-homogenous distribution of {sup 99}Tc within thalli of A. nodosum, different hypotheses are discussed. Uptake and elimination of {sup 99}Tc appears to be most pronounced in the actively growing segments. To date, such non-homogenous distribution of {sup 99}Tc within thalli of A. nodosum has not been taken into consideration, neither in connection with sample collection nor analysis. This paper shows that special protocols must be followed if A. nodosum is going to be used as a bioindicator for {sup 99}Tc in the marine environment. A sampling strategy is proposed.

  5. Statistical segmentation of multidimensional brain datasets

    Science.gov (United States)

    Desco, Manuel; Gispert, Juan D.; Reig, Santiago; Santos, Andres; Pascau, Javier; Malpica, Norberto; Garcia-Barreno, Pedro

    2001-07-01

    This paper presents an automatic segmentation procedure for MRI neuroimages that overcomes part of the problems involved in multidimensional clustering techniques like partial volume effects (PVE), processing speed and difficulty of incorporating a priori knowledge. The method is a three-stage procedure: 1) Exclusion of background and skull voxels using threshold-based region growing techniques with fully automated seed selection. 2) Expectation Maximization algorithms are used to estimate the probability density function (PDF) of the remaining pixels, which are assumed to be mixtures of gaussians. These pixels can then be classified into cerebrospinal fluid (CSF), white matter and grey matter. Using this procedure, our method takes advantage of using the full covariance matrix (instead of the diagonal) for the joint PDF estimation. On the other hand, logistic discrimination techniques are more robust against violation of multi-gaussian assumptions. 3) A priori knowledge is added using Markov Random Field techniques. The algorithm has been tested with a dataset of 30 brain MRI studies (co-registered T1 and T2 MRI). Our method was compared with clustering techniques and with template-based statistical segmentation, using manual segmentation as a gold-standard. Our results were more robust and closer to the gold-standard.

  6. REVIEW ON HARD SEGMENT INFLUENCESON THE PHYSICALPROPERTIES OF THERMOPLASTICPOLYURETHANES

    Directory of Open Access Journals (Sweden)

    Nurul Hidayati Fithriyah

    2012-04-01

    Full Text Available Thermoplastic polyurethanes (TPUs are the fastest growing market in polyurethane technology mainly due to their easy process ability, versatile properties and recyclable nature. They find applications in high performance materials like coatings, adhesives, fibres and foams in a variety of industries ranging from automotive and footwear to medical implants. TPUs are linear block copolymers comprising of alternating soft and hard segments. The versatile properties of TPUs are usually attributed to their phase-separated morphologies. Different parameters are known to affect TPUs physical properties. One of those is their chemical architecture that is the statistical arrangement of hard segments (HS and soft segments (SS.In particular the architecture of the HS will influence the molecular structure and intermolecular interaction. Its role as physical crosslink sites will govern thermal, mechanical and morphological properties. Hence a modification of HS chemical architecture might adjust the ultimate properties of TPU. This implication is important in process control of production and design of application. Therefore this paper will review various studies to understand the effect of different architecture to the properties of TPU.   Keywords: thermoplasticpolyurethanes, hard segment architecture, physical properties

  7. How do normal faults grow?

    OpenAIRE

    Blækkan, Ingvild; Bell, Rebecca; Rotevatn, Atle; Jackson, Christopher; Tvedt, Anette

    2018-01-01

    Faults grow via a sympathetic increase in their displacement and length (isolated fault model), or by rapid length establishment and subsequent displacement accrual (constant-length fault model). To test the significance and applicability of these two models, we use time-series displacement (D) and length (L) data extracted for faults from nature and experiments. We document a range of fault behaviours, from sympathetic D-L fault growth (isolated growth) to sub-vertical D-L growth trajectorie...

  8. Status of the segment interconnect, cable segment ancillary logic, and the cable segment hybrid driver projects

    International Nuclear Information System (INIS)

    Swoboda, C.; Barsotti, E.; Chappa, S.; Downing, R.; Goeransson, G.; Lensy, D.; Moore, G.; Rotolo, C.; Urish, J.

    1985-01-01

    The FASTBUS Segment Interconnect (SI) provides a communication path between two otherwise independent, asynchronous bus segments. In particular, the Segment Interconnect links a backplane crate segment to a cable segment. All standard FASTBUS address and data transactions can be passed through the SI or any number of SIs and segments in a path. Thus systems of arbitrary connection complexity can be formed, allowing simultaneous independent processing, yet still permitting devices associated with one segment to be accessed from others. The model S1 Segment Interconnect and the Cable Segment Ancillary Logic covered in this report comply with all the mandatory features stated in the FASTBUS specification document DOE/ER-0189. A block diagram of the SI is shown

  9. Clinical evaluation of semi-automatic open-source algorithmic software segmentation of the mandibular bone: Practical feasibility and assessment of a new course of action.

    Science.gov (United States)

    Wallner, Jürgen; Hochegger, Kerstin; Chen, Xiaojun; Mischak, Irene; Reinbacher, Knut; Pau, Mauro; Zrnc, Tomislav; Schwenzer-Zimmerer, Katja; Zemann, Wolfgang; Schmalstieg, Dieter; Egger, Jan

    2018-01-01

    Computer assisted technologies based on algorithmic software segmentation are an increasing topic of interest in complex surgical cases. However-due to functional instability, time consuming software processes, personnel resources or licensed-based financial costs many segmentation processes are often outsourced from clinical centers to third parties and the industry. Therefore, the aim of this trial was to assess the practical feasibility of an easy available, functional stable and licensed-free segmentation approach to be used in the clinical practice. In this retrospective, randomized, controlled trail the accuracy and accordance of the open-source based segmentation algorithm GrowCut was assessed through the comparison to the manually generated ground truth of the same anatomy using 10 CT lower jaw data-sets from the clinical routine. Assessment parameters were the segmentation time, the volume, the voxel number, the Dice Score and the Hausdorff distance. Overall semi-automatic GrowCut segmentation times were about one minute. Mean Dice Score values of over 85% and Hausdorff Distances below 33.5 voxel could be achieved between the algorithmic GrowCut-based segmentations and the manual generated ground truth schemes. Statistical differences between the assessment parameters were not significant (p 0.94) for any of the comparison made between the two groups. Complete functional stable and time saving segmentations with high accuracy and high positive correlation could be performed by the presented interactive open-source based approach. In the cranio-maxillofacial complex the used method could represent an algorithmic alternative for image-based segmentation in the clinical practice for e.g. surgical treatment planning or visualization of postoperative results and offers several advantages. Due to an open-source basis the used method could be further developed by other groups or specialists. Systematic comparisons to other segmentation approaches or with a

  10. Ontology-Based Knowledge Organization for the Radiograph Images Segmentation

    Directory of Open Access Journals (Sweden)

    MATEI, O.

    2008-04-01

    Full Text Available The quantity of thoracic radiographies in the medical field is ever growing. An automated system for segmenting the images would help doctors enormously. Some approaches are knowledge-based; therefore we propose here an ontology for this purpose. Thus it is machine oriented, rather than human-oriented. That is all the structures visible on a thoracic image are described from a technical point of view.

  11. Rapid Statistical Learning Supporting Word Extraction From Continuous Speech.

    Science.gov (United States)

    Batterink, Laura J

    2017-07-01

    The identification of words in continuous speech, known as speech segmentation, is a critical early step in language acquisition. This process is partially supported by statistical learning, the ability to extract patterns from the environment. Given that speech segmentation represents a potential bottleneck for language acquisition, patterns in speech may be extracted very rapidly, without extensive exposure. This hypothesis was examined by exposing participants to continuous speech streams composed of novel repeating nonsense words. Learning was measured on-line using a reaction time task. After merely one exposure to an embedded novel word, learners demonstrated significant learning effects, as revealed by faster responses to predictable than to unpredictable syllables. These results demonstrate that learners gained sensitivity to the statistical structure of unfamiliar speech on a very rapid timescale. This ability may play an essential role in early stages of language acquisition, allowing learners to rapidly identify word candidates and "break in" to an unfamiliar language.

  12. Segmented block copolymers with monodisperse aramide end-segments

    NARCIS (Netherlands)

    Araichimani, A.; Gaymans, R.J.

    2008-01-01

    Segmented block copolymers were synthesized using monodisperse diaramide (TT) as hard segments and PTMO with a molecular weight of 2 900 g · mol-1 as soft segments. The aramide: PTMO segment ratio was increased from 1:1 to 2:1 thereby changing the structure from a high molecular weight multi-block

  13. Segmentation of consumer's markets and evaluation of market's segments

    OpenAIRE

    ŠVECOVÁ, Iveta

    2013-01-01

    The goal of this bachelor thesis was to explain a possibly segmentation of consumer´s markets for a chosen company, and to present a suitable goods offer, so it would be suitable to the needs of selected segments. The work is divided into theoretical and practical part. First part describes marketing, segmentation, segmentation of consumer's markets, consumer's market, market's segments a other terms. Second part describes an evaluation of questionnaire survey, discovering of market's segment...

  14. PREPAID TELECOM CUSTOMERS SEGMENTATION USING THE K-MEAN ALGORITHM

    Directory of Open Access Journals (Sweden)

    Marar Liviu Ioan

    2012-07-01

    Full Text Available The scope of relationship marketing is to retain customers and win their loyalty. This can be achieved if the companies’ products and services are developed and sold considering customers’ demands. Fulfilling customers’ demands, taken as the starting point of relationship marketing, can be obtained by acknowledging that the customers’ needs and wishes are heterogeneous. The segmentation of the customers’ base allows operators to overcome this because it illustrates the whole heterogeneous market as the sum of smaller homogeneous markets. The concept of segmentation relies on the high probability of persons grouped into segments based on common demands and behaviours to have a similar response to marketing strategies. This article focuses on the segmentation of a telecom customer base according to specific and noticeable criteria of a certain service. Although the segmentation concept is widely approached in professional literature, articles on the segmentation of a telecom customer base are very scarce, due to the strategic nature of this information. Market segmentation is carried out based on how customers spent their money on credit recharging, on making calls, on sending SMS and on Internet navigation. The method used for customer segmentation is the K-mean cluster analysis. To assess the internal cohesion of the clusters we employed the average sum of squares error indicator, and to determine the differences among the clusters we used the ANOVA and the post-hoc Tukey tests. The analyses revealed seven customer segments with different features and behaviours. The results enable the telecom company to conceive marketing strategies and planning which lead to better understanding of its customers’ needs and ultimately to a more efficient relationship with the subscribers and enhanced customer satisfaction. At the same time, the results enable the description and characterization of expenditure patterns

  15. Vessel-guided airway segmentation based on voxel classification

    DEFF Research Database (Denmark)

    Lo, Pechin Chien Pau; Sporring, Jon; Ashraf, Haseem

    2008-01-01

    This paper presents a method for improving airway tree segmentation using vessel orientation information. We use the fact that an airway branch is always accompanied by an artery, with both structures having similar orientations. This work is based on a  voxel classification airway segmentation...... method proposed previously. The probability of a voxel belonging to the airway, from the voxel classification method, is augmented with an orientation similarity measure as a criterion for region growing. The orientation similarity measure of a voxel indicates how similar is the orientation...... of the surroundings of a voxel, estimated based on a tube model, is to that of a neighboring vessel. The proposed method is tested on 20 CT images from different subjects selected randomly from a lung cancer screening study. Length of the airway branches from the results of the proposed method are significantly...

  16. Growing skull hemangioma: first and unique description in a patient with Klippel-Trénaunay-Weber syndrome.

    Science.gov (United States)

    van der Loo, Lars E; Beckervordersandforth, Jan; Colon, Albert J; Schijns, Olaf E M G

    2017-02-01

    We present the first and unique case of a rapid-growing skull hemangioma in a patient with Klippel-Trénaunay-Weber syndrome. This case report provides evidence that not all rapid-growing, osteolytic skull lesions need to have a malignant character but certainly need a histopathological verification. This material offers insight into the list of rare pathological diagnoses in an infrequent syndrome.

  17. A top-down manner-based DCNN architecture for semantic image segmentation.

    Directory of Open Access Journals (Sweden)

    Kai Qiao

    Full Text Available Given their powerful feature representation for recognition, deep convolutional neural networks (DCNNs have been driving rapid advances in high-level computer vision tasks. However, their performance in semantic image segmentation is still not satisfactory. Based on the analysis of visual mechanism, we conclude that DCNNs in a bottom-up manner are not enough, because semantic image segmentation task requires not only recognition but also visual attention capability. In the study, superpixels containing visual attention information are introduced in a top-down manner, and an extensible architecture is proposed to improve the segmentation results of current DCNN-based methods. We employ the current state-of-the-art fully convolutional network (FCN and FCN with conditional random field (DeepLab-CRF as baselines to validate our architecture. Experimental results of the PASCAL VOC segmentation task qualitatively show that coarse edges and error segmentation results are well improved. We also quantitatively obtain about 2%-3% intersection over union (IOU accuracy improvement on the PASCAL VOC 2011 and 2012 test sets.

  18. A method for smoothing segmented lung boundary in chest CT images

    Science.gov (United States)

    Yim, Yeny; Hong, Helen

    2007-03-01

    To segment low density lung regions in chest CT images, most of methods use the difference in gray-level value of pixels. However, radiodense pulmonary vessels and pleural nodules that contact with the surrounding anatomy are often excluded from the segmentation result. To smooth lung boundary segmented by gray-level processing in chest CT images, we propose a new method using scan line search. Our method consists of three main steps. First, lung boundary is extracted by our automatic segmentation method. Second, segmented lung contour is smoothed in each axial CT slice. We propose a scan line search to track the points on lung contour and find rapidly changing curvature efficiently. Finally, to provide consistent appearance between lung contours in adjacent axial slices, 2D closing in coronal plane is applied within pre-defined subvolume. Our method has been applied for performance evaluation with the aspects of visual inspection, accuracy and processing time. The results of our method show that the smoothness of lung contour was considerably increased by compensating for pulmonary vessels and pleural nodules.

  19. OASIS is Automated Statistical Inference for Segmentation, with applications to multiple sclerosis lesion segmentation in MRI.

    Science.gov (United States)

    Sweeney, Elizabeth M; Shinohara, Russell T; Shiee, Navid; Mateen, Farrah J; Chudgar, Avni A; Cuzzocreo, Jennifer L; Calabresi, Peter A; Pham, Dzung L; Reich, Daniel S; Crainiceanu, Ciprian M

    2013-01-01

    Magnetic resonance imaging (MRI) can be used to detect lesions in the brains of multiple sclerosis (MS) patients and is essential for diagnosing the disease and monitoring its progression. In practice, lesion load is often quantified by either manual or semi-automated segmentation of MRI, which is time-consuming, costly, and associated with large inter- and intra-observer variability. We propose OASIS is Automated Statistical Inference for Segmentation (OASIS), an automated statistical method for segmenting MS lesions in MRI studies. We use logistic regression models incorporating multiple MRI modalities to estimate voxel-level probabilities of lesion presence. Intensity-normalized T1-weighted, T2-weighted, fluid-attenuated inversion recovery and proton density volumes from 131 MRI studies (98 MS subjects, 33 healthy subjects) with manual lesion segmentations were used to train and validate our model. Within this set, OASIS detected lesions with a partial area under the receiver operating characteristic curve for clinically relevant false positive rates of 1% and below of 0.59% (95% CI; [0.50%, 0.67%]) at the voxel level. An experienced MS neuroradiologist compared these segmentations to those produced by LesionTOADS, an image segmentation software that provides segmentation of both lesions and normal brain structures. For lesions, OASIS out-performed LesionTOADS in 74% (95% CI: [65%, 82%]) of cases for the 98 MS subjects. To further validate the method, we applied OASIS to 169 MRI studies acquired at a separate center. The neuroradiologist again compared the OASIS segmentations to those from LesionTOADS. For lesions, OASIS ranked higher than LesionTOADS in 77% (95% CI: [71%, 83%]) of cases. For a randomly selected subset of 50 of these studies, one additional radiologist and one neurologist also scored the images. Within this set, the neuroradiologist ranked OASIS higher than LesionTOADS in 76% (95% CI: [64%, 88%]) of cases, the neurologist 66% (95% CI: [52%, 78

  20. Segmentation of multiple sclerosis lesions in MR images: a review

    International Nuclear Information System (INIS)

    Mortazavi, Daryoush; Kouzani, Abbas Z.; Soltanian-Zadeh, Hamid

    2012-01-01

    Multiple sclerosis (MS) is an inflammatory demyelinating disease that the parts of the nervous system through the lesions generated in the white matter of the brain. It brings about disabilities in different organs of the body such as eyes and muscles. Early detection of MS and estimation of its progression are critical for optimal treatment of the disease. For diagnosis and treatment evaluation of MS lesions, they may be detected and segmented in Magnetic Resonance Imaging (MRI) scans of the brain. However, due to the large amount of MRI data to be analyzed, manual segmentation of the lesions by clinical experts translates into a very cumbersome and time consuming task. In addition, manual segmentation is subjective and prone to human errors. Several groups have developed computerized methods to detect and segment MS lesions. These methods are not categorized and compared in the past. This paper reviews and compares various MS lesion segmentation methods proposed in recent years. It covers conventional methods like multilevel thresholding and region growing, as well as more recent Bayesian methods that require parameter estimation algorithms. It also covers parameter estimation methods like expectation maximization and adaptive mixture model which are among unsupervised techniques as well as kNN and Parzen window methods that are among supervised techniques. Integration of knowledge-based methods such as atlas-based approaches with Bayesian methods increases segmentation accuracy. In addition, employing intelligent classifiers like Fuzzy C-Means, Fuzzy Inference Systems, and Artificial Neural Networks reduces misclassified voxels. (orig.)

  1. Segmentation of multiple sclerosis lesions in MR images: a review

    Energy Technology Data Exchange (ETDEWEB)

    Mortazavi, Daryoush; Kouzani, Abbas Z. [Deakin University, School of Engineering, Geelong, Victoria (Australia); Soltanian-Zadeh, Hamid [Henry Ford Health System, Image Analysis Laboratory, Radiology Department, Detroit, MI (United States); University of Tehran, Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, Tehran (Iran, Islamic Republic of); School of Cognitive Sciences, Institute for Studies in Theoretical Physics and Mathematics (IPM), Tehran (Iran, Islamic Republic of)

    2012-04-15

    Multiple sclerosis (MS) is an inflammatory demyelinating disease that the parts of the nervous system through the lesions generated in the white matter of the brain. It brings about disabilities in different organs of the body such as eyes and muscles. Early detection of MS and estimation of its progression are critical for optimal treatment of the disease. For diagnosis and treatment evaluation of MS lesions, they may be detected and segmented in Magnetic Resonance Imaging (MRI) scans of the brain. However, due to the large amount of MRI data to be analyzed, manual segmentation of the lesions by clinical experts translates into a very cumbersome and time consuming task. In addition, manual segmentation is subjective and prone to human errors. Several groups have developed computerized methods to detect and segment MS lesions. These methods are not categorized and compared in the past. This paper reviews and compares various MS lesion segmentation methods proposed in recent years. It covers conventional methods like multilevel thresholding and region growing, as well as more recent Bayesian methods that require parameter estimation algorithms. It also covers parameter estimation methods like expectation maximization and adaptive mixture model which are among unsupervised techniques as well as kNN and Parzen window methods that are among supervised techniques. Integration of knowledge-based methods such as atlas-based approaches with Bayesian methods increases segmentation accuracy. In addition, employing intelligent classifiers like Fuzzy C-Means, Fuzzy Inference Systems, and Artificial Neural Networks reduces misclassified voxels. (orig.)

  2. A spatiotemporal-based scheme for efficient registration-based segmentation of thoracic 4-D MRI.

    Science.gov (United States)

    Yang, Y; Van Reeth, E; Poh, C L; Tan, C H; Tham, I W K

    2014-05-01

    Dynamic three-dimensional (3-D) (four-dimensional, 4-D) magnetic resonance (MR) imaging is gaining importance in the study of pulmonary motion for respiratory diseases and pulmonary tumor motion for radiotherapy. To perform quantitative analysis using 4-D MR images, segmentation of anatomical structures such as the lung and pulmonary tumor is required. Manual segmentation of entire thoracic 4-D MRI data that typically contains many 3-D volumes acquired over several breathing cycles is extremely tedious, time consuming, and suffers high user variability. This requires the development of new automated segmentation schemes for 4-D MRI data segmentation. Registration-based segmentation technique that uses automatic registration methods for segmentation has been shown to be an accurate method to segment structures for 4-D data series. However, directly applying registration-based segmentation to segment 4-D MRI series lacks efficiency. Here we propose an automated 4-D registration-based segmentation scheme that is based on spatiotemporal information for the segmentation of thoracic 4-D MR lung images. The proposed scheme saved up to 95% of computation amount while achieving comparable accurate segmentations compared to directly applying registration-based segmentation to 4-D dataset. The scheme facilitates rapid 3-D/4-D visualization of the lung and tumor motion and potentially the tracking of tumor during radiation delivery.

  3. Compartmental analysis of roots in intact rapidly-growing Spergularia marina and Lactuca sativa: partial characterization of the symplasms functional in the radial transport of Na+ and K+

    International Nuclear Information System (INIS)

    Lazof, D.B.

    1987-01-01

    Techniques of compartmental analysis were adapted to the study of intact roots of rapidly-growing Spergularia marine and Lactuca sativa. Using large numbers of plants short time-courses of uptake and chase, 42 K + and 22 Na + transport could be resolved, even during a chase following a brief 10 minute labeling period. The use of intact plant systems allowed distinction of that portion of the isotope flux into the root, associated with the ion-conducting symplasms. A small compartment, which rapidly (t/sub .5/ + , accounting for the observed obtention of linear translocation rates within minutes of transferring to labeled solution. The ion contents of this compartment varied in proportion to the external ion concentration. When K + was at a high external concentration, labeled K + exchanged into this same symplasm, but chasing a short pulse indicated that K + transport to the xylem was not through a rapidly-exchanging compartment. At physiological concentrations of K + the evidence indicated that transport of K + across the root proceeded through a compartment which was not exchanging rapidly with the external medium. The rise to a linear rate of isotope translocation was gradual and translocation during a chase, following a brief pulse,was prolonged, indicating that this compartment retained its specific activity for a considerable period

  4. Locally excitatory, globally inhibitory oscillator networks: theory and application to scene segmentation

    Science.gov (United States)

    Wang, DeLiang; Terman, David

    1995-01-01

    A novel class of locally excitatory, globally inhibitory oscillator networks (LEGION) is proposed and investigated analytically and by computer simulation. The model of each oscillator corresponds to a standard relaxation oscillator with two time scales. The network exhibits a mechanism of selective gating, whereby an oscillator jumping up to its active phase rapidly recruits the oscillators stimulated by the same pattern, while preventing other oscillators from jumping up. We show analytically that with the selective gating mechanism the network rapidly achieves both synchronization within blocks of oscillators that are stimulated by connected regions and desynchronization between different blocks. Computer simulations demonstrate LEGION's promising ability for segmenting multiple input patterns in real time. This model lays a physical foundation for the oscillatory correlation theory of feature binding, and may provide an effective computational framework for scene segmentation and figure/ground segregation.

  5. Impact of growing income inequality on sustainable development in China: a provincial-level analysis

    NARCIS (Netherlands)

    Heerink, N.B.M.; Ma, J.

    2006-01-01

    A growing body of literature has documented the rapidly increasing income disparities that accompanied China's economic growth in the 1980s and 1990s, and the driving factors behind this. Growing income inequality in its turn may have important implications for the accumulation of physical capital,

  6. Optical coherence tomography in anterior segment imaging

    Science.gov (United States)

    Kalev-Landoy, Maya; Day, Alexander C.; Cordeiro, M. Francesca; Migdal, Clive

    2008-01-01

    Purpose To evaluate the ability of optical coherence tomography (OCT), designed primarily to image the posterior segment, to visualize the anterior chamber angle (ACA) in patients with different angle configurations. Methods In a prospective observational study, the anterior segments of 26 eyes of 26 patients were imaged using the Zeiss Stratus OCT, model 3000. Imaging of the anterior segment was achieved by adjusting the focusing control on the Stratus OCT. A total of 16 patients had abnormal angle configurations including narrow or closed angles and plateau irides, and 10 had normal angle configurations as determined by prior full ophthalmic examination, including slit-lamp biomicroscopy and gonioscopy. Results In all cases, OCT provided high-resolution information regarding iris configuration. The ACA itself was clearly visualized in patients with narrow or closed angles, but not in patients with open angles. Conclusions Stratus OCT offers a non-contact, convenient and rapid method of assessing the configuration of the anterior chamber. Despite its limitations, it may be of help during the routine clinical assessment and treatment of patients with glaucoma, particularly when gonioscopy is not possible or difficult to interpret. PMID:17355288

  7. Occupational employment trends in selected nuclear industry segments in the United States of America

    International Nuclear Information System (INIS)

    Blair, L.M.

    1980-01-01

    The United States of America's nuclear energy industry expanded rapidly between 1968 and 1977, with total employment increasing by approximately 60%. Between 1973 and 1977 employment grew at a rate of 6.8% per year. The nuclear industry appears to have reached a mature status with the primary focus on commercial activities. The relative number of workers involved in research and development activities, outside of contract research facilities, has declined considerably since 1968 but appears to have stabilized. The industry labour force still has a relatively high proportion (43%) of scientific, engineering and technical workers. The occupational employment composition appears to have stabilized in the various nuclear segments indicating the emergence of longer run occupational distribution patterns. Employment expanded rapidly between 1968 and 1977 in most nuclear segments, with the exception of the research and development segment, where employment decreased by one-third. The present uncertainties concerning nuclear power development could have substantial impacts on the nuclear-related scientific, engineering, and technical labour force if a sizeable contraction occurs in reactor design and manufacturing and in design of nuclear facilities. (author)

  8. Segmentation of foreground apple targets by fusing visual attention mechanism and growth rules of seed points

    Energy Technology Data Exchange (ETDEWEB)

    Qu, W.; Shang, W.; Shao, Y.; Wang, D.; Yu, X.; Song, H.

    2015-07-01

    Accurate segmentation of apple targets is one of the most important problems to be solved in the vision system of apple picking robots. This work aimed to solve the difficulties that background targets often bring to foreground targets segmentation, by fusing the visual attention mechanism and the growth rule of seed points. Background targets could be eliminated by extracting the ROI (region of interest) of apple targets; the ROI was roughly segmented on the HSV color space, and then each of the pixels was used as a seed growing point. The growth rule of the seed points was adopted to obtain the whole area of apple targets from seed growing points. The proposed method was tested with 20 images captured in a natural scene, including 54 foreground apple targets and approximately 84 background apple targets. Experimental results showed that the proposed method can remove background targets and focus on foreground targets, while the k-means algorithm and the chromatic aberration algorithm cannot. Additionally, its average segmentation error rate was 13.23%, which is 2.71% higher than that of the k-means algorithm and 2.95% lower than that of the chromatic aberration algorithm. In conclusion, the proposed method contributes to the vision system of apple-picking robots to locate foreground apple targets quickly and accurately under a natural scene. (Author)

  9. Generation of a genetically encoded marker of rod photoreceptor outer segment growth and renewal

    Directory of Open Access Journals (Sweden)

    John J. Willoughby

    2011-10-01

    Vertebrate photoreceptors are specialized light sensing neurons. The photoreceptor outer segment is a highly modified cilium where photons of light are transduced into a chemical and electrical signal. The outer segment has the typical cilary axoneme but, in addition, it has a large number of densely packed, stacked, intramembranous discs. The molecular and cellular mechanisms that contribute to vertebrate photoreceptor outer segment morphogenesis are still largely unknown. Unlike typical cilia, the outer segment is continuously regenerated or renewed throughout the life of the animal through the combined process of distal outer segment shedding and proximal outer segment growth. The process of outer segment renewal was discovered over forty years ago, but we still lack an understanding of how photoreceptors renew their outer segments and few, if any, molecular mechanisms that regulate outer segment growth or shedding have been described. Our lack of progress in understanding how photoreceptors renew their outer segments has been hampered by the difficulty in measuring rates of renewal. We have created a new method that uses heat-shock induction of a fluorescent protein that can be used to rapidly measure outer segment growth rates. We describe this method, the stable transgenic line we created, and the growth rates observed in larval and adult rod photoreceptors using this new method. This new method will allow us to begin to define the genetic and molecular mechanisms that regulate rod outer segment renewal, a crucial aspect of photoreceptor function and, possibly, viability.

  10. An optimized process flow for rapid segmentation of cortical bones of the craniofacial skeleton using the level-set method.

    Science.gov (United States)

    Szwedowski, T D; Fialkov, J; Pakdel, A; Whyne, C M

    2013-01-01

    Accurate representation of skeletal structures is essential for quantifying structural integrity, for developing accurate models, for improving patient-specific implant design and in image-guided surgery applications. The complex morphology of thin cortical structures of the craniofacial skeleton (CFS) represents a significant challenge with respect to accurate bony segmentation. This technical study presents optimized processing steps to segment the three-dimensional (3D) geometry of thin cortical bone structures from CT images. In this procedure, anoisotropic filtering and a connected components scheme were utilized to isolate and enhance the internal boundaries between craniofacial cortical and trabecular bone. Subsequently, the shell-like nature of cortical bone was exploited using boundary-tracking level-set methods with optimized parameters determined from large-scale sensitivity analysis. The process was applied to clinical CT images acquired from two cadaveric CFSs. The accuracy of the automated segmentations was determined based on their volumetric concurrencies with visually optimized manual segmentations, without statistical appraisal. The full CFSs demonstrated volumetric concurrencies of 0.904 and 0.719; accuracy increased to concurrencies of 0.936 and 0.846 when considering only the maxillary region. The highly automated approach presented here is able to segment the cortical shell and trabecular boundaries of the CFS in clinical CT images. The results indicate that initial scan resolution and cortical-trabecular bone contrast may impact performance. Future application of these steps to larger data sets will enable the determination of the method's sensitivity to differences in image quality and CFS morphology.

  11. Attenuation correction with region growing method used in the positron emission mammography imaging system

    Science.gov (United States)

    Gu, Xiao-Yue; Li, Lin; Yin, Peng-Fei; Yun, Ming-Kai; Chai, Pei; Huang, Xian-Chao; Sun, Xiao-Li; Wei, Long

    2015-10-01

    The Positron Emission Mammography imaging system (PEMi) provides a novel nuclear diagnosis method dedicated for breast imaging. With a better resolution than whole body PET, PEMi can detect millimeter-sized breast tumors. To address the requirement of semi-quantitative analysis with a radiotracer concentration map of the breast, a new attenuation correction method based on a three-dimensional seeded region growing image segmentation (3DSRG-AC) method has been developed. The method gives a 3D connected region as the segmentation result instead of image slices. The continuity property of the segmentation result makes this new method free of activity variation of breast tissues. The threshold value chosen is the key process for the segmentation method. The first valley in the grey level histogram of the reconstruction image is set as the lower threshold, which works well in clinical application. Results show that attenuation correction for PEMi improves the image quality and the quantitative accuracy of radioactivity distribution determination. Attenuation correction also improves the probability of detecting small and early breast tumors. Supported by Knowledge Innovation Project of The Chinese Academy of Sciences (KJCX2-EW-N06)

  12. VISION AND STRATEGIC THINKING IN THE ROMANIAN FAST GROWING FIRMS MANAGEMENT

    Directory of Open Access Journals (Sweden)

    Nicolae BIBU

    2016-07-01

    Full Text Available The purpose of this paper is to present preliminary specific issues concerning the vision and the strategic thinking of the managers of Romanian fast growing firms in the years of rapid growth. This paper clarifies two research questions. (1 The first research question is what is the message of the manager's vision of the Romanian fast growing firms? Therefore, we must first verify if the managers of the Romanian fast growing firms have a concrete vision about the business they run and if so, what is the vision of the managers about the companies that they lead? (2 The second research question is what findings can be drawn about the role of strategic thinking of the managers in the management of the Romanian fast growing firms? The research that we have conducted is a qualitative research. The research method that we used is the interview. The interview is specific to qualitative research. Regarding the method of analysis that we used it is the content analysis. The research was conducted on a total of 17 Romanian fast growing firms that are located in Timiș County. The firms were identified based on a specific selection criteria set after a thorough review of the literature in the field. The 17 companies that we have analysed represent the foundation of 17 in-depth case studies, which we believe helped us to better understand what it means in the Romanian context to grow fast, through the entrepreneurs managers vision and strategic thinking. The results presented in this paper come to strengthen the results reached by other researchers in this field. The results present an image of the current Romanian context – about the role of strategic thinking of the entrepreneur manager in the management of Romanian fast growing firms. The paper presents a detailed analysis of managers' vision of the Romanian fast growing firms. The paper also presents findings about the role of strategic thinking in helping managers achieve rapid growth in the

  13. Fully convolutional neural networks improve abdominal organ segmentation

    Science.gov (United States)

    Bobo, Meg F.; Bao, Shunxing; Huo, Yuankai; Yao, Yuang; Virostko, Jack; Plassard, Andrew J.; Lyu, Ilwoo; Assad, Albert; Abramson, Richard G.; Hilmes, Melissa A.; Landman, Bennett A.

    2018-03-01

    Abdominal image segmentation is a challenging, yet important clinical problem. Variations in body size, position, and relative organ positions greatly complicate the segmentation process. Historically, multi-atlas methods have achieved leading results across imaging modalities and anatomical targets. However, deep learning is rapidly overtaking classical approaches for image segmentation. Recently, Zhou et al. showed that fully convolutional networks produce excellent results in abdominal organ segmentation of computed tomography (CT) scans. Yet, deep learning approaches have not been applied to whole abdomen magnetic resonance imaging (MRI) segmentation. Herein, we evaluate the applicability of an existing fully convolutional neural network (FCNN) designed for CT imaging to segment abdominal organs on T2 weighted (T2w) MRI's with two examples. In the primary example, we compare a classical multi-atlas approach with FCNN on forty-five T2w MRI's acquired from splenomegaly patients with five organs labeled (liver, spleen, left kidney, right kidney, and stomach). Thirty-six images were used for training while nine were used for testing. The FCNN resulted in a Dice similarity coefficient (DSC) of 0.930 in spleens, 0.730 in left kidneys, 0.780 in right kidneys, 0.913 in livers, and 0.556 in stomachs. The performance measures for livers, spleens, right kidneys, and stomachs were significantly better than multi-atlas (p < 0.05, Wilcoxon rank-sum test). In a secondary example, we compare the multi-atlas approach with FCNN on 138 distinct T2w MRI's with manually labeled pancreases (one label). On the pancreas dataset, the FCNN resulted in a median DSC of 0.691 in pancreases versus 0.287 for multi-atlas. The results are highly promising given relatively limited training data and without specific training of the FCNN model and illustrate the potential of deep learning approaches to transcend imaging modalities. 1

  14. Evaluation of segmentation algorithms for generation of patient models in radiofrequency hyperthermia

    International Nuclear Information System (INIS)

    Wust, P.; Gellermann, J.; Beier, J.; Tilly, W.; Troeger, J.; Felix, R.; Wegner, S.; Oswald, H.; Stalling, D.; Hege, H.C.; Deuflhard, P.

    1998-01-01

    Time-efficient and easy-to-use segmentation algorithms (contour generation) are a precondition for various applications in radiation oncology, especially for planning purposes in hyperthermia. We have developed the three following algorithms for contour generation and implemented them in an editor of the HyperPlan hyperthermia planning system. Firstly, a manual contour input with numerous correction and editing options. Secondly, a volume growing algorithm with adjustable threshold range and minimal region size. Thirdly, a watershed transformation in two and three dimensions. In addition, the region input function of the Helax commercial radiation therapy planning system was available for comparison. All four approaches were applied under routine conditions to two-dimensional computed tomographic slices of the superior thoracic aperture, mid-chest, upper abdomen, mid-abdomen, pelvis and thigh; they were also applied to a 3D CT sequence of 72 slices using the three-dimensional extension of the algorithms. Time to generate the contours and their quality with respect to a reference model were determined. Manual input for a complete patient model required approximately 5 to 6 h for 72 CT slices (4.5 min/slice). If slight irregularities at object boundaries are accepted, this time can be reduced to 3.5 min/slice using the volume growing algorithm. However, generating a tetrahedron mesh from such a contour sequence for hyperthermia planning (the basis for finite-element algorithms) requires a significant amount of postediting. With the watershed algorithm extended to three dimensions, processing time can be further reduced to 3 min/slice while achieving satisfactory contour quality. Therefore, this method is currently regarded as offering some potential for efficient automated model generation in hyperthermia. In summary, the 3D volume growing algorithm and watershed transformation are both suitable for segmentation of even low-contrast objects. However, they are not

  15. NPOESS Tools for Rapid Algorithm Updates

    Science.gov (United States)

    Route, G.; Grant, K. D.; Hughes, B.; Reed, B.

    2009-12-01

    The National Oceanic and Atmospheric Administration (NOAA), Department of Defense (DoD), and National Aeronautics and Space Administration (NASA) are jointly acquiring the next-generation weather and environmental satellite system; the National Polar-orbiting Operational Environmental Satellite System (NPOESS). NPOESS replaces the current Polar-orbiting Operational Environmental Satellites (POES) managed by NOAA and the Defense Meteorological Satellite Program (DMSP) managed by the DoD. The NPOESS satellites carry a suite of sensors that collect meteorological, oceanographic, climatological, and solar-geophysical observations of the earth, atmosphere, and space. The ground data processing segment for NPOESS is the Interface Data Processing Segment (IDPS), developed by Raytheon Intelligence and Information Systems. The IDPS processes both NPP and NPOESS satellite data to provide environmental data products to NOAA and DoD processing centers operated by the United States government. Northrop Grumman Aerospace Systems Algorithms and Data Products (A&DP) organization is responsible for the algorithms that produce the EDRs, including their quality aspects. As the Calibration and Validation activities move forward following both the NPP launch and subsequent NPOESS launches, rapid algorithm updates may be required. Raytheon and Northrop Grumman have developed tools and processes to enable changes to be evaluated, tested, and moved into the operational baseline in a rapid and efficient manner. This presentation will provide an overview of the tools available to the Cal/Val teams to ensure rapid and accurate assessment of algorithm changes, along with the processes in place to ensure baseline integrity.

  16. Brookhaven segment interconnect

    International Nuclear Information System (INIS)

    Morse, W.M.; Benenson, G.; Leipuner, L.B.

    1983-01-01

    We have performed a high energy physics experiment using a multisegment Brookhaven FASTBUS system. The system was composed of three crate segments and two cable segments. We discuss the segment interconnect module which permits communication between the various segments

  17. An Automatic Indirect Immunofluorescence Cell Segmentation System

    Directory of Open Access Journals (Sweden)

    Yung-Kuan Chan

    2014-01-01

    Full Text Available Indirect immunofluorescence (IIF with HEp-2 cells has been used for the detection of antinuclear autoantibodies (ANA in systemic autoimmune diseases. The ANA testing allows us to scan a broad range of autoantibody entities and to describe them by distinct fluorescence patterns. Automatic inspection for fluorescence patterns in an IIF image can assist physicians, without relevant experience, in making correct diagnosis. How to segment the cells from an IIF image is essential in developing an automatic inspection system for ANA testing. This paper focuses on the cell detection and segmentation; an efficient method is proposed for automatically detecting the cells with fluorescence pattern in an IIF image. Cell culture is a process in which cells grow under control. Cell counting technology plays an important role in measuring the cell density in a culture tank. Moreover, assessing medium suitability, determining population doubling times, and monitoring cell growth in cultures all require a means of quantifying cell population. The proposed method also can be used to count the cells from an image taken under a fluorescence microscope.

  18. Rapid mass movement of chloroplasts during segment formation of the calcifying siphonalean green alga, Halimeda macroloba

    DEFF Research Database (Denmark)

    Larkum, Anthony W D; Salih, Anya; Kühl, Michael

    2011-01-01

    The calcifying siphonalean green alga, Halimeda macroloba is abundant on coral reefs and is important in the production of calcium carbonate sediments. The process by which new green segments are formed over-night is revealed here for the first time.......The calcifying siphonalean green alga, Halimeda macroloba is abundant on coral reefs and is important in the production of calcium carbonate sediments. The process by which new green segments are formed over-night is revealed here for the first time....

  19. An improved K-means clustering algorithm in agricultural image segmentation

    Science.gov (United States)

    Cheng, Huifeng; Peng, Hui; Liu, Shanmei

    Image segmentation is the first important step to image analysis and image processing. In this paper, according to color crops image characteristics, we firstly transform the color space of image from RGB to HIS, and then select proper initial clustering center and cluster number in application of mean-variance approach and rough set theory followed by clustering calculation in such a way as to automatically segment color component rapidly and extract target objects from background accurately, which provides a reliable basis for identification, analysis, follow-up calculation and process of crops images. Experimental results demonstrate that improved k-means clustering algorithm is able to reduce the computation amounts and enhance precision and accuracy of clustering.

  20. Active Segmentation.

    Science.gov (United States)

    Mishra, Ajay; Aloimonos, Yiannis

    2009-01-01

    The human visual system observes and understands a scene/image by making a series of fixations. Every fixation point lies inside a particular region of arbitrary shape and size in the scene which can either be an object or just a part of it. We define as a basic segmentation problem the task of segmenting that region containing the fixation point. Segmenting the region containing the fixation is equivalent to finding the enclosing contour- a connected set of boundary edge fragments in the edge map of the scene - around the fixation. This enclosing contour should be a depth boundary.We present here a novel algorithm that finds this bounding contour and achieves the segmentation of one object, given the fixation. The proposed segmentation framework combines monocular cues (color/intensity/texture) with stereo and/or motion, in a cue independent manner. The semantic robots of the immediate future will be able to use this algorithm to automatically find objects in any environment. The capability of automatically segmenting objects in their visual field can bring the visual processing to the next level. Our approach is different from current approaches. While existing work attempts to segment the whole scene at once into many areas, we segment only one image region, specifically the one containing the fixation point. Experiments with real imagery collected by our active robot and from the known databases 1 demonstrate the promise of the approach.

  1. Prosthetic component segmentation with blur compensation: a fast method for 3D fluoroscopy.

    Science.gov (United States)

    Tarroni, Giacomo; Tersi, Luca; Corsi, Cristiana; Stagni, Rita

    2012-06-01

    A new method for prosthetic component segmentation from fluoroscopic images is presented. The hybrid approach we propose combines diffusion filtering, region growing and level-set techniques without exploiting any a priori knowledge of the analyzed geometry. The method was evaluated on a synthetic dataset including 270 images of knee and hip prosthesis merged to real fluoroscopic data simulating different conditions of blurring and illumination gradient. The performance of the method was assessed by comparing estimated contours to references using different metrics. Results showed that the segmentation procedure is fast, accurate, independent on the operator as well as on the specific geometrical characteristics of the prosthetic component, and able to compensate for amount of blurring and illumination gradient. Importantly, the method allows a strong reduction of required user interaction time when compared to traditional segmentation techniques. Its effectiveness and robustness in different image conditions, together with simplicity and fast implementation, make this prosthetic component segmentation procedure promising and suitable for multiple clinical applications including assessment of in vivo joint kinematics in a variety of cases.

  2. Automatic segmentation of the lateral geniculate nucleus: Application to control and glaucoma patients.

    Science.gov (United States)

    Wang, Jieqiong; Miao, Wen; Li, Jing; Li, Meng; Zhen, Zonglei; Sabel, Bernhard; Xian, Junfang; He, Huiguang

    2015-11-30

    The lateral geniculate nucleus (LGN) is a key relay center of the visual system. Because the LGN morphology is affected by different diseases, it is of interest to analyze its morphology by segmentation. However, existing LGN segmentation methods are non-automatic, inefficient and prone to experimenters' bias. To address these problems, we proposed an automatic LGN segmentation algorithm based on T1-weighted imaging. First, the prior information of LGN was used to create a prior mask. Then region growing was applied to delineate LGN. We evaluated this automatic LGN segmentation method by (1) comparison with manually segmented LGN, (2) anatomically locating LGN in the visual system via LGN-based tractography, (3) application to control and glaucoma patients. The similarity coefficients of automatic segmented LGN and manually segmented one are 0.72 (0.06) for the left LGN and 0.77 (0.07) for the right LGN. LGN-based tractography shows the subcortical pathway seeding from LGN passes the optic tract and also reaches V1 through the optic radiation, which is consistent with the LGN location in the visual system. In addition, LGN asymmetry as well as LGN atrophy along with age is observed in normal controls. The investigation of glaucoma effects on LGN volumes demonstrates that the bilateral LGN volumes shrink in patients. The automatic LGN segmentation is objective, efficient, valid and applicable. Experiment results proved the validity and applicability of the algorithm. Our method will speed up the research on visual system and greatly enhance studies of different vision-related diseases. Copyright © 2015 Elsevier B.V. All rights reserved.

  3. Auxin Does Not Alter the Permeability of Pea Segments to Tritium-labeled Water.

    Science.gov (United States)

    Dowler, M J; Rayle, D L

    1974-02-01

    The possibility of an auxin effect on the permeability of pea (Pisum sativum L. ev. Alaska) segments to tritium-labeled water has been investigated by three separate laboratories, and the combined results are presented. We were unable to obtain any indication of a rapid effect of indoleacetic acid on the efflux of (3)HHO when pea segments previously "loaded" for 90 minutes with (3)HHO were transferred to unlabeled aqueous medium with indoleacetic acid. We were able to confirm that segments pretreated with (3)HHO plus indoleacetic acid for 60 to 90 minutes can show an enhanced (3)HHO release as compared with minus indoleacetic acid controls. However, this phenomenon appears to be due to an increased uptake of (3)HHO during the prolonged indoleacetic acid pretreatment, and therefore we conclude that auxin does not alter the permeability of pea segments to (3)HHO in either short term or long term tests. We confirm previous reports that the uptake of (3)HHO in pea segments proceeds largely through the cut surfaces, and that the cuticle is a potent barrier to (3)HHO flux.

  4. Multiple Vehicle Detection and Segmentation in Malaysia Traffic Flow

    Science.gov (United States)

    Fariz Hasan, Ahmad; Fikri Che Husin, Mohd; Affendi Rosli, Khairul; Norhafiz Hashim, Mohd; Faiz Zainal Abidin, Amar

    2018-03-01

    Vision based system are widely used in the field of Intelligent Transportation System (ITS) to extract a large amount of information to analyze traffic scenes. By rapid number of vehicles on the road as well as significant increase on cameras dictated the need for traffic surveillance systems. This system can take over the burden some task was performed by human operator in traffic monitoring centre. The main technique proposed by this paper is concentrated on developing a multiple vehicle detection and segmentation focusing on monitoring through Closed Circuit Television (CCTV) video. The system is able to automatically segment vehicle extracted from heavy traffic scene by optical flow estimation alongside with blob analysis technique in order to detect the moving vehicle. Prior to segmentation, blob analysis technique will compute the area of interest region corresponding to moving vehicle which will be used to create bounding box on that particular vehicle. Experimental validation on the proposed system was performed and the algorithm is demonstrated on various set of traffic scene.

  5. JPSS CGS Tools For Rapid Algorithm Updates

    Science.gov (United States)

    Smith, D. C.; Grant, K. D.

    2011-12-01

    The National Oceanic and Atmospheric Administration (NOAA) and National Aeronautics and Space Administration (NASA) are jointly acquiring the next-generation civilian weather and environmental satellite system: the Joint Polar Satellite System (JPSS). JPSS will contribute the afternoon orbit component and ground processing system of the restructured National Polar-orbiting Operational Environmental Satellite System (NPOESS). As such, JPSS replaces the current Polar-orbiting Operational Environmental Satellites (POES) managed by NOAA and the ground processing component of both POES and the Defense Meteorological Satellite Program (DMSP) replacement known as the Defense Weather Satellite System (DWSS), managed by the Department of Defense (DoD). The JPSS satellites will carry a suite of sensors designed to collect meteorological, oceanographic, climatological, and solar-geophysical observations of the earth, atmosphere, and space. The ground processing system for JPSS is known as the JPSS Common Ground System (JPSS CGS), and consists of a Command, Control, and Communications Segment (C3S) and the Interface Data Processing Segment (IDPS). Both are developed by Raytheon Intelligence and Information Systems (IIS). The Interface Data Processing Segment will process NPOESS Preparatory Project, Joint Polar Satellite System and Defense Weather Satellite System satellite data to provide environmental data products to NOAA and DoD processing centers operated by the United States government. Under NPOESS, Northrop Grumman Aerospace Systems Algorithms and Data Products (A&DP) organization was responsible for the algorithms that produce the EDRs, including their quality aspects. For JPSS, that responsibility has transferred to NOAA's Center for Satellite Applications & Research (STAR). As the Calibration and Validation (Cal/Val) activities move forward following both the NPP launch and subsequent JPSS and DWSS launches, rapid algorithm updates may be required. Raytheon and

  6. GeoSegmenter: A statistically learned Chinese word segmenter for the geoscience domain

    Science.gov (United States)

    Huang, Lan; Du, Youfu; Chen, Gongyang

    2015-03-01

    Unlike English, the Chinese language has no space between words. Segmenting texts into words, known as the Chinese word segmentation (CWS) problem, thus becomes a fundamental issue for processing Chinese documents and the first step in many text mining applications, including information retrieval, machine translation and knowledge acquisition. However, for the geoscience subject domain, the CWS problem remains unsolved. Although a generic segmenter can be applied to process geoscience documents, they lack the domain specific knowledge and consequently their segmentation accuracy drops dramatically. This motivated us to develop a segmenter specifically for the geoscience subject domain: the GeoSegmenter. We first proposed a generic two-step framework for domain specific CWS. Following this framework, we built GeoSegmenter using conditional random fields, a principled statistical framework for sequence learning. Specifically, GeoSegmenter first identifies general terms by using a generic baseline segmenter. Then it recognises geoscience terms by learning and applying a model that can transform the initial segmentation into the goal segmentation. Empirical experimental results on geoscience documents and benchmark datasets showed that GeoSegmenter could effectively recognise both geoscience terms and general terms.

  7. Single-segment and double-segment INTACS for post-LASIK ectasia.

    Directory of Open Access Journals (Sweden)

    Hassan Hashemi

    2014-09-01

    Full Text Available The objective of the present study was to compare single segment and double segment INTACS rings in the treatment of post-LASIK ectasia. In this interventional study, 26 eyes with post-LASIK ectasia were assessed. Ectasia was defined as progressive myopia regardless of astigmatism, along with topographic evidence of inferior steepening of the cornea after LASIK. We excluded those with a history of intraocular surgery, certain eye conditions, and immune disorders, as well as monocular, pregnant and lactating patients. A total of 11 eyes had double ring and 15 eyes had single ring implantation. Visual and refractive outcomes were compared with preoperative values based on the number of implanted INTACS rings. Pre and postoperative spherical equivalent were -3.92 and -2.29 diopter (P=0.007. The spherical equivalent decreased by 1 ± 3.2 diopter in the single-segment group and 2.56 ± 1.58 diopter in the double-segment group (P=0.165. Mean preoperative astigmatism was 2.38 ± 1.93 diopter which decreased to 2.14 ± 1.1 diopter after surgery (P=0.508; 0.87 ± 1.98 diopter decrease in the single-segment group and 0.67 ± 1.2 diopter increase in the double-segment group (P=0.025. Nineteen patients (75% gained one or two lines, and only three, who were all in the double-segment group, lost one or two lines of best corrected visual acuity. The spherical equivalent and vision significantly decreased in all patients. In these post-LASIK ectasia patients, the spherical equivalent was corrected better with two segments compared to single segment implantation; nonetheless, the level of astigmatism in the single-segment group was significantly better than that in the double-segment group.

  8. FAST-GROWING COMPANIES FROM TIMIS COUNTRY: DOES THE AGE MATTER?

    Directory of Open Access Journals (Sweden)

    ALB MARIA

    2015-03-01

    Full Text Available This paper examines the relation between the company’s age and its growth and analyses the influence of age on growth by studying a specific group of companies, namely fast-growing companies from the Timis County, Romania. We have studied the performance of the fast-growing companies in the period of 2010-2013 using the STATA IC 12 software application. A linear regression analysis model with two variables was used. The dependent variable used was the rapid growth of the company, measured by the growth rate of the turnover and the independent variable used was the age of the company, measured by the number of years. The model was tested using the number of employees as a control variable. This paper’s conclusion is in agreement with many other findings from the literature in this subject. The presented results show that the turnover growth rates in the Romanian fast-growing companies tend to drop from one year to another, as the companies grow older.

  9. Interplay between a Wnt-dependent organiser and the Notch segmentation clock regulates posterior development in Periplaneta americana

    Directory of Open Access Journals (Sweden)

    John E. Chesebro

    2012-12-01

    Sequential addition of segments in the posteriorly growing end of the embryo is a developmental mechanism common to many bilaterians. However, posterior growth and patterning in most animals also entails the establishment of a ‘posterior organiser’ that expresses the Caudal and Wnt proteins and has been proposed to be an ancestral feature of animal development. We have studied the functional relationships between the Wnt-driven organiser and the segmentation mechanisms in a basal insect, the cockroach Periplaneta americana. Here, posteriorly-expressed Wnt1 promotes caudal and Delta expression early in development to generate a growth zone from which segments will later bud off. caudal maintains the undifferentiated growth zone by dampening Delta expression, and hence Notch-mediated segmentation occurs just outside the caudal domain. In turn, Delta expression maintains Wnt1, maintaining this posterior gene network until all segments have formed. This feedback between caudal, Wnt and Notch-signalling in regulating growth and segmentation seems conserved in other arthropods, with some aspects found even in vertebrates. Thus our findings not only support an ancestral Wnt posterior organiser, but also impinge on the proposals for a common origin of segmentation in arthropods, annelids and vertebrates.

  10. Rapid detection and subtyping of human influenza A viruses and reassortants by pyrosequencing.

    Directory of Open Access Journals (Sweden)

    Yi-Mo Deng

    Full Text Available BACKGROUND: Given the continuing co-circulation of the 2009 H1N1 pandemic influenza A viruses with seasonal H3N2 viruses, rapid and reliable detection of newly emerging influenza reassortant viruses is important to enhance our influenza surveillance. METHODOLOGY/PRINCIPAL FINDINGS: A novel pyrosequencing assay was developed for the rapid identification and subtyping of potential human influenza A virus reassortants based on all eight gene segments of the virus. Except for HA and NA genes, one universal set of primers was used to amplify and subtype each of the six internal genes. With this method, all eight gene segments of 57 laboratory isolates and 17 original specimens of seasonal H1N1, H3N2 and 2009 H1N1 pandemic viruses were correctly matched with their corresponding subtypes. In addition, this method was shown to be capable of detecting reassortant viruses by correctly identifying the source of all 8 gene segments from three vaccine production reassortant viruses and three H1N2 viruses. CONCLUSIONS/SIGNIFICANCE: In summary, this pyrosequencing assay is a sensitive and specific procedure for screening large numbers of viruses for reassortment events amongst the commonly circulating human influenza A viruses, which is more rapid and cheaper than using conventional sequencing approaches.

  11. Rapid detection and subtyping of human influenza A viruses and reassortants by pyrosequencing.

    Science.gov (United States)

    Deng, Yi-Mo; Caldwell, Natalie; Barr, Ian G

    2011-01-01

    Given the continuing co-circulation of the 2009 H1N1 pandemic influenza A viruses with seasonal H3N2 viruses, rapid and reliable detection of newly emerging influenza reassortant viruses is important to enhance our influenza surveillance. A novel pyrosequencing assay was developed for the rapid identification and subtyping of potential human influenza A virus reassortants based on all eight gene segments of the virus. Except for HA and NA genes, one universal set of primers was used to amplify and subtype each of the six internal genes. With this method, all eight gene segments of 57 laboratory isolates and 17 original specimens of seasonal H1N1, H3N2 and 2009 H1N1 pandemic viruses were correctly matched with their corresponding subtypes. In addition, this method was shown to be capable of detecting reassortant viruses by correctly identifying the source of all 8 gene segments from three vaccine production reassortant viruses and three H1N2 viruses. In summary, this pyrosequencing assay is a sensitive and specific procedure for screening large numbers of viruses for reassortment events amongst the commonly circulating human influenza A viruses, which is more rapid and cheaper than using conventional sequencing approaches.

  12. Automatic ultrasound image enhancement for 2D semi-automatic breast-lesion segmentation

    Science.gov (United States)

    Lu, Kongkuo; Hall, Christopher S.

    2014-03-01

    Breast cancer is the fastest growing cancer, accounting for 29%, of new cases in 2012, and second leading cause of cancer death among women in the United States and worldwide. Ultrasound (US) has been used as an indispensable tool for breast cancer detection/diagnosis and treatment. In computer-aided assistance, lesion segmentation is a preliminary but vital step, but the task is quite challenging in US images, due to imaging artifacts that complicate detection and measurement of the suspect lesions. The lesions usually present with poor boundary features and vary significantly in size, shape, and intensity distribution between cases. Automatic methods are highly application dependent while manual tracing methods are extremely time consuming and have a great deal of intra- and inter- observer variability. Semi-automatic approaches are designed to counterbalance the advantage and drawbacks of the automatic and manual methods. However, considerable user interaction might be necessary to ensure reasonable segmentation for a wide range of lesions. This work proposes an automatic enhancement approach to improve the boundary searching ability of the live wire method to reduce necessary user interaction while keeping the segmentation performance. Based on the results of segmentation of 50 2D breast lesions in US images, less user interaction is required to achieve desired accuracy, i.e. < 80%, when auto-enhancement is applied for live-wire segmentation.

  13. Two novel species of rapidly growing mycobacteria: Mycobacterium lehmannii sp. nov. and Mycobacterium neumannii sp. nov.

    Science.gov (United States)

    Nouioui, Imen; Sangal, Vartul; Carro, Lorena; Teramoto, Kanae; Jando, Marlen; Montero-Calasanz, Maria Del Carmen; Igual, José Mariano; Sutcliffe, Iain; Goodfellow, Michael; Klenk, Hans-Peter

    2017-12-01

    Two rapidly growing mycobacteria with identical 16S rRNA gene sequences were the subject of a polyphasic taxonomic study. The strains formed a well-supported subclade in the mycobacterial 16S rRNA gene tree and were most closely associated with the type strain of Mycobacterium novocastrense. Single and multilocus sequence analyses based on hsp65, rpoB and 16S rRNA gene sequences showed that strains SN 1900 T and SN 1904 T are phylogenetically distinct but share several chemotaxonomic and phenotypic features that are are consistent with their classification in the genus Mycobacterium. The two strains were distinguished by their different fatty acid and mycolic acid profiles, and by a combination of phenotypic features. The digital DNA-DNA hybridization (dDDH) and average nucleotide identity (ANI) values for strains SN 1900 T and SN 1904 T were 61.0 % and 94.7 %, respectively; in turn, the corresponding dDDH and ANI values with M. novocastrense DSM 44203 T were 41.4 % and 42.8 % and 89.3 % and 89.5 %, respectively. These results show that strains SN1900 T and SN 1904 T form new centres of taxonomic variation within the genus Mycobacterium. Consequently, strains SN 1900 T (40 T =CECT 8763 T =DSM 43219 T ) and SN 1904 T (2409 T =CECT 8766 T =DSM 43532 T ) are considered to represent novel species, for which the names Mycobacteriumlehmannii sp. nov. and Mycobacteriumneumannii sp. nov. are proposed. A strain designated as 'Mycobacteriumacapulsensis' was shown to be a bona fide member of the putative novel species, M. lehmannii.

  14. Focused volcanism and growth of a slow spreading segment (Mid-Atlantic Ridge, 35°N)

    Science.gov (United States)

    Rabain, Aline; Cannat, Mathilde; Escartín, Javier; Pouliquen, Gaud; Deplus, Christine; Rommevaux-Jestin, Céline

    2001-02-01

    Using off axis bathymetry, gravity and magnetic data, we studied the formation of a prominent seamount chain across segment OH1 (Mid-Atlantic Ridge, 35°N), and its relation to the past segmentation of the area. We also studied the size and shape of the seamounts to understand the processes leading to their formation. The chain is elongated in the spreading direction, and extends from the present day segment center to ˜6 Ma on both flanks. It coincides with a pronounced low in the residual mantle Bouguer gravity anomaly, suggesting thicker crust and thus more abundant magmatism than in surrounding areas. Magnetic anomalies are well defined over the seamount chain, consistent with formation on or near the axis. The seamounts within the chain are larger on average than those from other areas of the Mid-Atlantic Ridge, reflecting higher magma volumes and fluxes during eruptions. The distribution of seamounts suggests a focused magmatic source, located beneath the eastern side of the ridge axis, at a constant distance (˜45 km) from the Oceanographer transform fault. A V-shaped trend defines the southern end of OH1 and indicates that the segment propagated rapidly southwards, increasing in length from 50 to 90 km. The onset of propagation at ˜6 Ma coincided with the initiation of the volcanic chain, suggesting that magma supply at that time was focused at the end of the segment rather than at its center, as is typical for Mid-Atlantic Ridge segments. We propose that this unusual configuration is a consequence of the cold edge effect of the Oceanographer fracture zone. We also propose that enhanced and focused magmatism beneath the seamount chain may have caused the rapid southward propagation of OH1 over the past ˜6 Ma.

  15. Food (In)Security in Rapidly Urbanising, Low-Income Contexts

    OpenAIRE

    Cecilia Tacoli

    2017-01-01

    Urbanisation in low and middle-income nations presents both opportunities and immense challenges. As urban centres grow rapidly, inadequate housing and the lack of basic infrastructure and services affect a large and growing proportion of their population. There is also a growing body of evidence on urban poverty and its links with environmental hazards. There is, however, limited knowledge of how these challenges affect the ways in which poor urban residents gain access to food and secure he...

  16. Accounting for segment correlations in segmented gamma-ray scans

    International Nuclear Information System (INIS)

    Sheppard, G.A.; Prettyman, T.H.; Piquette, E.C.

    1994-01-01

    In a typical segmented gamma-ray scanner (SGS), the detector's field of view is collimated so that a complete horizontal slice or segment of the desired thickness is visible. Ordinarily, the collimator is not deep enough to exclude gamma rays emitted from sample volumes above and below the segment aligned with the collimator. This can lead to assay biases, particularly for certain radioactive-material distributions. Another consequence of the collimator's low aspect ratio is that segment assays at the top and bottom of the sample are biased low because the detector's field of view is not filled. This effect is ordinarily countered by placing the sample on a low-Z pedestal and scanning one or more segment thicknesses below and above the sample. This takes extra time, however, We have investigated a number of techniques that both account for correlated segments and correct for end effects in SGS assays. Also, we have developed an algorithm that facilitates estimates of assay precision. Six calculation methods have been compared by evaluating the results of thousands of simulated, assays for three types of gamma-ray source distribution and ten masses. We will report on these computational studies and their experimental verification

  17. Organisational Factors of Rapid Growth of Slovenian Dynamic Enterprises

    Directory of Open Access Journals (Sweden)

    Pšeničny Viljem

    2013-01-01

    Full Text Available The authors provide key findings on the internal and external environmental factors of growth that affect the rapid growth of dynamic enterprises in relation to individual key organisational factors or functions. The key organisational relationships in a growing enterprise are upgraded with previous research findings and identified key factors of rapid growth through qualitative and quantitative analysis based on the analysis of 4,511 dynamic Slovenian enterprises exhibiting growth potential. More than 250 descriptive attributes of a sample of firms from 2011 were also used for further qualitative analysis and verification of key growth factors. On the basis of the sample (the study was conducted with 131 Slovenian dynamic enterprises, the authors verify whether these factors are the same as the factors that were studied in previous researches. They also provide empirical findings on rapid growth factors in relation to individual organisational functions: administration - management - implementation (entrepreneur - manager - employees. Through factor analysis they look for the correlation strength between individual variables (attributes that best describe each factor of rapid growth and that relate to the aforementioned organisational functions in dynamic enterprises. The research findings on rapid growth factors offer companies the opportunity to consider these factors during the planning and implementation phases of their business, to choose appropriate instruments for the transition from a small fast growing firm to a professionally managed growing company, to stimulate growth and to choose an appropriate growth strategy and organisational factors in order to remain, or become, dynamic enterprises that can further contribute to the preservation, growth and development of the Slovenian economy

  18. Rapid prototyping framework for robot-assisted training of autistic children

    NARCIS (Netherlands)

    Kim, Mingyu; Barakova, E.I.; Lourens, T.

    2014-01-01

    Research in uptake and actual use of robots in socially assistive tasks is rapidly growing. However, practical applications lack behind due to the enormous effort to create meaningful behaviours. This paper describes a rapid prototyping framework for robot-assisted training of children with Autism

  19. Image segmentation by hierarchial agglomeration of polygons using ecological statistics

    Science.gov (United States)

    Prasad, Lakshman; Swaminarayan, Sriram

    2013-04-23

    A method for rapid hierarchical image segmentation based on perceptually driven contour completion and scene statistics is disclosed. The method begins with an initial fine-scale segmentation of an image, such as obtained by perceptual completion of partial contours into polygonal regions using region-contour correspondences established by Delaunay triangulation of edge pixels as implemented in VISTA. The resulting polygons are analyzed with respect to their size and color/intensity distributions and the structural properties of their boundaries. Statistical estimates of granularity of size, similarity of color, texture, and saliency of intervening boundaries are computed and formulated into logical (Boolean) predicates. The combined satisfiability of these Boolean predicates by a pair of adjacent polygons at a given segmentation level qualifies them for merging into a larger polygon representing a coarser, larger-scale feature of the pixel image and collectively obtains the next level of polygonal segments in a hierarchy of fine-to-coarse segmentations. The iterative application of this process precipitates textured regions as polygons with highly convolved boundaries and helps distinguish them from objects which typically have more regular boundaries. The method yields a multiscale decomposition of an image into constituent features that enjoy a hierarchical relationship with features at finer and coarser scales. This provides a traversable graph structure from which feature content and context in terms of other features can be derived, aiding in automated image understanding tasks. The method disclosed is highly efficient and can be used to decompose and analyze large images.

  20. Object-based change detection in rapid urbanization regions with remotely sensed observations: a case study of Shenzhen, China

    Science.gov (United States)

    He, Lihuang; Dong, Guihua; Wang, Wei-Min; Yang, Lijun; Liang, Hong

    2013-10-01

    China, the most populous country on Earth, has experienced rapid urbanization which is one of the main causes of many environmental and ecological problems. Therefore, the monitoring of rapid urbanization regions and the environment is of critical importance for their sustainable development. In this study, the object-based classification is employed to detect the change of land cover in Shenzhen, which is located in South China and has been urbanized rapidly in recent three decades. First, four Landsat TM images, which were acquired on 1990, 2000 and 2010, respectively, are selected from the image database. Atmospheric corrections are conducted on these images with improved dark-object subtraction technique and surface meteorological observations. Geometric correction is processed with ground control points derived from topographic maps. Second, a region growing multi-resolution segmentation and a soft nearest neighbour classifier are used to finish object-based classification. After analyzing the fraction of difference classes over time series, we conclude that the comparison of derived land cover classes with socio-economic statistics demonstrates the strong positive correlation between built-up classes and urban population as well as gross GDP and GDPs in second and tertiary industries. Two different mechanisms of urbanization, namely new land development and redevelopment, are revealed. Consequently, we found that, the districts of Shenzhen were urbanized through different mechanisms.

  1. Hydrophilic segmented block copolymers based on poly(ethylene oxide) and monodisperse amide segments

    NARCIS (Netherlands)

    Husken, D.; Feijen, Jan; Gaymans, R.J.

    2007-01-01

    Segmented block copolymers based on poly(ethylene oxide) (PEO) flexible segments and monodisperse crystallizable bisester tetra-amide segments were made via a polycondensation reaction. The molecular weight of the PEO segments varied from 600 to 4600 g/mol and a bisester tetra-amide segment (T6T6T)

  2. Spinal segmental dysgenesis

    Directory of Open Access Journals (Sweden)

    N Mahomed

    2009-06-01

    Full Text Available Spinal segmental dysgenesis is a rare congenital spinal abnormality , seen in neonates and infants in which a segment of the spine and spinal cord fails to develop normally . The condition is segmental with normal vertebrae above and below the malformation. This condition is commonly associated with various abnormalities that affect the heart, genitourinary, gastrointestinal tract and skeletal system. We report two cases of spinal segmental dysgenesis and the associated abnormalities.

  3. Delineating slowly and rapidly evolving fractions of the Drosophila genome.

    Science.gov (United States)

    Keith, Jonathan M; Adams, Peter; Stephen, Stuart; Mattick, John S

    2008-05-01

    Evolutionary conservation is an important indicator of function and a major component of bioinformatic methods to identify non-protein-coding genes. We present a new Bayesian method for segmenting pairwise alignments of eukaryotic genomes while simultaneously classifying segments into slowly and rapidly evolving fractions. We also describe an information criterion similar to the Akaike Information Criterion (AIC) for determining the number of classes. Working with pairwise alignments enables detection of differences in conservation patterns among closely related species. We analyzed three whole-genome and three partial-genome pairwise alignments among eight Drosophila species. Three distinct classes of conservation level were detected. Sequences comprising the most slowly evolving component were consistent across a range of species pairs, and constituted approximately 62-66% of the D. melanogaster genome. Almost all (>90%) of the aligned protein-coding sequence is in this fraction, suggesting much of it (comprising the majority of the Drosophila genome, including approximately 56% of non-protein-coding sequences) is functional. The size and content of the most rapidly evolving component was species dependent, and varied from 1.6% to 4.8%. This fraction is also enriched for protein-coding sequence (while containing significant amounts of non-protein-coding sequence), suggesting it is under positive selection. We also classified segments according to conservation and GC content simultaneously. This analysis identified numerous sub-classes of those identified on the basis of conservation alone, but was nevertheless consistent with that classification. Software, data, and results available at www.maths.qut.edu.au/-keithj/. Genomic segments comprising the conservation classes available in BED format.

  4. Automatic Melody Segmentation

    NARCIS (Netherlands)

    Rodríguez López, Marcelo

    2016-01-01

    The work presented in this dissertation investigates music segmentation. In the field of Musicology, segmentation refers to a score analysis technique, whereby notated pieces or passages of these pieces are divided into “units” referred to as sections, periods, phrases, and so on. Segmentation

  5. FogBank: a single cell segmentation across multiple cell lines and image modalities.

    Science.gov (United States)

    Chalfoun, Joe; Majurski, Michael; Dima, Alden; Stuelten, Christina; Peskin, Adele; Brady, Mary

    2014-12-30

    Many cell lines currently used in medical research, such as cancer cells or stem cells, grow in confluent sheets or colonies. The biology of individual cells provide valuable information, thus the separation of touching cells in these microscopy images is critical for counting, identification and measurement of individual cells. Over-segmentation of single cells continues to be a major problem for methods based on morphological watershed due to the high level of noise in microscopy cell images. There is a need for a new segmentation method that is robust over a wide variety of biological images and can accurately separate individual cells even in challenging datasets such as confluent sheets or colonies. We present a new automated segmentation method called FogBank that accurately separates cells when confluent and touching each other. This technique is successfully applied to phase contrast, bright field, fluorescence microscopy and binary images. The method is based on morphological watershed principles with two new features to improve accuracy and minimize over-segmentation. First, FogBank uses histogram binning to quantize pixel intensities which minimizes the image noise that causes over-segmentation. Second, FogBank uses a geodesic distance mask derived from raw images to detect the shapes of individual cells, in contrast to the more linear cell edges that other watershed-like algorithms produce. We evaluated the segmentation accuracy against manually segmented datasets using two metrics. FogBank achieved segmentation accuracy on the order of 0.75 (1 being a perfect match). We compared our method with other available segmentation techniques in term of achieved performance over the reference data sets. FogBank outperformed all related algorithms. The accuracy has also been visually verified on data sets with 14 cell lines across 3 imaging modalities leading to 876 segmentation evaluation images. FogBank produces single cell segmentation from confluent cell

  6. Segmented trapped vortex cavity

    Science.gov (United States)

    Grammel, Jr., Leonard Paul (Inventor); Pennekamp, David Lance (Inventor); Winslow, Jr., Ralph Henry (Inventor)

    2010-01-01

    An annular trapped vortex cavity assembly segment comprising includes a cavity forward wall, a cavity aft wall, and a cavity radially outer wall there between defining a cavity segment therein. A cavity opening extends between the forward and aft walls at a radially inner end of the assembly segment. Radially spaced apart pluralities of air injection first and second holes extend through the forward and aft walls respectively. The segment may include first and second expansion joint features at distal first and second ends respectively of the segment. The segment may include a forward subcomponent including the cavity forward wall attached to an aft subcomponent including the cavity aft wall. The forward and aft subcomponents include forward and aft portions of the cavity radially outer wall respectively. A ring of the segments may be circumferentially disposed about an axis to form an annular segmented vortex cavity assembly.

  7. Plant-based milk alternatives an emerging segment of functional beverages: a review

    OpenAIRE

    Sethi, Swati; Tyagi, S. K.; Anurag, Rahul K.

    2016-01-01

    Plant-based or non-dairy milk alternative is the fast growing segment in newer food product development category of functional and specialty beverage across the globe. Nowadays, cow milk allergy, lactose intolerance, calorie concern and prevalence of hypercholesterolemia, more preference to vegan diets has influenced consumers towards choosing cow milk alternatives. Plant-based milk alternatives are a rising trend, which can serve as an inexpensive alternate to poor economic group of developi...

  8. Segmental vitiligo with segmental morphea: An autoimmune link?

    Directory of Open Access Journals (Sweden)

    Pravesh Yadav

    2014-01-01

    Full Text Available An 18-year old girl with segmental vitiligo involving the left side of the trunk and left upper limb with segmental morphea involving the right side of trunk and right upper limb without any deeper involvement is illustrated. There was no history of preceding drug intake, vaccination, trauma, radiation therapy, infection, or hormonal therapy. Family history of stable vitiligo in her brother and a history of type II diabetes mellitus in the father were elicited. Screening for autoimmune diseases and antithyroid antibody was negative. An autoimmune link explaining the co-occurrence has been proposed. Cutaneous mosiacism could explain the presence of both the pathologies in a segmental distribution.

  9. Market Segmentation in Business Technology Base: The Case of Segmentation of Sparkling

    Directory of Open Access Journals (Sweden)

    Valéria Riscarolli

    2014-08-01

    Full Text Available A common market segmentation premise for products and services rules consumer behavior as the segmentation center piece. Would this be the logic for segmentation used by small technology based companies? In this article we target at determining the principles of market segmentation used by a vitiwinery company, as research object. This company is recognized by its products excellence, either in domestic as well as in the foreign market, among 13 distinct countries. The research method used is a case study, through information from the company’s CEOs and crossed by primary information from observation and formal registries and documents of the company. In this research we look at sparkling wines market segmentation. Main results indicate that the winery studied considers only technological elements as the basis to build a market segment. One may conclude that a market segmentation for this company is based upon technological dominion of sparkling wines production, aligned with a premium-price policy. In the company, directorship believes that as sparkling wines market is still incipient in the country, sparkling wine market segments will form and consolidate after the evolution of consumers tasting preferences, depending on technologies that boost sparkling wines quality. 

  10. Far East LPG sales will grow faster than in West

    International Nuclear Information System (INIS)

    Anon.

    1996-01-01

    LPG sales through 2010 in regions east of the Suez Canal (East of Suez) will grow at more than twice those in regions west of the canal. East-of-Suez sales will grow at more than 4.0%/year, compared to slightly less than 2.0%/year growth in sales West of Suez. East-of-Suez sales will reach 92 million tons/year (tpy) by 2010, accounting for 39% of the worldwide total. This share was 31% in1995 and only 27% in 1990. LPG sales worldwide will reach 192 million tons in 2000 and 243 million tpy by 2010. In 1995, they were 163 million tons. These are some of the major conclusions of a recent study by Frank R. Spadine, Christine Kozar, and Rudy Clark of New York City-based consultant Poten and Partners Inc. Details of the study are in the fall report ''World Trade in LPG 1990--2010''. This paper discusses demand segments, seaborne balance, Western sources, largest trading region, North American supplies, and other supplies

  11. GPU-based relative fuzzy connectedness image segmentation

    International Nuclear Information System (INIS)

    Zhuge Ying; Ciesielski, Krzysztof C.; Udupa, Jayaram K.; Miller, Robert W.

    2013-01-01

    Purpose:Recently, clinical radiological research and practice are becoming increasingly quantitative. Further, images continue to increase in size and volume. For quantitative radiology to become practical, it is crucial that image segmentation algorithms and their implementations are rapid and yield practical run time on very large data sets. The purpose of this paper is to present a parallel version of an algorithm that belongs to the family of fuzzy connectedness (FC) algorithms, to achieve an interactive speed for segmenting large medical image data sets. Methods: The most common FC segmentations, optimizing an ℓ ∞ -based energy, are known as relative fuzzy connectedness (RFC) and iterative relative fuzzy connectedness (IRFC). Both RFC and IRFC objects (of which IRFC contains RFC) can be found via linear time algorithms, linear with respect to the image size. The new algorithm, P-ORFC (for parallel optimal RFC), which is implemented by using NVIDIA’s Compute Unified Device Architecture (CUDA) platform, considerably improves the computational speed of the above mentioned CPU based IRFC algorithm. Results: Experiments based on four data sets of small, medium, large, and super data size, achieved speedup factors of 32.8×, 22.9×, 20.9×, and 17.5×, correspondingly, on the NVIDIA Tesla C1060 platform. Although the output of P-ORFC need not precisely match that of IRFC output, it is very close to it and, as the authors prove, always lies between the RFC and IRFC objects. Conclusions: A parallel version of a top-of-the-line algorithm in the family of FC has been developed on the NVIDIA GPUs. An interactive speed of segmentation has been achieved, even for the largest medical image data set. Such GPU implementations may play a crucial role in automatic anatomy recognition in clinical radiology.

  12. GPU-based relative fuzzy connectedness image segmentation

    Energy Technology Data Exchange (ETDEWEB)

    Zhuge Ying; Ciesielski, Krzysztof C.; Udupa, Jayaram K.; Miller, Robert W. [Radiation Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892 (United States); Department of Mathematics, West Virginia University, Morgantown, West Virginia 26506 (United States) and Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania 19104 (United States); Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania 19104 (United States); Radiation Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892 (United States)

    2013-01-15

    Purpose:Recently, clinical radiological research and practice are becoming increasingly quantitative. Further, images continue to increase in size and volume. For quantitative radiology to become practical, it is crucial that image segmentation algorithms and their implementations are rapid and yield practical run time on very large data sets. The purpose of this paper is to present a parallel version of an algorithm that belongs to the family of fuzzy connectedness (FC) algorithms, to achieve an interactive speed for segmenting large medical image data sets. Methods: The most common FC segmentations, optimizing an Script-Small-L {sub {infinity}}-based energy, are known as relative fuzzy connectedness (RFC) and iterative relative fuzzy connectedness (IRFC). Both RFC and IRFC objects (of which IRFC contains RFC) can be found via linear time algorithms, linear with respect to the image size. The new algorithm, P-ORFC (for parallel optimal RFC), which is implemented by using NVIDIA's Compute Unified Device Architecture (CUDA) platform, considerably improves the computational speed of the above mentioned CPU based IRFC algorithm. Results: Experiments based on four data sets of small, medium, large, and super data size, achieved speedup factors of 32.8 Multiplication-Sign , 22.9 Multiplication-Sign , 20.9 Multiplication-Sign , and 17.5 Multiplication-Sign , correspondingly, on the NVIDIA Tesla C1060 platform. Although the output of P-ORFC need not precisely match that of IRFC output, it is very close to it and, as the authors prove, always lies between the RFC and IRFC objects. Conclusions: A parallel version of a top-of-the-line algorithm in the family of FC has been developed on the NVIDIA GPUs. An interactive speed of segmentation has been achieved, even for the largest medical image data set. Such GPU implementations may play a crucial role in automatic anatomy recognition in clinical radiology.

  13. GPU-based relative fuzzy connectedness image segmentation.

    Science.gov (United States)

    Zhuge, Ying; Ciesielski, Krzysztof C; Udupa, Jayaram K; Miller, Robert W

    2013-01-01

    Recently, clinical radiological research and practice are becoming increasingly quantitative. Further, images continue to increase in size and volume. For quantitative radiology to become practical, it is crucial that image segmentation algorithms and their implementations are rapid and yield practical run time on very large data sets. The purpose of this paper is to present a parallel version of an algorithm that belongs to the family of fuzzy connectedness (FC) algorithms, to achieve an interactive speed for segmenting large medical image data sets. The most common FC segmentations, optimizing an [script-l](∞)-based energy, are known as relative fuzzy connectedness (RFC) and iterative relative fuzzy connectedness (IRFC). Both RFC and IRFC objects (of which IRFC contains RFC) can be found via linear time algorithms, linear with respect to the image size. The new algorithm, P-ORFC (for parallel optimal RFC), which is implemented by using NVIDIA's Compute Unified Device Architecture (CUDA) platform, considerably improves the computational speed of the above mentioned CPU based IRFC algorithm. Experiments based on four data sets of small, medium, large, and super data size, achieved speedup factors of 32.8×, 22.9×, 20.9×, and 17.5×, correspondingly, on the NVIDIA Tesla C1060 platform. Although the output of P-ORFC need not precisely match that of IRFC output, it is very close to it and, as the authors prove, always lies between the RFC and IRFC objects. A parallel version of a top-of-the-line algorithm in the family of FC has been developed on the NVIDIA GPUs. An interactive speed of segmentation has been achieved, even for the largest medical image data set. Such GPU implementations may play a crucial role in automatic anatomy recognition in clinical radiology.

  14. GPU-based relative fuzzy connectedness image segmentation

    Science.gov (United States)

    Zhuge, Ying; Ciesielski, Krzysztof C.; Udupa, Jayaram K.; Miller, Robert W.

    2013-01-01

    Purpose: Recently, clinical radiological research and practice are becoming increasingly quantitative. Further, images continue to increase in size and volume. For quantitative radiology to become practical, it is crucial that image segmentation algorithms and their implementations are rapid and yield practical run time on very large data sets. The purpose of this paper is to present a parallel version of an algorithm that belongs to the family of fuzzy connectedness (FC) algorithms, to achieve an interactive speed for segmenting large medical image data sets. Methods: The most common FC segmentations, optimizing an ℓ∞-based energy, are known as relative fuzzy connectedness (RFC) and iterative relative fuzzy connectedness (IRFC). Both RFC and IRFC objects (of which IRFC contains RFC) can be found via linear time algorithms, linear with respect to the image size. The new algorithm, P-ORFC (for parallel optimal RFC), which is implemented by using NVIDIA’s Compute Unified Device Architecture (CUDA) platform, considerably improves the computational speed of the above mentioned CPU based IRFC algorithm. Results: Experiments based on four data sets of small, medium, large, and super data size, achieved speedup factors of 32.8×, 22.9×, 20.9×, and 17.5×, correspondingly, on the NVIDIA Tesla C1060 platform. Although the output of P-ORFC need not precisely match that of IRFC output, it is very close to it and, as the authors prove, always lies between the RFC and IRFC objects. Conclusions: A parallel version of a top-of-the-line algorithm in the family of FC has been developed on the NVIDIA GPUs. An interactive speed of segmentation has been achieved, even for the largest medical image data set. Such GPU implementations may play a crucial role in automatic anatomy recognition in clinical radiology. PMID:23298094

  15. A Decision-Tree-Based Algorithm for Speech/Music Classification and Segmentation

    Directory of Open Access Journals (Sweden)

    Lavner Yizhar

    2009-01-01

    Full Text Available We present an efficient algorithm for segmentation of audio signals into speech or music. The central motivation to our study is consumer audio applications, where various real-time enhancements are often applied. The algorithm consists of a learning phase and a classification phase. In the learning phase, predefined training data is used for computing various time-domain and frequency-domain features, for speech and music signals separately, and estimating the optimal speech/music thresholds, based on the probability density functions of the features. An automatic procedure is employed to select the best features for separation. In the test phase, initial classification is performed for each segment of the audio signal, using a three-stage sieve-like approach, applying both Bayesian and rule-based methods. To avoid erroneous rapid alternations in the classification, a smoothing technique is applied, averaging the decision on each segment with past segment decisions. Extensive evaluation of the algorithm, on a database of more than 12 hours of speech and more than 22 hours of music showed correct identification rates of 99.4% and 97.8%, respectively, and quick adjustment to alternating speech/music sections. In addition to its accuracy and robustness, the algorithm can be easily adapted to different audio types, and is suitable for real-time operation.

  16. Consistent interactive segmentation of pulmonary ground glass nodules identified in CT studies

    Science.gov (United States)

    Zhang, Li; Fang, Ming; Naidich, David P.; Novak, Carol L.

    2004-05-01

    Ground glass nodules (GGNs) have proved especially problematic in lung cancer diagnosis, as despite frequently being malignant they characteristically have extremely slow rates of growth. This problem is further magnified by the small size of many of these lesions now being routinely detected following the introduction of multislice CT scanners capable of acquiring contiguous high resolution 1 to 1.25 mm sections throughout the thorax in a single breathhold period. Although segmentation of solid nodules can be used clinically to determine volume doubling times quantitatively, reliable methods for segmentation of pure ground glass nodules have yet to be introduced. Our purpose is to evaluate a newly developed computer-based segmentation method for rapid and reproducible measurements of pure ground glass nodules. 23 pure or mixed ground glass nodules were identified in a total of 8 patients by a radiologist and subsequently segmented by our computer-based method using Markov random field and shape analysis. The computer-based segmentation was initialized by a click point. Methodological consistency was assessed using the overlap ratio between 3 segmentations initialized by 3 different click points for each nodule. The 95% confidence interval on the mean of the overlap ratios proved to be [0.984, 0.998]. The computer-based method failed on two nodules that were difficult to segment even manually either due to especially low contrast or markedly irregular margins. While achieving consistent manual segmentation of ground glass nodules has proven problematic most often due to indistinct boundaries and interobserver variability, our proposed method introduces a powerful new tool for obtaining reproducible quantitative measurements of these lesions. It is our intention to further document the value of this approach with a still larger set of ground glass nodules.

  17. NPP/NPOESS Tools for Rapid Algorithm Updates

    Science.gov (United States)

    Route, G.; Grant, K. D.; Hughes, R.

    2010-12-01

    The National Oceanic and Atmospheric Administration (NOAA), Department of Defense (DoD), and National Aeronautics and Space Administration (NASA) are jointly acquiring the next-generation weather and environmental satellite system; the National Polar-orbiting Operational Environmental Satellite System (NPOESS). NPOESS replaces the current Polar-orbiting Operational Environmental Satellites (POES) managed by NOAA and the Defense Meteorological Satellite Program (DMSP) managed by the DoD. The NPOESS Preparatory Project (NPP) and NPOESS satellites will carry a suite of sensors that collect meteorological, oceanographic, climatological, and solar-geophysical observations of the earth, atmosphere, and space. The ground data processing segment for NPOESS is the Interface Data Processing Segment (IDPS), developed by Raytheon Intelligence and Information Systems. The IDPS processes both NPP and NPOESS satellite data to provide environmental data products to NOAA and DoD processing centers operated by the United States government. The Northrop Grumman Aerospace Systems (NGAS) Algorithms and Data Products (A&DP) organization is responsible for the algorithms that produce the Environmental Data Records (EDRs), including their quality aspects. As the Calibration and Validation (Cal/Val) activities move forward following both the NPP launch and subsequent NPOESS launches, rapid algorithm updates may be required. Raytheon and Northrop Grumman have developed tools and processes to enable changes to be evaluated, tested, and moved into the operational baseline in a rapid and efficient manner. This presentation will provide an overview of the tools available to the Cal/Val teams to ensure rapid and accurate assessment of algorithm changes, along with the processes in place to ensure baseline integrity.

  18. Two-stage atlas subset selection in multi-atlas based image segmentation

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Tingting, E-mail: tingtingzhao@mednet.ucla.edu; Ruan, Dan, E-mail: druan@mednet.ucla.edu [The Department of Radiation Oncology, University of California, Los Angeles, California 90095 (United States)

    2015-06-15

    Purpose: Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. Methods: An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stage atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. Results: The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. Conclusions: The authors

  19. Two-stage atlas subset selection in multi-atlas based image segmentation.

    Science.gov (United States)

    Zhao, Tingting; Ruan, Dan

    2015-06-01

    Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stage atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. The authors have developed a novel two-stage atlas

  20. Two-stage atlas subset selection in multi-atlas based image segmentation

    International Nuclear Information System (INIS)

    Zhao, Tingting; Ruan, Dan

    2015-01-01

    Purpose: Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. Methods: An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stage atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. Results: The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. Conclusions: The authors

  1. Fluence map segmentation

    International Nuclear Information System (INIS)

    Rosenwald, J.-C.

    2008-01-01

    The lecture addressed the following topics: 'Interpreting' the fluence map; The sequencer; Reasons for difference between desired and actual fluence map; Principle of 'Step and Shoot' segmentation; Large number of solutions for given fluence map; Optimizing 'step and shoot' segmentation; The interdigitation constraint; Main algorithms; Conclusions on segmentation algorithms (static mode); Optimizing intensity levels and monitor units; Sliding window sequencing; Synchronization to avoid the tongue-and-groove effect; Accounting for physical characteristics of MLC; Importance of corrections for leaf transmission and offset; Accounting for MLC mechanical constraints; The 'complexity' factor; Incorporating the sequencing into optimization algorithm; Data transfer to the treatment machine; Interface between R and V and accelerator; and Conclusions on fluence map segmentation (Segmentation is part of the overall inverse planning procedure; 'Step and Shoot' and 'Dynamic' options are available for most TPS (depending on accelerator model; The segmentation phase tends to come into the optimization loop; The physical characteristics of the MLC have a large influence on final dose distribution; The IMRT plans (MU and relative dose distribution) must be carefully validated). (P.A.)

  2. Strategic market segmentation

    Directory of Open Access Journals (Sweden)

    Maričić Branko R.

    2015-01-01

    Full Text Available Strategic planning of marketing activities is the basis of business success in modern business environment. Customers are not homogenous in their preferences and expectations. Formulating an adequate marketing strategy, focused on realization of company's strategic objectives, requires segmented approach to the market that appreciates differences in expectations and preferences of customers. One of significant activities in strategic planning of marketing activities is market segmentation. Strategic planning imposes a need to plan marketing activities according to strategically important segments on the long term basis. At the same time, there is a need to revise and adapt marketing activities on the short term basis. There are number of criteria based on which market segmentation is performed. The paper will consider effectiveness and efficiency of different market segmentation criteria based on empirical research of customer expectations and preferences. The analysis will include traditional criteria and criteria based on behavioral model. The research implications will be analyzed from the perspective of selection of the most adequate market segmentation criteria in strategic planning of marketing activities.

  3. Impact of image segmentation on high-content screening data quality for SK-BR-3 cells

    Directory of Open Access Journals (Sweden)

    Li Yizheng

    2007-09-01

    Full Text Available Abstract Background High content screening (HCS is a powerful method for the exploration of cellular signalling and morphology that is rapidly being adopted in cancer research. HCS uses automated microscopy to collect images of cultured cells. The images are subjected to segmentation algorithms to identify cellular structures and quantitate their morphology, for hundreds to millions of individual cells. However, image analysis may be imperfect, especially for "HCS-unfriendly" cell lines whose morphology is not well handled by current image segmentation algorithms. We asked if segmentation errors were common for a clinically relevant cell line, if such errors had measurable effects on the data, and if HCS data could be improved by automated identification of well-segmented cells. Results Cases of poor cell body segmentation occurred frequently for the SK-BR-3 cell line. We trained classifiers to identify SK-BR-3 cells that were well segmented. On an independent test set created by human review of cell images, our optimal support-vector machine classifier identified well-segmented cells with 81% accuracy. The dose responses of morphological features were measurably different in well- and poorly-segmented populations. Elimination of the poorly-segmented cell population increased the purity of DNA content distributions, while appropriately retaining biological heterogeneity, and simultaneously increasing our ability to resolve specific morphological changes in perturbed cells. Conclusion Image segmentation has a measurable impact on HCS data. The application of a multivariate shape-based filter to identify well-segmented cells improved HCS data quality for an HCS-unfriendly cell line, and could be a valuable post-processing step for some HCS datasets.

  4. Why segmentation matters: Experience-driven segmentation errors impair "morpheme" learning.

    Science.gov (United States)

    Finn, Amy S; Hudson Kam, Carla L

    2015-09-01

    We ask whether an adult learner's knowledge of their native language impedes statistical learning in a new language beyond just word segmentation (as previously shown). In particular, we examine the impact of native-language word-form phonotactics on learners' ability to segment words into their component morphemes and learn phonologically triggered variation of morphemes. We find that learning is impaired when words and component morphemes are structured to conflict with a learner's native-language phonotactic system, but not when native-language phonotactics do not conflict with morpheme boundaries in the artificial language. A learner's native-language knowledge can therefore have a cascading impact affecting word segmentation and the morphological variation that relies upon proper segmentation. These results show that getting word segmentation right early in learning is deeply important for learning other aspects of language, even those (morphology) that are known to pose a great difficulty for adult language learners. (c) 2015 APA, all rights reserved).

  5. Salted and preserved duck eggs: a consumer market segmentation analysis.

    Science.gov (United States)

    Arthur, Jennifer; Wiseman, Kelleen; Cheng, K M

    2015-08-01

    The combination of increasing ethnic diversity in North America and growing consumer support for local food products may present opportunities for local producers and processors in the ethnic foods product category. Our study examined the ethnic Chinese (pop. 402,000) market for salted and preserved duck eggs in Vancouver, British Columbia (BC), Canada. The objective of the study was to develop a segmentation model using survey data to categorize consumer groups based on their attitudes and the importance they placed on product attributes. We further used post-segmentation acculturation score, demographics and buyer behaviors to define these groups. Data were gathered via a survey of randomly selected Vancouver households with Chinese surnames (n = 410), targeting the adult responsible for grocery shopping. Results from principal component analysis and a 2-step cluster analysis suggest the existence of 4 market segments, described as Enthusiasts, Potentialists, Pragmatists, Health Skeptics (salted duck eggs), and Neutralists (preserved duck eggs). Kruskal Wallis tests and post hoc Mann-Whitney tests found significant differences between segments in terms of attitudes and the importance placed on product characteristics. Health Skeptics, preserved egg Potentialists, and Pragmatists of both egg products were significantly biased against Chinese imports compared to others. Except for Enthusiasts, segments disagreed that eggs are 'Healthy Products'. Preserved egg Enthusiasts had a significantly lower acculturation score (AS) compared to all others, while salted egg Enthusiasts had a lower AS compared to Health Skeptics. All segments rated "produced in BC, not mainland China" products in the "neutral to very likely" range for increasing their satisfaction with the eggs. Results also indicate that buyers of each egg type are willing to pay an average premium of at least 10% more for BC produced products versus imports, with all other characteristics equal. Overall

  6. Consumer segmentation based on food-related lifestyles and analysis of rabbit meat consumption

    Directory of Open Access Journals (Sweden)

    J. Buitrago-Vera

    2016-09-01

    Full Text Available Market segmentation divides the market into small groups of consumers who share similar characteristics. As all consumers within the same group have a common profile, marketing strategies can be adapted to target a specific type of consumer. Owing to the rapid changes in today’s society, consumer lifestyle has become the ideal criterion for market segmentation. In this study, we employed the food-related lifestyle model, which scholars have shown to be suitable and valid in several countries. Using data from a survey (with 3.53% error, we segmented the Spanish food market based on consumers’ food-related lifestyles. For each segment, we identified the consumer profile and analysed consumers’ consumption of rabbit meat. Factor analysis and cluster analysis yielded 4 segments: (i ‘Unconcerned’ (36.8% of the sample mainly consists of male consumers. Consumers in this segment value neither the freshness nor the price/quality ratio of their food items and consume rabbit meat rarely (39.4% or sporadically (29.3%. (ii ‘Cooks’ (18.4% predominantly consists of middle-aged women. Consumers in this segment are highly demanding and critical of the quality of food products. They like cooking and are regular consumers of rabbit meat (40.6%. (iii ‘Out-of-home consumers and convenience shoppers’ (28.6% mostly consists of consumers aged between 25 and 34 y old and contains a large proportion of upper-class consumers. Consumers in this segment prefer to eat out and consume convenience products. This segment has the second highest percentage of regular consumers of rabbit meat (36.9%. The segment also has the second highest percentage of consumers who rarely or never eat rabbit meat (43.9%. (iv ‘Rational purchaser with little interest in cooking’ (16.2% has the highest proportion of consumers aged 55 to 74 y old. Consumers in this segment have the least interest in cooking, the most interest in the purchasing process, and the lowest

  7. Realization of Chinese word segmentation based on deep learning method

    Science.gov (United States)

    Wang, Xuefei; Wang, Mingjiang; Zhang, Qiquan

    2017-08-01

    In recent years, with the rapid development of deep learning, it has been widely used in the field of natural language processing. In this paper, I use the method of deep learning to achieve Chinese word segmentation, with large-scale corpus, eliminating the need to construct additional manual characteristics. In the process of Chinese word segmentation, the first step is to deal with the corpus, use word2vec to get word embedding of the corpus, each character is 50. After the word is embedded, the word embedding feature is fed to the bidirectional LSTM, add a linear layer to the hidden layer of the output, and then add a CRF to get the model implemented in this paper. Experimental results show that the method used in the 2014 People's Daily corpus to achieve a satisfactory accuracy.

  8. Do teachers and students get the Ed-Tech products they need: The challenges of Ed-Tech procurement in a rapidly growing market

    Directory of Open Access Journals (Sweden)

    Jennifer Morrison

    2015-03-01

    Full Text Available Ed-tech courseware products to support teaching and learning are being developed and made available for acquisition by school districts at a rapid rate. In this growing market, developers and providers face challenges with making their products visible to customers, while school district stakeholders must grapple with “discovering” which products of the many available best address their instructional needs. The present study presents the experiences with and perceptions about the procurement process from 47 superintendents representing diverse school districts in the U. S. Results indicate that, while improvements are desired in many aspects of the procurement process, the superintendents, overall, believe that, once desired products are identified, they are generally able to acquire them. Difficulties lie in tighter budgets, discovering products that are potentially the best choices, and evaluating the effectiveness of the products selected as options. These findings are presented and interpreted in relation to five major “Action Points” in the procurement process, and also with regard to implications for evaluating how educational technology impacts K-12 instruction.

  9. Myofibroblastoma: An Unusual Rapidly Growing Benign Tumour in a Male Breast

    International Nuclear Information System (INIS)

    Rafique, A.; Arshad, A.

    2013-01-01

    Myofibroblastoma is an unusual benign tumour of the breast predominantly seen in men in their sixth to seventh decade. The gross appearance is that of a well circumscribed nodule, characteristically small, seldom exceeding 3 cm. We present a case of an unusually large myofibroblastoma, which mimicked a malignant breast tumour. A 40 years old male, known case of tetralogy of Fallot, was operated in infancy in abroad, presented with a rapid enlargement of right breast over 5 - 6 weeks. Examination revealed a firm 10 cm hemispherical lump occupying the whole of the right breast with normal overlying skin. Since core biopsy was inconclusive, a subcutaneous mastectomy was performed to remove the tumour, which weighed 500 gms. Histopathology and immunocytochemistry revealed a mixed classical and collagenised type of myofibroblastoma. The patient is well with no evidence of recurrence. (author)

  10. Czochralski method of growing single crystals. State-of-art

    International Nuclear Information System (INIS)

    Bukowski, A.; Zabierowski, P.

    1999-01-01

    Modern Czochralski method of single crystal growing has been described. The example of Czochralski process is given. The advantages that caused the rapid progress of the method have been presented. The method limitations that motivated the further research and new solutions are also presented. As the example two different ways of the technique development has been described: silicon single crystals growth in the magnetic field; continuous liquid feed of silicon crystals growth. (author)

  11. Combining multiple FDG-PET radiotherapy target segmentation methods to reduce the effect of variable performance of individual segmentation methods

    Energy Technology Data Exchange (ETDEWEB)

    McGurk, Ross J. [Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705 (United States); Bowsher, James; Das, Shiva K. [Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina 27705 (United States); Lee, John A [Molecular Imaging and Experimental Radiotherapy Unit, Universite Catholique de Louvain, 1200 Brussels (Belgium)

    2013-04-15

    Purpose: Many approaches have been proposed to segment high uptake objects in 18F-fluoro-deoxy-glucose positron emission tomography images but none provides consistent performance across the large variety of imaging situations. This study investigates the use of two methods of combining individual segmentation methods to reduce the impact of inconsistent performance of the individual methods: simple majority voting and probabilistic estimation. Methods: The National Electrical Manufacturers Association image quality phantom containing five glass spheres with diameters 13-37 mm and two irregularly shaped volumes (16 and 32 cc) formed by deforming high-density polyethylene bottles in a hot water bath were filled with 18-fluoro-deoxyglucose and iodine contrast agent. Repeated 5-min positron emission tomography (PET) images were acquired at 4:1 and 8:1 object-to-background contrasts for spherical objects and 4.5:1 and 9:1 for irregular objects. Five individual methods were used to segment each object: 40% thresholding, adaptive thresholding, k-means clustering, seeded region-growing, and a gradient based method. Volumes were combined using a majority vote (MJV) or Simultaneous Truth And Performance Level Estimate (STAPLE) method. Accuracy of segmentations relative to CT ground truth volumes were assessed using the Dice similarity coefficient (DSC) and the symmetric mean absolute surface distances (SMASDs). Results: MJV had median DSC values of 0.886 and 0.875; and SMASD of 0.52 and 0.71 mm for spheres and irregular shapes, respectively. STAPLE provided similar results with median DSC of 0.886 and 0.871; and median SMASD of 0.50 and 0.72 mm for spheres and irregular shapes, respectively. STAPLE had significantly higher DSC and lower SMASD values than MJV for spheres (DSC, p < 0.0001; SMASD, p= 0.0101) but MJV had significantly higher DSC and lower SMASD values compared to STAPLE for irregular shapes (DSC, p < 0.0001; SMASD, p= 0.0027). DSC was not significantly

  12. A new segmentation strategy for processing magnetic anomaly detection data of shallow depth ferromagnetic pipeline

    Science.gov (United States)

    Feng, Shuo; Liu, Dejun; Cheng, Xing; Fang, Huafeng; Li, Caifang

    2017-04-01

    Magnetic anomalies produced by underground ferromagnetic pipelines because of the polarization of earth's magnetic field are used to obtain the information on the location, buried depth and other parameters of pipelines. In order to achieve a fast inversion and interpretation of measured data, it is necessary to develop a fast and stable forward method. Magnetic dipole reconstruction (MDR), as a kind of integration numerical method, is well suited for simulating a thin pipeline anomaly. In MDR the pipeline model must be cut into small magnetic dipoles through different segmentation methods. The segmentation method has an impact on the stability and speed of forward calculation. Rapid and accurate simulation of deep-buried pipelines has been achieved by exciting segmentation method. However, in practical measurement, the depth of underground pipe is uncertain. When it comes to the shallow-buried pipeline, the present segmentation may generate significant errors. This paper aims at solving this problem in three stages. First, the cause of inaccuracy is analyzed by simulation experiment. Secondly, new variable interval section segmentation is proposed based on the existing segmentation. It can help MDR method to obtain simulation results in a fast way under the premise of ensuring the accuracy of different depth models. Finally, the measured data is inversed based on new segmentation method. The result proves that the inversion based on the new segmentation can achieve fast and accurate inversion of depth parameters of underground pipes without being limited by pipeline depth.

  13. Segmentation Based Classification of 3D Urban Point Clouds: A Super-Voxel Based Approach with Evaluation

    Directory of Open Access Journals (Sweden)

    Laurent Trassoudaine

    2013-03-01

    Full Text Available Segmentation and classification of urban range data into different object classes have several challenges due to certain properties of the data, such as density variation, inconsistencies due to missing data and the large data size that require heavy computation and large memory. A method to classify urban scenes based on a super-voxel segmentation of sparse 3D data obtained from LiDAR sensors is presented. The 3D point cloud is first segmented into voxels, which are then characterized by several attributes transforming them into super-voxels. These are joined together by using a link-chain method rather than the usual region growing algorithm to create objects. These objects are then classified using geometrical models and local descriptors. In order to evaluate the results, a new metric that combines both segmentation and classification results simultaneously is presented. The effects of voxel size and incorporation of RGB color and laser reflectance intensity on the classification results are also discussed. The method is evaluated on standard data sets using different metrics to demonstrate its efficacy.

  14. User Interaction in Semi-Automatic Segmentation of Organs at Risk: a Case Study in Radiotherapy.

    Science.gov (United States)

    Ramkumar, Anjana; Dolz, Jose; Kirisli, Hortense A; Adebahr, Sonja; Schimek-Jasch, Tanja; Nestle, Ursula; Massoptier, Laurent; Varga, Edit; Stappers, Pieter Jan; Niessen, Wiro J; Song, Yu

    2016-04-01

    Accurate segmentation of organs at risk is an important step in radiotherapy planning. Manual segmentation being a tedious procedure and prone to inter- and intra-observer variability, there is a growing interest in automated segmentation methods. However, automatic methods frequently fail to provide satisfactory result, and post-processing corrections are often needed. Semi-automatic segmentation methods are designed to overcome these problems by combining physicians' expertise and computers' potential. This study evaluates two semi-automatic segmentation methods with different types of user interactions, named the "strokes" and the "contour", to provide insights into the role and impact of human-computer interaction. Two physicians participated in the experiment. In total, 42 case studies were carried out on five different types of organs at risk. For each case study, both the human-computer interaction process and quality of the segmentation results were measured subjectively and objectively. Furthermore, different measures of the process and the results were correlated. A total of 36 quantifiable and ten non-quantifiable correlations were identified for each type of interaction. Among those pairs of measures, 20 of the contour method and 22 of the strokes method were strongly or moderately correlated, either directly or inversely. Based on those correlated measures, it is concluded that: (1) in the design of semi-automatic segmentation methods, user interactions need to be less cognitively challenging; (2) based on the observed workflows and preferences of physicians, there is a need for flexibility in the interface design; (3) the correlated measures provide insights that can be used in improving user interaction design.

  15. Automated Segmentation and Classification of Coral using Fluid Lensing from Unmanned Airborne Platforms

    Science.gov (United States)

    Instrella, Ron; Chirayath, Ved

    2016-01-01

    In recent years, there has been a growing interest among biologists in monitoring the short and long term health of the world's coral reefs. The environmental impact of climate change poses a growing threat to these biologically diverse and fragile ecosystems, prompting scientists to use remote sensing platforms and computer vision algorithms to analyze shallow marine systems. In this study, we present a novel method for performing coral segmentation and classification from aerial data collected from small unmanned aerial vehicles (sUAV). Our method uses Fluid Lensing algorithms to remove and exploit strong optical distortions created along the air-fluid boundary to produce cm-scale resolution imagery of the ocean floor at depths up to 5 meters. A 3D model of the reef is reconstructed using structure from motion (SFM) algorithms, and the associated depth information is combined with multidimensional maximum a posteriori (MAP) estimation to separate organic from inorganic material and classify coral morphologies in the Fluid-Lensed transects. In this study, MAP estimation is performed using a set of manually classified 100 x 100 pixel training images to determine the most probable coral classification within an interrogated region of interest. Aerial footage of a coral reef was captured off the coast of American Samoa and used to test our proposed method. 90 x 20 meter transects of the Samoan coastline undergo automated classification and are manually segmented by a marine biologist for comparison, leading to success rates as high as 85%. This method has broad applications for coastal remote sensing, and will provide marine biologists access to large swaths of high resolution, segmented coral imagery.

  16. The challenges of reporting and using technology in television: an analysis of the segment Conecte from Jornal da Globo

    Directory of Open Access Journals (Sweden)

    Paula Regina Puhl

    2013-06-01

    Full Text Available The article discusses the appropriation of television, with a focuson telejournalism, of new technologies based on digital convergence concepts,transmedia narratives, cross media and research data on the use and profile ofusers of TV and the Internet in Brazil. We decided to analyze the observationof six editions of the segment Conecte from Jornal da Globo. The observationshows that even with the growing number of people with access to the Internetand digital devices, a consolidated television network as Globo the segment doesnot yet offer tools of distribution and participation to its users.

  17. Northern Virginia wineries: understanding visitor motivations for market segmentation

    Science.gov (United States)

    Cammeral Geide; Laurie Harmon; Robert Baker

    2009-01-01

    The wine industry is a rapidly growing sector of Virginia's economy, yet little research has been done on this topic. The purpose of this study was to obtain a better understanding of northern Virginia winery visitors' motivations to help winery operators better focus their marketing efforts. This exploratory research project collected basic information about...

  18. A hybrid segmentation method for partitioning the liver based on 4D DCE-MR images

    Science.gov (United States)

    Zhang, Tian; Wu, Zhiyi; Runge, Jurgen H.; Lavini, Cristina; Stoker, Jaap; van Gulik, Thomas; Cieslak, Kasia P.; van Vliet, Lucas J.; Vos, Frans M.

    2018-03-01

    The Couinaud classification of hepatic anatomy partitions the liver into eight functionally independent segments. Detection and segmentation of the hepatic vein (HV), portal vein (PV) and inferior vena cava (IVC) plays an important role in the subsequent delineation of the liver segments. To facilitate pharmacokinetic modeling of the liver based on the same data, a 4D DCE-MR scan protocol was selected. This yields images with high temporal resolution but low spatial resolution. Since the liver's vasculature consists of many tiny branches, segmentation of these images is challenging. The proposed framework starts with registration of the 4D DCE-MRI series followed by region growing from manually annotated seeds in the main branches of key blood vessels in the liver. It calculates the Pearson correlation between the time intensity curves (TICs) of a seed and all voxels. A maximum correlation map for each vessel is obtained by combining the correlation maps for all branches of the same vessel through a maximum selection per voxel. The maximum correlation map is incorporated in a level set scheme to individually delineate the main vessels. Subsequently, the eight liver segments are segmented based on three vertical intersecting planes fit through the three skeleton branches of HV and IVC's center of mass as well as a horizontal plane fit through the skeleton of PV. Our segmentation regarding delineation of the vessels is more accurate than the results of two state-of-the-art techniques on five subjects in terms of the average symmetric surface distance (ASSD) and modified Hausdorff distance (MHD). Furthermore, the proposed liver partitioning achieves large overlap with manual reference segmentations (expressed in Dice Coefficient) in all but a small minority of segments (mean values between 87% and 94% for segments 2-8). The lower mean overlap for segment 1 (72%) is due to the limited spatial resolution of our DCE-MR scan protocol.

  19. DEWS (DEep White matter hyperintensity Segmentation framework): A fully automated pipeline for detecting small deep white matter hyperintensities in migraineurs.

    Science.gov (United States)

    Park, Bo-Yong; Lee, Mi Ji; Lee, Seung-Hak; Cha, Jihoon; Chung, Chin-Sang; Kim, Sung Tae; Park, Hyunjin

    2018-01-01

    Migraineurs show an increased load of white matter hyperintensities (WMHs) and more rapid deep WMH progression. Previous methods for WMH segmentation have limited efficacy to detect small deep WMHs. We developed a new fully automated detection pipeline, DEWS (DEep White matter hyperintensity Segmentation framework), for small and superficially-located deep WMHs. A total of 148 non-elderly subjects with migraine were included in this study. The pipeline consists of three components: 1) white matter (WM) extraction, 2) WMH detection, and 3) false positive reduction. In WM extraction, we adjusted the WM mask to re-assign misclassified WMHs back to WM using many sequential low-level image processing steps. In WMH detection, the potential WMH clusters were detected using an intensity based threshold and region growing approach. For false positive reduction, the detected WMH clusters were classified into final WMHs and non-WMHs using the random forest (RF) classifier. Size, texture, and multi-scale deep features were used to train the RF classifier. DEWS successfully detected small deep WMHs with a high positive predictive value (PPV) of 0.98 and true positive rate (TPR) of 0.70 in the training and test sets. Similar performance of PPV (0.96) and TPR (0.68) was attained in the validation set. DEWS showed a superior performance in comparison with other methods. Our proposed pipeline is freely available online to help the research community in quantifying deep WMHs in non-elderly adults.

  20. Deformable meshes for medical image segmentation accurate automatic segmentation of anatomical structures

    CERN Document Server

    Kainmueller, Dagmar

    2014-01-01

    ? Segmentation of anatomical structures in medical image data is an essential task in clinical practice. Dagmar Kainmueller introduces methods for accurate fully automatic segmentation of anatomical structures in 3D medical image data. The author's core methodological contribution is a novel deformation model that overcomes limitations of state-of-the-art Deformable Surface approaches, hence allowing for accurate segmentation of tip- and ridge-shaped features of anatomical structures. As for practical contributions, she proposes application-specific segmentation pipelines for a range of anatom

  1. The Slow-Growing Orange, A Demographer’s Look at Future Los Angeles,

    Science.gov (United States)

    1984-04-01

    and even some downtown Los Angeles neighborhoods, through " gentrification "--will grow rapidly at the expense of others. A second dramatic aspect of...shores. Modern developments in commuaications and transportation, which have enabled us to expand trade with Asia and Latin America, have also

  2. Effects of landscape change on fish assemblage structure in a rapidly growing metropolitan area in North Carolina, USA

    Science.gov (United States)

    Kennen, J.G.; Chang, M.; Tracy, B.H.

    2005-01-01

    We evaluated a comprehensive set of natural and land-use attributes that represent the major facets of urban development at fish monitoring sites in the rapidly growing Raleigh-Durham, North Carolina metropolitan area. We used principal component and correlation analysis to obtain a nonredundant subset of variables that extracted most variation in the complete set. With this subset of variables, we assessed the effect of urban growth on fish assemblage structure. We evaluated variation in fish assemblage structure with nonmetric multidimensional scaling (NMDS). We used correlation analysis to identify the most important environmental and landscape variables associated with significant NMDS axes. The second NMDS axis is related to many indices of land-use/land-cover change and habitat. Significant correlations with proportion of largest forest patch to total patch size (r = -0.460, P < 0.01), diversity of patch types (r = 0.554, P < 0.001), and population density (r = 0.385, P < 0.05) helped identify NMDS axis 2 as a disturbance gradient. Positive and negative correlations between the abundance of redbreast sunfish Lepomis auritus and bluehead chub Nocomis leptocephalus, respectively, and NMDS axis 2 also were evident. The North Carolina index of biotic integrity and many of its component metrics were highly correlated with urbanization. These results indicate that aquatic ecosystem integrity would be optimized by a comprehensive integrated management strategy that includes the preservation of landscape function by maximizing the conservation of contiguous tracts of forested lands and vegetative cover in watersheds. ?? 2005 by the American Fisheries Society.

  3. Rapid Analysis and Exploration of Fluorescence Microscopy Images

    OpenAIRE

    Pavie, Benjamin; Rajaram, Satwik; Ouyang, Austin; Altschuler, Jason; Steininger, Robert J; Wu, Lani; Altschuler, Steven

    2014-01-01

    Despite rapid advances in high-throughput microscopy, quantitative image-based assays still pose significant challenges. While a variety of specialized image analysis tools are available, most traditional image-analysis-based workflows have steep learning curves (for fine tuning of analysis parameters) and result in long turnaround times between imaging and analysis. In particular, cell segmentation, the process of identifying individual cells in an image, is a major bottleneck in this regard.

  4. Speaker segmentation and clustering

    OpenAIRE

    Kotti, M; Moschou, V; Kotropoulos, C

    2008-01-01

    07.08.13 KB. Ok to add the accepted version to Spiral, Elsevier says ok whlile mandate not enforced. This survey focuses on two challenging speech processing topics, namely: speaker segmentation and speaker clustering. Speaker segmentation aims at finding speaker change points in an audio stream, whereas speaker clustering aims at grouping speech segments based on speaker characteristics. Model-based, metric-based, and hybrid speaker segmentation algorithms are reviewed. Concerning speaker...

  5. Segmentation of the Infant Food Market

    OpenAIRE

    Hrůzová, Daniela

    2015-01-01

    The theoretical part covers general market segmentation, namely the marketing importance of differences among consumers, the essence of market segmentation, its main conditions and the process of segmentation, which consists of four consecutive phases - defining the market, determining important criteria, uncovering segments and developing segment profiles. The segmentation criteria, segmentation approaches, methods and techniques for the process of market segmentation are also described in t...

  6. SU-C-207B-03: A Geometrical Constrained Chan-Vese Based Tumor Segmentation Scheme for PET

    International Nuclear Information System (INIS)

    Chen, L; Zhou, Z; Wang, J

    2016-01-01

    Purpose: Accurate segmentation of tumor in PET is challenging when part of tumor is connected with normal organs/tissues with no difference in intensity. Conventional segmentation methods, such as thresholding or region growing, cannot generate satisfactory results in this case. We proposed a geometrical constrained Chan-Vese based scheme to segment tumor in PET for this special case by considering the similarity between two adjacent slices. Methods: The proposed scheme performs segmentation in a slice-by-slice fashion where an accurate segmentation of one slice is used as the guidance for segmentation of rest slices. For a slice that the tumor is not directly connected to organs/tissues with similar intensity values, a conventional clustering-based segmentation method under user’s guidance is used to obtain an exact tumor contour. This is set as the initial contour and the Chan-Vese algorithm is applied for segmenting the tumor in the next adjacent slice by adding constraints of tumor size, position and shape information. This procedure is repeated until the last slice of PET containing tumor. The proposed geometrical constrained Chan-Vese based algorithm was implemented in Matlab and its performance was tested on several cervical cancer patients where cervix and bladder are connected with similar activity values. The positive predictive values (PPV) are calculated to characterize the segmentation accuracy of the proposed scheme. Results: Tumors were accurately segmented by the proposed method even when they are connected with bladder in the image with no difference in intensity. The average PPVs were 0.9571±0.0355 and 0.9894±0.0271 for 17 slices and 11 slices of PET from two patients, respectively. Conclusion: We have developed a new scheme to segment tumor in PET images for the special case that the tumor is quite similar to or connected to normal organs/tissues in the image. The proposed scheme can provide a reliable way for segmenting tumors.

  7. SU-C-207B-03: A Geometrical Constrained Chan-Vese Based Tumor Segmentation Scheme for PET

    Energy Technology Data Exchange (ETDEWEB)

    Chen, L; Zhou, Z; Wang, J [UT Southwestern Medical Center, Dallas, TX (United States)

    2016-06-15

    Purpose: Accurate segmentation of tumor in PET is challenging when part of tumor is connected with normal organs/tissues with no difference in intensity. Conventional segmentation methods, such as thresholding or region growing, cannot generate satisfactory results in this case. We proposed a geometrical constrained Chan-Vese based scheme to segment tumor in PET for this special case by considering the similarity between two adjacent slices. Methods: The proposed scheme performs segmentation in a slice-by-slice fashion where an accurate segmentation of one slice is used as the guidance for segmentation of rest slices. For a slice that the tumor is not directly connected to organs/tissues with similar intensity values, a conventional clustering-based segmentation method under user’s guidance is used to obtain an exact tumor contour. This is set as the initial contour and the Chan-Vese algorithm is applied for segmenting the tumor in the next adjacent slice by adding constraints of tumor size, position and shape information. This procedure is repeated until the last slice of PET containing tumor. The proposed geometrical constrained Chan-Vese based algorithm was implemented in Matlab and its performance was tested on several cervical cancer patients where cervix and bladder are connected with similar activity values. The positive predictive values (PPV) are calculated to characterize the segmentation accuracy of the proposed scheme. Results: Tumors were accurately segmented by the proposed method even when they are connected with bladder in the image with no difference in intensity. The average PPVs were 0.9571±0.0355 and 0.9894±0.0271 for 17 slices and 11 slices of PET from two patients, respectively. Conclusion: We have developed a new scheme to segment tumor in PET images for the special case that the tumor is quite similar to or connected to normal organs/tissues in the image. The proposed scheme can provide a reliable way for segmenting tumors.

  8. Phasing multi-segment undulators

    International Nuclear Information System (INIS)

    Chavanne, J.; Elleaume, P.; Vaerenbergh, P. Van

    1996-01-01

    An important issue in the manufacture of multi-segment undulators as a source of synchrotron radiation or as a free-electron laser (FEL) is the phasing between successive segments. The state of the art is briefly reviewed, after which a novel pure permanent magnet phasing section that is passive and does not require any current is presented. The phasing section allows the introduction of a 6 mm longitudinal gap between each segment, resulting in complete mechanical independence and reduced magnetic interaction between segments. The tolerance of the longitudinal positioning of one segment with respect to the next is found to be 2.8 times lower than that of conventional phasing. The spectrum at all gaps and useful harmonics is almost unchanged when compared with a single-segment undulator of the same total length. (au) 3 refs

  9. Robust semi-automatic segmentation of pulmonary subsolid nodules in chest computed tomography scans

    International Nuclear Information System (INIS)

    Lassen, B C; Kuhnigk, J-M; Van Ginneken, B; Van Rikxoort, E M; Jacobs, C

    2015-01-01

    The malignancy of lung nodules is most often detected by analyzing changes of the nodule diameter in follow-up scans. A recent study showed that comparing the volume or the mass of a nodule over time is much more significant than comparing the diameter. Since the survival rate is higher when the disease is still in an early stage it is important to detect the growth rate as soon as possible. However manual segmentation of a volume is time-consuming. Whereas there are several well evaluated methods for the segmentation of solid nodules, less work is done on subsolid nodules which actually show a higher malignancy rate than solid nodules. In this work we present a fast, semi-automatic method for segmentation of subsolid nodules. As minimal user interaction the method expects a user-drawn stroke on the largest diameter of the nodule. First, a threshold-based region growing is performed based on intensity analysis of the nodule region and surrounding parenchyma. In the next step the chest wall is removed by a combination of a connected component analyses and convex hull calculation. Finally, attached vessels are detached by morphological operations. The method was evaluated on all nodules of the publicly available LIDC/IDRI database that were manually segmented and rated as non-solid or part-solid by four radiologists (Dataset 1) and three radiologists (Dataset 2). For these 59 nodules the Jaccard index for the agreement of the proposed method with the manual reference segmentations was 0.52/0.50 (Dataset 1/Dataset 2) compared to an inter-observer agreement of the manual segmentations of 0.54/0.58 (Dataset 1/Dataset 2). Furthermore, the inter-observer agreement using the proposed method (i.e. different input strokes) was analyzed and gave a Jaccard index of 0.74/0.74 (Dataset 1/Dataset 2). The presented method provides satisfactory segmentation results with minimal observer effort in minimal time and can reduce the inter-observer variability for segmentation of

  10. Robust semi-automatic segmentation of pulmonary subsolid nodules in chest computed tomography scans

    Science.gov (United States)

    Lassen, B. C.; Jacobs, C.; Kuhnigk, J.-M.; van Ginneken, B.; van Rikxoort, E. M.

    2015-02-01

    The malignancy of lung nodules is most often detected by analyzing changes of the nodule diameter in follow-up scans. A recent study showed that comparing the volume or the mass of a nodule over time is much more significant than comparing the diameter. Since the survival rate is higher when the disease is still in an early stage it is important to detect the growth rate as soon as possible. However manual segmentation of a volume is time-consuming. Whereas there are several well evaluated methods for the segmentation of solid nodules, less work is done on subsolid nodules which actually show a higher malignancy rate than solid nodules. In this work we present a fast, semi-automatic method for segmentation of subsolid nodules. As minimal user interaction the method expects a user-drawn stroke on the largest diameter of the nodule. First, a threshold-based region growing is performed based on intensity analysis of the nodule region and surrounding parenchyma. In the next step the chest wall is removed by a combination of a connected component analyses and convex hull calculation. Finally, attached vessels are detached by morphological operations. The method was evaluated on all nodules of the publicly available LIDC/IDRI database that were manually segmented and rated as non-solid or part-solid by four radiologists (Dataset 1) and three radiologists (Dataset 2). For these 59 nodules the Jaccard index for the agreement of the proposed method with the manual reference segmentations was 0.52/0.50 (Dataset 1/Dataset 2) compared to an inter-observer agreement of the manual segmentations of 0.54/0.58 (Dataset 1/Dataset 2). Furthermore, the inter-observer agreement using the proposed method (i.e. different input strokes) was analyzed and gave a Jaccard index of 0.74/0.74 (Dataset 1/Dataset 2). The presented method provides satisfactory segmentation results with minimal observer effort in minimal time and can reduce the inter-observer variability for segmentation of

  11. Segmented-spectrum detection mechanism for medical x-ray in CdTe

    Science.gov (United States)

    Shi, Zaifeng; Meng, Qingzhen; Cao, Qingjie; Yao, Suying

    2016-01-01

    This paper presents a segmented X-ray spectrum detection method based on a layered X-ray detector in Cadmium Telluride (CdTe) substrate. We describe the three-dimensional structure of proposed detector pixel and investigate the matched spectrum-resolving method. Polychromatic X-ray beam enter the CdTe substrate edge on and will be absorbed completely in different thickness varying with photon energy. Discrete potential wells are formed under external controlling voltage to collect the photo-electrons generated in different layers, and segmented X-ray spectrum can be deduced from the quantity of photo-electrons. In this work, we verify the feasibility of the segmented-spectrum detection mechanism by simulating the absorption of monochromatic X-ray in a CdTe substrate. Experiments in simulation show that the number of photo-electrons grow exponentially with the increase of incident thickness, and photons with different energy will be absorbed in various thickness. The charges generated in different layers are collected into adjacent potential wells, and collection efficiency is estimated to be about 87% for different incident intensity under the 40000V/cm electric field. Errors caused by charge sharing between neighboring layers are also analyzed, and it can be considered negligible by setting appropriate size of electrodes.

  12. Dynamic thermal characteristics of heat pipe via segmented thermal resistance model for electric vehicle battery cooling

    Science.gov (United States)

    Liu, Feifei; Lan, Fengchong; Chen, Jiqing

    2016-07-01

    Heat pipe cooling for battery thermal management systems (BTMSs) in electric vehicles (EVs) is growing due to its advantages of high cooling efficiency, compact structure and flexible geometry. Considering the transient conduction, phase change and uncertain thermal conditions in a heat pipe, it is challenging to obtain the dynamic thermal characteristics accurately in such complex heat and mass transfer process. In this paper, a ;segmented; thermal resistance model of a heat pipe is proposed based on thermal circuit method. The equivalent conductivities of different segments, viz. the evaporator and condenser of pipe, are used to determine their own thermal parameters and conditions integrated into the thermal model of battery for a complete three-dimensional (3D) computational fluid dynamics (CFD) simulation. The proposed ;segmented; model shows more precise than the ;non-segmented; model by the comparison of simulated and experimental temperature distribution and variation of an ultra-thin micro heat pipe (UMHP) battery pack, and has less calculation error to obtain dynamic thermal behavior for exact thermal design, management and control of heat pipe BTMSs. Using the ;segmented; model, the cooling effect of the UMHP pack with different natural/forced convection and arrangements is predicted, and the results correspond well to the tests.

  13. FRAMEWORK FOR COMPARING SEGMENTATION ALGORITHMS

    Directory of Open Access Journals (Sweden)

    G. Sithole

    2015-05-01

    Full Text Available The notion of a ‘Best’ segmentation does not exist. A segmentation algorithm is chosen based on the features it yields, the properties of the segments (point sets it generates, and the complexity of its algorithm. The segmentation is then assessed based on a variety of metrics such as homogeneity, heterogeneity, fragmentation, etc. Even after an algorithm is chosen its performance is still uncertain because the landscape/scenarios represented in a point cloud have a strong influence on the eventual segmentation. Thus selecting an appropriate segmentation algorithm is a process of trial and error. Automating the selection of segmentation algorithms and their parameters first requires methods to evaluate segmentations. Three common approaches for evaluating segmentation algorithms are ‘goodness methods’, ‘discrepancy methods’ and ‘benchmarks’. Benchmarks are considered the most comprehensive method of evaluation. This paper shortcomings in current benchmark methods are identified and a framework is proposed that permits both a visual and numerical evaluation of segmentations for different algorithms, algorithm parameters and evaluation metrics. The concept of the framework is demonstrated on a real point cloud. Current results are promising and suggest that it can be used to predict the performance of segmentation algorithms.

  14. Why segmentation matters: experience-driven segmentation errors impair “morpheme” learning

    Science.gov (United States)

    Finn, Amy S.; Hudson Kam, Carla L.

    2015-01-01

    We ask whether an adult learner’s knowledge of their native language impedes statistical learning in a new language beyond just word segmentation (as previously shown). In particular, we examine the impact of native-language word-form phonotactics on learners’ ability to segment words into their component morphemes and learn phonologically triggered variation of morphemes. We find that learning is impaired when words and component morphemes are structured to conflict with a learner’s native-language phonotactic system, but not when native-language phonotactics do not conflict with morpheme boundaries in the artificial language. A learner’s native-language knowledge can therefore have a cascading impact affecting word segmentation and the morphological variation that relies upon proper segmentation. These results show that getting word segmentation right early in learning is deeply important for learning other aspects of language, even those (morphology) that are known to pose a great difficulty for adult language learners. PMID:25730305

  15. Segment-Tube: Spatio-Temporal Action Localization in Untrimmed Videos with Per-Frame Segmentation

    OpenAIRE

    Le Wang; Xuhuan Duan; Qilin Zhang; Zhenxing Niu; Gang Hua; Nanning Zheng

    2018-01-01

    Inspired by the recent spatio-temporal action localization efforts with tubelets (sequences of bounding boxes), we present a new spatio-temporal action localization detector Segment-tube, which consists of sequences of per-frame segmentation masks. The proposed Segment-tube detector can temporally pinpoint the starting/ending frame of each action category in the presence of preceding/subsequent interference actions in untrimmed videos. Simultaneously, the Segment-tube detector produces per-fr...

  16. Deep convolutional neural network and 3D deformable approach for tissue segmentation in musculoskeletal magnetic resonance imaging.

    Science.gov (United States)

    Liu, Fang; Zhou, Zhaoye; Jang, Hyungseok; Samsonov, Alexey; Zhao, Gengyan; Kijowski, Richard

    2018-04-01

    To describe and evaluate a new fully automated musculoskeletal tissue segmentation method using deep convolutional neural network (CNN) and three-dimensional (3D) simplex deformable modeling to improve the accuracy and efficiency of cartilage and bone segmentation within the knee joint. A fully automated segmentation pipeline was built by combining a semantic segmentation CNN and 3D simplex deformable modeling. A CNN technique called SegNet was applied as the core of the segmentation method to perform high resolution pixel-wise multi-class tissue classification. The 3D simplex deformable modeling refined the output from SegNet to preserve the overall shape and maintain a desirable smooth surface for musculoskeletal structure. The fully automated segmentation method was tested using a publicly available knee image data set to compare with currently used state-of-the-art segmentation methods. The fully automated method was also evaluated on two different data sets, which include morphological and quantitative MR images with different tissue contrasts. The proposed fully automated segmentation method provided good segmentation performance with segmentation accuracy superior to most of state-of-the-art methods in the publicly available knee image data set. The method also demonstrated versatile segmentation performance on both morphological and quantitative musculoskeletal MR images with different tissue contrasts and spatial resolutions. The study demonstrates that the combined CNN and 3D deformable modeling approach is useful for performing rapid and accurate cartilage and bone segmentation within the knee joint. The CNN has promising potential applications in musculoskeletal imaging. Magn Reson Med 79:2379-2391, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

  17. An efficient global energy optimization approach for robust 3D plane segmentation of point clouds

    Science.gov (United States)

    Dong, Zhen; Yang, Bisheng; Hu, Pingbo; Scherer, Sebastian

    2018-03-01

    Automatic 3D plane segmentation is necessary for many applications including point cloud registration, building information model (BIM) reconstruction, simultaneous localization and mapping (SLAM), and point cloud compression. However, most of the existing 3D plane segmentation methods still suffer from low precision and recall, and inaccurate and incomplete boundaries, especially for low-quality point clouds collected by RGB-D sensors. To overcome these challenges, this paper formulates the plane segmentation problem as a global energy optimization because it is robust to high levels of noise and clutter. First, the proposed method divides the raw point cloud into multiscale supervoxels, and considers planar supervoxels and individual points corresponding to nonplanar supervoxels as basic units. Then, an efficient hybrid region growing algorithm is utilized to generate initial plane set by incrementally merging adjacent basic units with similar features. Next, the initial plane set is further enriched and refined in a mutually reinforcing manner under the framework of global energy optimization. Finally, the performances of the proposed method are evaluated with respect to six metrics (i.e., plane precision, plane recall, under-segmentation rate, over-segmentation rate, boundary precision, and boundary recall) on two benchmark datasets. Comprehensive experiments demonstrate that the proposed method obtained good performances both in high-quality TLS point clouds (i.e., http://SEMANTIC3D.NET)

  18. Grow, Baby, Grow

    Science.gov (United States)

    Maybe you quit smoking during your pregnancy. Or maybe you struggled and weren’t able to stay quit. Now that your baby is here, trying to stay away from smoking is still important. That’s because the chemicals in smoke can make it harder for your baby to grow like he or she should.

  19. Genetics in Ophthalmology III – Posterior Segment Diseases

    Directory of Open Access Journals (Sweden)

    Canan Aslı Utine

    2012-10-01

    Full Text Available Genetic diseases are congenital or acquired hereditary diseases that result from structural/functional disorders of the human genome. Today, the genetic factors that play a role in many diseases are being highlighted with the rapid progress in the field of genetics science. It becomes increasingly important that physicians from all disciplines have knowledge about the basic principles of genetics, patterns of inheritance, etc., so that they can follow the new developments. In genetic eye diseases, ophthalmologists should know the basic clinical and recently rapidly developing genetic characteristics of these diseases in order to properly approach the diagnosis and treatment and to provide genetic counseling. In this paper, posterior segment eye diseases of genetic origin are reviewed, and retinoblastoma, mitochondrial diseases, retinal dysplasia, retinitis pigmentosa, choroideremia, gyrate atrophy, Alström disease, ocular albinism, optic nerve hypoplasia, anophthalmia/microphthalmia and Leber’s congenital amaurosis are covered. (Turk J Ophthalmol 2012; 42: 386-92

  20. Rapid Conditioning for the Next Generation Melting System

    Energy Technology Data Exchange (ETDEWEB)

    Rue, David M. [Gas Technology Institute, Des Plaines, IL (United States)

    2015-06-17

    This report describes work on Rapid Conditioning for the Next Generation Melting System under US Department of Energy Contract DE-FC36-06GO16010. The project lead was the Gas Technology Institute (GTI). Partners included Owens Corning and Johns Manville. Cost share for this project was provided by NYSERDA (the New York State Energy Research and Development Authority), Owens Corning, Johns Manville, Owens Illinois, and the US natural gas industry through GTI’s SMP and UTD programs. The overreaching focus of this project was to study and develop rapid refining approaches for segmented glass manufacturing processes using high-intensity melters such as the submerged combustion melter. The objectives of this project were to 1) test and evaluate the most promising approaches to rapidly condition the homogeneous glass produced from the submerged combustion melter, and 2) to design a pilot-scale NGMS system for fiberglass recycle.

  1. In Vitro Comparison of Ertapenem, Meropenem, and Imipenem against Isolates of Rapidly Growing Mycobacteria and Nocardia by Use of Broth Microdilution and Etest.

    Science.gov (United States)

    Brown-Elliott, Barbara A; Killingley, Jessica; Vasireddy, Sruthi; Bridge, Linda; Wallace, Richard J

    2016-06-01

    We compared the activities of the carbapenems ertapenem, meropenem, and imipenem against 180 isolates of rapidly growing mycobacteria (RGM) and 170 isolates of Nocardia using the Clinical and Laboratory Standards Institute (CLSI) guidelines. A subset of isolates was tested using the Etest. The rate of susceptibility to ertapenem and meropenem was limited and less than that to imipenem for the RGM. Analysis of major and minor discrepancies revealed that >90% of the isolates of Nocardia had higher MICs by the broth microdilution method than by Etest, in contrast to the lower broth microdilution MICs seen for >80% of the RGM. Imipenem remains the most active carbapenem against RGM, including Mycobacterium abscessus subsp. abscessus For Nocardia, imipenem was significantly more active only against Nocardia farcinica Although there may be utility in testing the activities of the newer carbapenems against Nocardia, their activities against the RGM should not be routinely tested. Testing by Etest is not recommended by the CLSI. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

  2. Translation-aware semantic segmentation via conditional least-square generative adversarial networks

    Science.gov (United States)

    Zhang, Mi; Hu, Xiangyun; Zhao, Like; Pang, Shiyan; Gong, Jinqi; Luo, Min

    2017-10-01

    Semantic segmentation has recently made rapid progress in the field of remote sensing and computer vision. However, many leading approaches cannot simultaneously translate label maps to possible source images with a limited number of training images. The core issue is insufficient adversarial information to interpret the inverse process and proper objective loss function to overcome the vanishing gradient problem. We propose the use of conditional least squares generative adversarial networks (CLS-GAN) to delineate visual objects and solve these problems. We trained the CLS-GAN network for semantic segmentation to discriminate dense prediction information either from training images or generative networks. We show that the optimal objective function of CLS-GAN is a special class of f-divergence and yields a generator that lies on the decision boundary of discriminator that reduces possible vanished gradient. We also demonstrate the effectiveness of the proposed architecture at translating images from label maps in the learning process. Experiments on a limited number of high resolution images, including close-range and remote sensing datasets, indicate that the proposed method leads to the improved semantic segmentation accuracy and can simultaneously generate high quality images from label maps.

  3. How Cloud Computing can help SMEs to grow faster?

    OpenAIRE

    Hasan, Ahmed Anwar

    2010-01-01

    In recent years, Cloud computing has successfully created hype and lots of people think that cloud computing might be the next big thing. The cloud platform is growing rapidly and lots of cloud service provider companies are coming up with huge number of innovative ideas where they are addressing specific needs of different organisations. The cloud computing is based on a service model architecture which is highly customisable and can fit into a specific or unique business process. Cloud comp...

  4. A robust pointer segmentation in biomedical images toward building a visual ontology for biomedical article retrieval

    Science.gov (United States)

    You, Daekeun; Simpson, Matthew; Antani, Sameer; Demner-Fushman, Dina; Thoma, George R.

    2013-01-01

    Pointers (arrows and symbols) are frequently used in biomedical images to highlight specific image regions of interest (ROIs) that are mentioned in figure captions and/or text discussion. Detection of pointers is the first step toward extracting relevant visual features from ROIs and combining them with textual descriptions for a multimodal (text and image) biomedical article retrieval system. Recently we developed a pointer recognition algorithm based on an edge-based pointer segmentation method, and subsequently reported improvements made on our initial approach involving the use of Active Shape Models (ASM) for pointer recognition and region growing-based method for pointer segmentation. These methods contributed to improving the recall of pointer recognition but not much to the precision. The method discussed in this article is our recent effort to improve the precision rate. Evaluation performed on two datasets and compared with other pointer segmentation methods show significantly improved precision and the highest F1 score.

  5. Metabolomic response of Calotropis procera growing in the desert to changes in water availability.

    Science.gov (United States)

    Ramadan, Ahmed; Sabir, Jamal S M; Alakilli, Saleha Y M; Shokry, Ahmed M; Gadalla, Nour O; Edris, Sherif; Al-Kordy, Magdy A; Al-Zahrani, Hassan S; El-Domyati, Fotouh M; Bahieldin, Ahmed; Baker, Neil R; Willmitzer, Lothar; Irgang, Susann

    2014-01-01

    Water availability is a major limitation for agricultural productivity. Plants growing in severe arid climates such as deserts provide tools for studying plant growth and performance under extreme drought conditions. The perennial species Calotropis procera used in this study is a shrub growing in many arid areas which has an exceptional ability to adapt and be productive in severe arid conditions. We describe the results of studying the metabolomic response of wild C procera plants growing in the desert to a one time water supply. Leaves of C. procera plants were taken at three time points before and 1 hour, 6 hours and 12 hours after watering and subjected to a metabolomics and lipidomics analysis. Analysis of the data reveals that within one hour after watering C. procera has already responded on the metabolic level to the sudden water availability as evidenced by major changes such as increased levels of most amino acids, a decrease in sucrose, raffinose and maltitol, a decrease in storage lipids (triacylglycerols) and an increase in membrane lipids including photosynthetic membranes. These changes still prevail at the 6 hour time point after watering however 12 hours after watering the metabolomics data are essentially indistinguishable from the prewatering state thus demonstrating not only a rapid response to water availability but also a rapid response to loss of water. Taken together these data suggest that the ability of C. procera to survive under the very harsh drought conditions prevailing in the desert might be associated with its rapid adjustments to water availability and losses.

  6. Joint shape segmentation with linear programming

    KAUST Repository

    Huang, Qixing

    2011-01-01

    We present an approach to segmenting shapes in a heterogenous shape database. Our approach segments the shapes jointly, utilizing features from multiple shapes to improve the segmentation of each. The approach is entirely unsupervised and is based on an integer quadratic programming formulation of the joint segmentation problem. The program optimizes over possible segmentations of individual shapes as well as over possible correspondences between segments from multiple shapes. The integer quadratic program is solved via a linear programming relaxation, using a block coordinate descent procedure that makes the optimization feasible for large databases. We evaluate the presented approach on the Princeton segmentation benchmark and show that joint shape segmentation significantly outperforms single-shape segmentation techniques. © 2011 ACM.

  7. Segment scheduling method for reducing 360° video streaming latency

    Science.gov (United States)

    Gudumasu, Srinivas; Asbun, Eduardo; He, Yong; Ye, Yan

    2017-09-01

    360° video is an emerging new format in the media industry enabled by the growing availability of virtual reality devices. It provides the viewer a new sense of presence and immersion. Compared to conventional rectilinear video (2D or 3D), 360° video poses a new and difficult set of engineering challenges on video processing and delivery. Enabling comfortable and immersive user experience requires very high video quality and very low latency, while the large video file size poses a challenge to delivering 360° video in a quality manner at scale. Conventionally, 360° video represented in equirectangular or other projection formats can be encoded as a single standards-compliant bitstream using existing video codecs such as H.264/AVC or H.265/HEVC. Such method usually needs very high bandwidth to provide an immersive user experience. While at the client side, much of such high bandwidth and the computational power used to decode the video are wasted because the user only watches a small portion (i.e., viewport) of the entire picture. Viewport dependent 360°video processing and delivery approaches spend more bandwidth on the viewport than on non-viewports and are therefore able to reduce the overall transmission bandwidth. This paper proposes a dual buffer segment scheduling algorithm for viewport adaptive streaming methods to reduce latency when switching between high quality viewports in 360° video streaming. The approach decouples the scheduling of viewport segments and non-viewport segments to ensure the viewport segment requested matches the latest user head orientation. A base layer buffer stores all lower quality segments, and a viewport buffer stores high quality viewport segments corresponding to the most recent viewer's head orientation. The scheduling scheme determines viewport requesting time based on the buffer status and the head orientation. This paper also discusses how to deploy the proposed scheduling design for various viewport adaptive video

  8. The hydrodynamics of segmented two-phase flow in a circular tube with rapidly dissolving drops.

    Science.gov (United States)

    Leary, Thomas F; Ramachandran, Arun

    2017-05-03

    This article discusses boundary integral simulations of dissolving drops flowing through a cylindrical tube for large aspect ratio drops. The dynamics of drop dissolution is determined by three dimensionless parameters: λ, the viscosity of the drop fluid relative to the suspending fluid; Ca, the capillary number defining the ratio of the hydrodynamic force to the interfacial tension force; and k, a dissolution constant based on the velocity of dissolution. For a single dissolving drop, the velocity in the upstream region is greater than the downstream region, and for sufficiently large k, the downstream velocity can be completely reversed, particularly at low Ca. The upstream end of the drop travels faster and experiences greater deformation than the downstream end. The film thickness, δ, between the drop and the tube wall is governed by a delicate balance between dissolution and changes in the outer fluid velocity resulting from a fixed pressure drop across the tube and mass continuity. Therefore, δ, and consequently, the drop average velocity, can increase, decrease or be relatively invariant in time. For two drops flowing in succession, while low Ca drops maintain a nearly constant separation distance during dissolution, at sufficiently large Ca, for all values of k, dissolution increases the separation distance between drops. Under these conditions, the liquid segments between two adjacent drops can no longer be considered as constant volume stirred tanks. These results will guide the choices of geometry and operating parameters that will facilitate the characterization of fast gas-liquid reactions via two-phase segmented flows.

  9. Segmentation-DrivenTomographic Reconstruction

    DEFF Research Database (Denmark)

    Kongskov, Rasmus Dalgas

    such that the segmentation subsequently can be carried out by use of a simple segmentation method, for instance just a thresholding method. We tested the advantages of going from a two-stage reconstruction method to a one stage segmentation-driven reconstruction method for the phase contrast tomography reconstruction......The tomographic reconstruction problem is concerned with creating a model of the interior of an object from some measured data, typically projections of the object. After reconstructing an object it is often desired to segment it, either automatically or manually. For computed tomography (CT...

  10. Rediscovering market segmentation.

    Science.gov (United States)

    Yankelovich, Daniel; Meer, David

    2006-02-01

    In 1964, Daniel Yankelovich introduced in the pages of HBR the concept of nondemographic segmentation, by which he meant the classification of consumers according to criteria other than age, residence, income, and such. The predictive power of marketing studies based on demographics was no longer strong enough to serve as a basis for marketing strategy, he argued. Buying patterns had become far better guides to consumers' future purchases. In addition, properly constructed nondemographic segmentations could help companies determine which products to develop, which distribution channels to sell them in, how much to charge for them, and how to advertise them. But more than 40 years later, nondemographic segmentation has become just as unenlightening as demographic segmentation had been. Today, the technique is used almost exclusively to fulfill the needs of advertising, which it serves mainly by populating commercials with characters that viewers can identify with. It is true that psychographic types like "High-Tech Harry" and "Joe Six-Pack" may capture some truth about real people's lifestyles, attitudes, self-image, and aspirations. But they are no better than demographics at predicting purchase behavior. Thus they give corporate decision makers very little idea of how to keep customers or capture new ones. Now, Daniel Yankelovich returns to these pages, with consultant David Meer, to argue the case for a broad view of nondemographic segmentation. They describe the elements of a smart segmentation strategy, explaining how segmentations meant to strengthen brand identity differ from those capable of telling a company which markets it should enter and what goods to make. And they introduce their "gravity of decision spectrum", a tool that focuses on the form of consumer behavior that should be of the greatest interest to marketers--the importance that consumers place on a product or product category.

  11. Building stewardship with recreation users: an approach of market segmentation to meet the goal of public-lands management

    Science.gov (United States)

    Po-Hsin Lai; Chia-Kuen Cheng; David Scott

    2007-01-01

    Participation in outdoor recreation has been increasing at a rate far exceeding the population growth since the 1980s. The growing demand for outdoor recreation amenities has imposed a great challenge on resource management agencies of public lands. This study proposed a segmentation framework to identify different outdoor recreation groups based on their attitudes...

  12. Automated segmentation of geographic atrophy using deep convolutional neural networks

    Science.gov (United States)

    Hu, Zhihong; Wang, Ziyuan; Sadda, SriniVas R.

    2018-02-01

    Geographic atrophy (GA) is an end-stage manifestation of the advanced age-related macular degeneration (AMD), the leading cause of blindness and visual impairment in developed nations. Techniques to rapidly and precisely detect and quantify GA would appear to be of critical importance in advancing the understanding of its pathogenesis. In this study, we develop an automated supervised classification system using deep convolutional neural networks (CNNs) for segmenting GA in fundus autofluorescene (FAF) images. More specifically, to enhance the contrast of GA relative to the background, we apply the contrast limited adaptive histogram equalization. Blood vessels may cause GA segmentation errors due to similar intensity level to GA. A tensor-voting technique is performed to identify the blood vessels and a vessel inpainting technique is applied to suppress the GA segmentation errors due to the blood vessels. To handle the large variation of GA lesion sizes, three deep CNNs with three varying sized input image patches are applied. Fifty randomly chosen FAF images are obtained from fifty subjects with GA. The algorithm-defined GA regions are compared with manual delineation by a certified grader. A two-fold cross-validation is applied to evaluate the algorithm performance. The mean segmentation accuracy, true positive rate (i.e. sensitivity), true negative rate (i.e. specificity), positive predictive value, false discovery rate, and overlap ratio, between the algorithm- and manually-defined GA regions are 0.97 +/- 0.02, 0.89 +/- 0.08, 0.98 +/- 0.02, 0.87 +/- 0.12, 0.13 +/- 0.12, and 0.79 +/- 0.12 respectively, demonstrating a high level of agreement.

  13. Ethical, moral and social dimensions in farm production practices: a segmentation study to assess Irish consumers’ perceptions of meat quality

    Directory of Open Access Journals (Sweden)

    Regan Á.

    2018-03-01

    Full Text Available Growing consumer concerns with modern farming and food production systems indicate a significant market opportunity for meat production practices that consider ethical, moral and social value traits. In the current study, we aimed to identify and characterise distinct segments of Irish consumers based on their perceptions of the quality of meat from different farm-level production practices (organic farming, high animal welfare standards, free range farming, and “natural”, treatment-free feeding regimes. An online survey was carried out with 251 Irish meat consumers. Using cluster analysis, we identified three distinct segments: “Target consumers”, “Purist consumers” and “Disinterested consumers”. Chi-square analyses revealed differences between the segments based on gender, age and meat-purchasing motivations. The results provide insight into the opportunities that exist for exploring new viable market segments as well as for engaging Irish consumers and empowering them with information around the ethical, social and moral aspects of farm-level practices related to meat production.

  14. Effect of Rapid Maxillary Expansion on Glenoid Fossa and Condyle-Fossa Relationship in Growing Patients (MEGP): Study Protocol for a Controlled Clinical Trial

    Science.gov (United States)

    Ghoussoub, Mona Sayegh; Rifai, Khaldoun; Garcia, Robert; Sleilaty, Ghassan

    2018-01-01

    Aims and Objectives: Rapid maxillary expansion (RME) is an orthodontic nonsurgical procedure aiming at increasing the width of the maxilla by opening mainly the intermaxillary suture in patients presenting a transverse maxillary skeletal deficiency. The objectives of the current prospective controlled clinical and radiographic study are to evaluate the hypothesis that RME in growing patients will result in radiographic changes at the level of interglenoid fossa distance, condyle-fossa relationship, and nasal cavity widths compared to the group who received no treatment initially and served as untreated control. Materials and Methods: In this prospective controlled clinical and radiographic study, forty healthy growing patients selected from a school-based population following a large screening campaign, ranging in age between 8 and 13 years, presenting a maxillary constriction with bilateral crossbite, and candidates for RME are being recruited. The first group will include participants willing to undergo treatment (n = 25) and the other group will include those inclined to postpone (n = 15). Results: The primary outcome is to compare radiologically the interglenoid fossa distance and the condyle-fossa relationship; nasal cavity width will be a secondary outcome. A multivariable analysis of Covariance model will be used, with the assessment of the time by group interaction, using age as covariate. The project protocol was reviewed and approved by the Ethics Committee of the Lebanese University, National Institute in Lebanon (CUEMB process number 31/04/2015). The study is funded by the Lebanese University and Centre National de Recherche Scientifique, Lebanon (Number: 652 on 14/04/2016). Conclusion: This prospective controlled clinical trial will give information about the effect of RME on the glenoid fossa and condyle-fossa relationship and its impact on the nasal cavity width. Trial Registration: Retrospectively registered in BioMed Central (DOI10.1186/ISRCTN

  15. A Segment-Based Trajectory Similarity Measure in the Urban Transportation Systems.

    Science.gov (United States)

    Mao, Yingchi; Zhong, Haishi; Xiao, Xianjian; Li, Xiaofang

    2017-03-06

    With the rapid spread of built-in GPS handheld smart devices, the trajectory data from GPS sensors has grown explosively. Trajectory data has spatio-temporal characteristics and rich information. Using trajectory data processing techniques can mine the patterns of human activities and the moving patterns of vehicles in the intelligent transportation systems. A trajectory similarity measure is one of the most important issues in trajectory data mining (clustering, classification, frequent pattern mining, etc.). Unfortunately, the main similarity measure algorithms with the trajectory data have been found to be inaccurate, highly sensitive of sampling methods, and have low robustness for the noise data. To solve the above problems, three distances and their corresponding computation methods are proposed in this paper. The point-segment distance can decrease the sensitivity of the point sampling methods. The prediction distance optimizes the temporal distance with the features of trajectory data. The segment-segment distance introduces the trajectory shape factor into the similarity measurement to improve the accuracy. The three kinds of distance are integrated with the traditional dynamic time warping algorithm (DTW) algorithm to propose a new segment-based dynamic time warping algorithm (SDTW). The experimental results show that the SDTW algorithm can exhibit about 57%, 86%, and 31% better accuracy than the longest common subsequence algorithm (LCSS), and edit distance on real sequence algorithm (EDR) , and DTW, respectively, and that the sensitivity to the noise data is lower than that those algorithms.

  16. Lung segment geometry study: simulation of largest possible tumours that fit into bronchopulmonary segments.

    Science.gov (United States)

    Welter, S; Stöcker, C; Dicken, V; Kühl, H; Krass, S; Stamatis, G

    2012-03-01

    Segmental resection in stage I non-small cell lung cancer (NSCLC) has been well described and is considered to have similar survival rates as lobectomy but with increased rates of local tumour recurrence due to inadequate parenchymal margins. In consequence, today segmentectomy is only performed when the tumour is smaller than 2 cm. Three-dimensional reconstructions from 11 thin-slice CT scans of bronchopulmonary segments were generated, and virtual spherical tumours were placed over the segments, respecting all segmental borders. As a next step, virtual parenchymal safety margins of 2 cm and 3 cm were subtracted and the size of the remaining tumour calculated. The maximum tumour diameters with a 30-mm parenchymal safety margin ranged from 26.1 mm in right-sided segments 7 + 8 to 59.8 mm in the left apical segments 1-3. Using a three-dimensional reconstruction of lung CT scans, we demonstrated that segmentectomy or resection of segmental groups should be feasible with adequate margins, even for larger tumours in selected cases. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

  17. Research Article Special Issue

    African Journals Online (AJOL)

    pc

    2017-11-10

    Nov 10, 2017 ... telecommunications industry has become a rapidly growing market. ... that if firms are fully aware of which segment of the customers poses high risk of churn, ... where y = dependent variables or predicted values, α = constant ...

  18. Investigation on the Weighted RANSAC Approaches for Building Roof Plane Segmentation from LiDAR Point Clouds

    Directory of Open Access Journals (Sweden)

    Bo Xu

    2015-12-01

    Full Text Available RANdom SAmple Consensus (RANSAC is a widely adopted method for LiDAR point cloud segmentation because of its robustness to noise and outliers. However, RANSAC has a tendency to generate false segments consisting of points from several nearly coplanar surfaces. To address this problem, we formulate the weighted RANSAC approach for the purpose of point cloud segmentation. In our proposed solution, the hard threshold voting function which considers both the point-plane distance and the normal vector consistency is transformed into a soft threshold voting function based on two weight functions. To improve weighted RANSAC’s ability to distinguish planes, we designed the weight functions according to the difference in the error distribution between the proper and improper plane hypotheses, based on which an outlier suppression ratio was also defined. Using the ratio, a thorough comparison was conducted between these different weight functions to determine the best performing function. The selected weight function was then compared to the existing weighted RANSAC methods, the original RANSAC, and a representative region growing (RG method. Experiments with two airborne LiDAR datasets of varying densities show that the various weighted methods can improve the segmentation quality differently, but the dedicated designed weight functions can significantly improve the segmentation accuracy and the topology correctness. Moreover, its robustness is much better when compared to the RG method.

  19. Electroporation-based treatment planning for deep-seated tumors based on automatic liver segmentation of MRI images.

    Science.gov (United States)

    Pavliha, Denis; Mušič, Maja M; Serša, Gregor; Miklavčič, Damijan

    2013-01-01

    Electroporation is the phenomenon that occurs when a cell is exposed to a high electric field, which causes transient cell membrane permeabilization. A paramount electroporation-based application is electrochemotherapy, which is performed by delivering high-voltage electric pulses that enable the chemotherapeutic drug to more effectively destroy the tumor cells. Electrochemotherapy can be used for treating deep-seated metastases (e.g. in the liver, bone, brain, soft tissue) using variable-geometry long-needle electrodes. To treat deep-seated tumors, patient-specific treatment planning of the electroporation-based treatment is required. Treatment planning is based on generating a 3D model of the organ and target tissue subject to electroporation (i.e. tumor nodules). The generation of the 3D model is done by segmentation algorithms. We implemented and evaluated three automatic liver segmentation algorithms: region growing, adaptive threshold, and active contours (snakes). The algorithms were optimized using a seven-case dataset manually segmented by the radiologist as a training set, and finally validated using an additional four-case dataset that was previously not included in the optimization dataset. The presented results demonstrate that patient's medical images that were not included in the training set can be successfully segmented using our three algorithms. Besides electroporation-based treatments, these algorithms can be used in applications where automatic liver segmentation is required.

  20. Performance of an Artificial Multi-observer Deep Neural Network for Fully Automated Segmentation of Polycystic Kidneys.

    Science.gov (United States)

    Kline, Timothy L; Korfiatis, Panagiotis; Edwards, Marie E; Blais, Jaime D; Czerwiec, Frank S; Harris, Peter C; King, Bernard F; Torres, Vicente E; Erickson, Bradley J

    2017-08-01

    Deep learning techniques are being rapidly applied to medical imaging tasks-from organ and lesion segmentation to tissue and tumor classification. These techniques are becoming the leading algorithmic approaches to solve inherently difficult image processing tasks. Currently, the most critical requirement for successful implementation lies in the need for relatively large datasets that can be used for training the deep learning networks. Based on our initial studies of MR imaging examinations of the kidneys of patients affected by polycystic kidney disease (PKD), we have generated a unique database of imaging data and corresponding reference standard segmentations of polycystic kidneys. In the study of PKD, segmentation of the kidneys is needed in order to measure total kidney volume (TKV). Automated methods to segment the kidneys and measure TKV are needed to increase measurement throughput and alleviate the inherent variability of human-derived measurements. We hypothesize that deep learning techniques can be leveraged to perform fast, accurate, reproducible, and fully automated segmentation of polycystic kidneys. Here, we describe a fully automated approach for segmenting PKD kidneys within MR images that simulates a multi-observer approach in order to create an accurate and robust method for the task of segmentation and computation of TKV for PKD patients. A total of 2000 cases were used for training and validation, and 400 cases were used for testing. The multi-observer ensemble method had mean ± SD percent volume difference of 0.68 ± 2.2% compared with the reference standard segmentations. The complete framework performs fully automated segmentation at a level comparable with interobserver variability and could be considered as a replacement for the task of segmentation of PKD kidneys by a human.

  1. Segmenting overlapping nano-objects in atomic force microscopy image

    Science.gov (United States)

    Wang, Qian; Han, Yuexing; Li, Qing; Wang, Bing; Konagaya, Akihiko

    2018-01-01

    Recently, techniques for nanoparticles have rapidly been developed for various fields, such as material science, medical, and biology. In particular, methods of image processing have widely been used to automatically analyze nanoparticles. A technique to automatically segment overlapping nanoparticles with image processing and machine learning is proposed. Here, two tasks are necessary: elimination of image noises and action of the overlapping shapes. For the first task, mean square error and the seed fill algorithm are adopted to remove noises and improve the quality of the original image. For the second task, four steps are needed to segment the overlapping nanoparticles. First, possibility split lines are obtained by connecting the high curvature pixels on the contours. Second, the candidate split lines are classified with a machine learning algorithm. Third, the overlapping regions are detected with the method of density-based spatial clustering of applications with noise (DBSCAN). Finally, the best split lines are selected with a constrained minimum value. We give some experimental examples and compare our technique with two other methods. The results can show the effectiveness of the proposed technique.

  2. Sipunculans and segmentation

    DEFF Research Database (Denmark)

    Wanninger, Andreas; Kristof, Alen; Brinkmann, Nora

    2009-01-01

    mechanisms may act on the level of gene expression, cell proliferation, tissue differentiation and organ system formation in individual segments. Accordingly, in some polychaete annelids the first three pairs of segmental peripheral neurons arise synchronously, while the metameric commissures of the ventral...

  3. Rapid analysis and exploration of fluorescence microscopy images.

    Science.gov (United States)

    Pavie, Benjamin; Rajaram, Satwik; Ouyang, Austin; Altschuler, Jason M; Steininger, Robert J; Wu, Lani F; Altschuler, Steven J

    2014-03-19

    Despite rapid advances in high-throughput microscopy, quantitative image-based assays still pose significant challenges. While a variety of specialized image analysis tools are available, most traditional image-analysis-based workflows have steep learning curves (for fine tuning of analysis parameters) and result in long turnaround times between imaging and analysis. In particular, cell segmentation, the process of identifying individual cells in an image, is a major bottleneck in this regard. Here we present an alternate, cell-segmentation-free workflow based on PhenoRipper, an open-source software platform designed for the rapid analysis and exploration of microscopy images. The pipeline presented here is optimized for immunofluorescence microscopy images of cell cultures and requires minimal user intervention. Within half an hour, PhenoRipper can analyze data from a typical 96-well experiment and generate image profiles. Users can then visually explore their data, perform quality control on their experiment, ensure response to perturbations and check reproducibility of replicates. This facilitates a rapid feedback cycle between analysis and experiment, which is crucial during assay optimization. This protocol is useful not just as a first pass analysis for quality control, but also may be used as an end-to-end solution, especially for screening. The workflow described here scales to large data sets such as those generated by high-throughput screens, and has been shown to group experimental conditions by phenotype accurately over a wide range of biological systems. The PhenoBrowser interface provides an intuitive framework to explore the phenotypic space and relate image properties to biological annotations. Taken together, the protocol described here will lower the barriers to adopting quantitative analysis of image based screens.

  4. Using Predictability for Lexical Segmentation.

    Science.gov (United States)

    Çöltekin, Çağrı

    2017-09-01

    This study investigates a strategy based on predictability of consecutive sub-lexical units in learning to segment a continuous speech stream into lexical units using computational modeling and simulations. Lexical segmentation is one of the early challenges during language acquisition, and it has been studied extensively through psycholinguistic experiments as well as computational methods. However, despite strong empirical evidence, the explicit use of predictability of basic sub-lexical units in models of segmentation is underexplored. This paper presents an incremental computational model of lexical segmentation for exploring the usefulness of predictability for lexical segmentation. We show that the predictability cue is a strong cue for segmentation. Contrary to earlier reports in the literature, the strategy yields state-of-the-art segmentation performance with an incremental computational model that uses only this particular cue in a cognitively plausible setting. The paper also reports an in-depth analysis of the model, investigating the conditions affecting the usefulness of the strategy. Copyright © 2016 Cognitive Science Society, Inc.

  5. Efficient graph-cut tattoo segmentation

    Science.gov (United States)

    Kim, Joonsoo; Parra, Albert; Li, He; Delp, Edward J.

    2015-03-01

    Law enforcement is interested in exploiting tattoos as an information source to identify, track and prevent gang-related crimes. Many tattoo image retrieval systems have been described. In a retrieval system tattoo segmentation is an important step for retrieval accuracy since segmentation removes background information in a tattoo image. Existing segmentation methods do not extract the tattoo very well when the background includes textures and color similar to skin tones. In this paper we describe a tattoo segmentation approach by determining skin pixels in regions near the tattoo. In these regions graph-cut segmentation using a skin color model and a visual saliency map is used to find skin pixels. After segmentation we determine which set of skin pixels are connected with each other that form a closed contour including a tattoo. The regions surrounded by the closed contours are considered tattoo regions. Our method segments tattoos well when the background includes textures and color similar to skin.

  6. A 2D driven 3D vessel segmentation algorithm for 3D digital subtraction angiography data

    International Nuclear Information System (INIS)

    Spiegel, M; Hornegger, J; Redel, T; Struffert, T; Doerfler, A

    2011-01-01

    Cerebrovascular disease is among the leading causes of death in western industrial nations. 3D rotational angiography delivers indispensable information on vessel morphology and pathology. Physicians make use of this to analyze vessel geometry in detail, i.e. vessel diameters, location and size of aneurysms, to come up with a clinical decision. 3D segmentation is a crucial step in this pipeline. Although a lot of different methods are available nowadays, all of them lack a method to validate the results for the individual patient. Therefore, we propose a novel 2D digital subtraction angiography (DSA)-driven 3D vessel segmentation and validation framework. 2D DSA projections are clinically considered as gold standard when it comes to measurements of vessel diameter or the neck size of aneurysms. An ellipsoid vessel model is applied to deliver the initial 3D segmentation. To assess the accuracy of the 3D vessel segmentation, its forward projections are iteratively overlaid with the corresponding 2D DSA projections. Local vessel discrepancies are modeled by a global 2D/3D optimization function to adjust the 3D vessel segmentation toward the 2D vessel contours. Our framework has been evaluated on phantom data as well as on ten patient datasets. Three 2D DSA projections from varying viewing angles have been used for each dataset. The novel 2D driven 3D vessel segmentation approach shows superior results against state-of-the-art segmentations like region growing, i.e. an improvement of 7.2% points in precision and 5.8% points for the Dice coefficient. This method opens up future clinical applications requiring the greatest vessel accuracy, e.g. computational fluid dynamic modeling.

  7. What are the visual features underlying rapid object recognition?

    Directory of Open Access Journals (Sweden)

    Sébastien M Crouzet

    2011-11-01

    Full Text Available Research progress in machine vision has been very significant in recent years. Robust face detection and identification algorithms are already readily available to consumers, and modern computer vision algorithms for generic object recognition are now coping with the richness and complexity of natural visual scenes. Unlike early vision models of object recognition that emphasized the role of figure-ground segmentation and spatial information between parts, recent successful approaches are based on the computation of loose collections of image features without prior segmentation or any explicit encoding of spatial relations. While these models remain simplistic models of visual processing, they suggest that, in principle, bottom-up activation of a loose collection of image features could support the rapid recognition of natural object categories and provide an initial coarse visual representation before more complex visual routines and attentional mechanisms take place. Focusing on biologically-plausible computational models of (bottom-up pre-attentive visual recognition, we review some of the key visual features that have been described in the literature. We discuss the consistency of these feature-based representations with classical theories from visual psychology and test their ability to account for human performance on a rapid object categorization task.

  8. Rapid Detection of the Varicella Zoster Virus

    Science.gov (United States)

    Lewis, Michelle P.; Harding, Robert

    2011-01-01

    1.Technology Description-Researchers discovered that when the Varicella Zoster Virus (VZV) reactivates from latency in the body, the virus is consistently present in saliva before the appearance of skin lesions. A small saliva sample is mixed with a specialized reagent in a test kit. If the virus is present in the saliva sample, the mixture turns a red color. The sensitivity and specificity emanates from an antibody-antigen reaction. This technology is a rapid, non-invasive, point of-of-care testing kit for detecting the virus from a saliva sample. The device is easy to use and can be used in clinics and in remote locations to quickly detect VZV and begin treatment with antiviral drugs. 2.Market Opportunity- RST Bioscience will be the first and only company to market a rapid, same day test kit for the detection of VZV in saliva. The RST detection test kit will have several advantages over existing, competitive technology. The test kit is self contained and laboratory equipment is not required for analysis of the sample. Only a single saliva sample is required to be taken instead of blood or cerebral spinal fluid. The test kit is portable, sterile and disposable after use. RST detection test kits require no electrical power or expensive storage equipment and can be used in remote locations. 3.Market Analysis- According to the CDC, it is estimated that 1 million cases of shingles occur each year in the U.S. with more than half over the age of sixty. There is a high demand for rapid diagnostics by the public. The point-of-care testing (POCT) market is growing faster than other segments of in vitro diagnostics. According to a July 2007 InteLab Corporation industry report the overall market for POCT was forecast to increase from $10.3 billion in 2005 to $18.7 billion by 2011. The market value of this test kit has not been determined. 4.Competition- The VZV vaccine prevents 50% of cases and reduces neuralgia by 66%. The most popular test detects VZV-specific IgM antibody

  9. Microscopy Image Browser: A Platform for Segmentation and Analysis of Multidimensional Datasets.

    Directory of Open Access Journals (Sweden)

    Ilya Belevich

    2016-01-01

    Full Text Available Understanding the structure-function relationship of cells and organelles in their natural context requires multidimensional imaging. As techniques for multimodal 3-D imaging have become more accessible, effective processing, visualization, and analysis of large datasets are posing a bottleneck for the workflow. Here, we present a new software package for high-performance segmentation and image processing of multidimensional datasets that improves and facilitates the full utilization and quantitative analysis of acquired data, which is freely available from a dedicated website. The open-source environment enables modification and insertion of new plug-ins to customize the program for specific needs. We provide practical examples of program features used for processing, segmentation and analysis of light and electron microscopy datasets, and detailed tutorials to enable users to rapidly and thoroughly learn how to use the program.

  10. Fold distributions at clover, crystal and segment levels for segmented clover detectors

    International Nuclear Information System (INIS)

    Kshetri, R; Bhattacharya, P

    2014-01-01

    Fold distributions at clover, crystal and segment levels have been extracted for an array of segmented clover detectors for various gamma energies. A simple analysis of the results based on a model independant approach has been presented. For the first time, the clover fold distribution of an array and associated array addback factor have been extracted. We have calculated the percentages of the number of crystals and segments that fire for a full energy peak event

  11. Optical Coherence Tomography in the UK Biobank Study - Rapid Automated Analysis of Retinal Thickness for Large Population-Based Studies.

    Directory of Open Access Journals (Sweden)

    Pearse A Keane

    Full Text Available To describe an approach to the use of optical coherence tomography (OCT imaging in large, population-based studies, including methods for OCT image acquisition, storage, and the remote, rapid, automated analysis of retinal thickness.In UK Biobank, OCT images were acquired between 2009 and 2010 using a commercially available "spectral domain" OCT device (3D OCT-1000, Topcon. Images were obtained using a raster scan protocol, 6 mm x 6 mm in area, and consisting of 128 B-scans. OCT image sets were stored on UK Biobank servers in a central repository, adjacent to high performance computers. Rapid, automated analysis of retinal thickness was performed using custom image segmentation software developed by the Topcon Advanced Biomedical Imaging Laboratory (TABIL. This software employs dual-scale gradient information to allow for automated segmentation of nine intraretinal boundaries in a rapid fashion.67,321 participants (134,642 eyes in UK Biobank underwent OCT imaging of both eyes as part of the ocular module. 134,611 images were successfully processed with 31 images failing segmentation analysis due to corrupted OCT files or withdrawal of subject consent for UKBB study participation. Average time taken to call up an image from the database and complete segmentation analysis was approximately 120 seconds per data set per login, and analysis of the entire dataset was completed in approximately 28 days.We report an approach to the rapid, automated measurement of retinal thickness from nearly 140,000 OCT image sets from the UK Biobank. In the near future, these measurements will be publically available for utilization by researchers around the world, and thus for correlation with the wealth of other data collected in UK Biobank. The automated analysis approaches we describe may be of utility for future large population-based epidemiological studies, clinical trials, and screening programs that employ OCT imaging.

  12. Intercalary bone segment transport in treatment of segmental tibial defects

    International Nuclear Information System (INIS)

    Iqbal, A.; Amin, M.S.

    2002-01-01

    Objective: To evaluate the results and complications of intercalary bone segment transport in the treatment of segmental tibial defects. Design: This is a retrospective analysis of patients with segmental tibial defects who were treated with intercalary bone segment transport method. Place and Duration of Study: The study was carried out at Combined Military Hospital, Rawalpindi from September 1997 to April 2001. Subjects and methods: Thirteen patients were included in the study who had developed tibial defects either due to open fractures with bone loss or subsequent to bone debridement of infected non unions. The mean bone defect was 6.4 cms and there were eight associated soft tissue defects. Locally made unilateral 'Naseer-Awais' (NA) fixator was used for bone segment transport. The distraction was done at the rate of 1mm/day after 7-10 days of osteotomy. The patients were followed-up fortnightly during distraction and monthly thereafter. The mean follow-up duration was 18 months. Results: The mean time in external fixation was 9.4 months. The m ean healing index' was 1.47 months/cm. Satisfactory union was achieved in all cases. Six cases (46.2%) required bone grafting at target site and in one of them grafting was required at the level of regeneration as well. All the wounds healed well with no residual infection. There was no residual leg length discrepancy of more than 20 mm nd one angular deformity of more than 5 degrees. The commonest complication encountered was pin track infection seen in 38% of Shanz Screws applied. Loosening occurred in 6.8% of Shanz screws, requiring re-adjustment. Ankle joint contracture with equinus deformity and peroneal nerve paresis occurred in one case each. The functional results were graded as 'good' in seven, 'fair' in four, and 'poor' in two patients. Overall, thirteen patients had 31 (minor/major) complications with a ratio of 2.38 complications per patient. To treat the bone defects and associated complications, a mean of

  13. Fast and Robust Segmentation and Classification for Change Detection in Urban Point Clouds

    Science.gov (United States)

    Roynard, X.; Deschaud, J.-E.; Goulette, F.

    2016-06-01

    Change detection is an important issue in city monitoring to analyse street furniture, road works, car parking, etc. For example, parking surveys are needed but are currently a laborious task involving sending operators in the streets to identify the changes in car locations. In this paper, we propose a method that performs a fast and robust segmentation and classification of urban point clouds, that can be used for change detection. We apply this method to detect the cars, as a particular object class, in order to perform parking surveys automatically. A recently proposed method already addresses the need for fast segmentation and classification of urban point clouds, using elevation images. The interest to work on images is that processing is much faster, proven and robust. However there may be a loss of information in complex 3D cases: for example when objects are one above the other, typically a car under a tree or a pedestrian under a balcony. In this paper we propose a method that retain the three-dimensional information while preserving fast computation times and improving segmentation and classification accuracy. It is based on fast region-growing using an octree, for the segmentation, and specific descriptors with Random-Forest for the classification. Experiments have been performed on large urban point clouds acquired by Mobile Laser Scanning. They show that the method is as fast as the state of the art, and that it gives more robust results in the complex 3D cases.

  14. Market segmentation in behavioral perspective.

    OpenAIRE

    Wells, V.K.; Chang, S.W.; Oliveira-Castro, J.M.; Pallister, J.

    2010-01-01

    A segmentation approach is presented using both traditional demographic segmentation bases (age, social class/occupation, and working status) and a segmentation by benefits sought. The benefits sought in this case are utilitarian and informational reinforcement, variables developed from the Behavioral Perspective Model (BPM). Using data from 1,847 consumers and from a total of 76,682 individual purchases, brand choice and price and reinforcement responsiveness were assessed for each segment a...

  15. Noise destroys feedback enhanced figure-ground segmentation but not feedforward figure-ground segmentation

    Science.gov (United States)

    Romeo, August; Arall, Marina; Supèr, Hans

    2012-01-01

    Figure-ground (FG) segmentation is the separation of visual information into background and foreground objects. In the visual cortex, FG responses are observed in the late stimulus response period, when neurons fire in tonic mode, and are accompanied by a switch in cortical state. When such a switch does not occur, FG segmentation fails. Currently, it is not known what happens in the brain on such occasions. A biologically plausible feedforward spiking neuron model was previously devised that performed FG segmentation successfully. After incorporating feedback the FG signal was enhanced, which was accompanied by a change in spiking regime. In a feedforward model neurons respond in a bursting mode whereas in the feedback model neurons fired in tonic mode. It is known that bursts can overcome noise, while tonic firing appears to be much more sensitive to noise. In the present study, we try to elucidate how the presence of noise can impair FG segmentation, and to what extent the feedforward and feedback pathways can overcome noise. We show that noise specifically destroys the feedback enhanced FG segmentation and leaves the feedforward FG segmentation largely intact. Our results predict that noise produces failure in FG perception. PMID:22934028

  16. Segment density profiles of polyelectrolyte brushes determined by Fourier transform ellipsometry

    Science.gov (United States)

    Biesalski, Markus; Rühe, Jürgen; Johannsmann, Diethelm

    1999-10-01

    We describe a method for the explicit determination of the segment density profile φ(z) of surface-attached polymer brushes with multiple angle of incidence null-ellipsometry. Because the refractive index contrast between the brush layer and the solvent is weak, multiple reflections are of minor influence and the ellipsometric spectrum is closely related to the Fourier transform of the refractive index profile, thereby allowing for explicit inversion of the ellipsometric data. We chose surface-attached monolayers of polymethacrylic acid (PMAA), a weak polyelectrolyte, as a model system and determined the segment density profile of this system as a function of the pH value of the surrounding medium by the Fourier method. Complementary to the Fourier analysis, fits with error functions are given as well. The brushes were prepared on the bases of high refractive index prisms with the "grafting-from" technique. In water, the brushes swell by more than a factor of 30. The swelling increases with increasing pH because of a growing fraction of dissociated acidic groups leading to a larger electrostatic repulsion.

  17. ADVANCED CLUSTER BASED IMAGE SEGMENTATION

    Directory of Open Access Journals (Sweden)

    D. Kesavaraja

    2011-11-01

    Full Text Available This paper presents efficient and portable implementations of a useful image segmentation technique which makes use of the faster and a variant of the conventional connected components algorithm which we call parallel Components. In the Modern world majority of the doctors are need image segmentation as the service for various purposes and also they expect this system is run faster and secure. Usually Image segmentation Algorithms are not working faster. In spite of several ongoing researches in Conventional Segmentation and its Algorithms might not be able to run faster. So we propose a cluster computing environment for parallel image Segmentation to provide faster result. This paper is the real time implementation of Distributed Image Segmentation in Clustering of Nodes. We demonstrate the effectiveness and feasibility of our method on a set of Medical CT Scan Images. Our general framework is a single address space, distributed memory programming model. We use efficient techniques for distributing and coalescing data as well as efficient combinations of task and data parallelism. The image segmentation algorithm makes use of an efficient cluster process which uses a novel approach for parallel merging. Our experimental results are consistent with the theoretical analysis and practical results. It provides the faster execution time for segmentation, when compared with Conventional method. Our test data is different CT scan images from the Medical database. More efficient implementations of Image Segmentation will likely result in even faster execution times.

  18. Liver segmentation in contrast enhanced CT data using graph cuts and interactive 3D segmentation refinement methods

    Energy Technology Data Exchange (ETDEWEB)

    Beichel, Reinhard; Bornik, Alexander; Bauer, Christian; Sorantin, Erich [Departments of Electrical and Computer Engineering and Internal Medicine, Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, Iowa 52242 (United States); Institute for Computer Graphics and Vision, Graz University of Technology, Inffeldgasse 16, A-8010 Graz (Austria); Department of Electrical and Computer Engineering, Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, Iowa 52242 (United States); Department of Radiology, Medical University Graz, Auenbruggerplatz 34, A-8010 Graz (Austria)

    2012-03-15

    Purpose: Liver segmentation is an important prerequisite for the assessment of liver cancer treatment options like tumor resection, image-guided radiation therapy (IGRT), radiofrequency ablation, etc. The purpose of this work was to evaluate a new approach for liver segmentation. Methods: A graph cuts segmentation method was combined with a three-dimensional virtual reality based segmentation refinement approach. The developed interactive segmentation system allowed the user to manipulate volume chunks and/or surfaces instead of 2D contours in cross-sectional images (i.e, slice-by-slice). The method was evaluated on twenty routinely acquired portal-phase contrast enhanced multislice computed tomography (CT) data sets. An independent reference was generated by utilizing a currently clinically utilized slice-by-slice segmentation method. After 1 h of introduction to the developed segmentation system, three experts were asked to segment all twenty data sets with the proposed method. Results: Compared to the independent standard, the relative volumetric segmentation overlap error averaged over all three experts and all twenty data sets was 3.74%. Liver segmentation required on average 16 min of user interaction per case. The calculated relative volumetric overlap errors were not found to be significantly different [analysis of variance (ANOVA) test, p = 0.82] between experts who utilized the proposed 3D system. In contrast, the time required by each expert for segmentation was found to be significantly different (ANOVA test, p = 0.0009). Major differences between generated segmentations and independent references were observed in areas were vessels enter or leave the liver and no accepted criteria for defining liver boundaries exist. In comparison, slice-by-slice based generation of the independent standard utilizing a live wire tool took 70.1 min on average. A standard 2D segmentation refinement approach applied to all twenty data sets required on average 38.2 min of

  19. Liver segmentation in contrast enhanced CT data using graph cuts and interactive 3D segmentation refinement methods

    International Nuclear Information System (INIS)

    Beichel, Reinhard; Bornik, Alexander; Bauer, Christian; Sorantin, Erich

    2012-01-01

    Purpose: Liver segmentation is an important prerequisite for the assessment of liver cancer treatment options like tumor resection, image-guided radiation therapy (IGRT), radiofrequency ablation, etc. The purpose of this work was to evaluate a new approach for liver segmentation. Methods: A graph cuts segmentation method was combined with a three-dimensional virtual reality based segmentation refinement approach. The developed interactive segmentation system allowed the user to manipulate volume chunks and/or surfaces instead of 2D contours in cross-sectional images (i.e, slice-by-slice). The method was evaluated on twenty routinely acquired portal-phase contrast enhanced multislice computed tomography (CT) data sets. An independent reference was generated by utilizing a currently clinically utilized slice-by-slice segmentation method. After 1 h of introduction to the developed segmentation system, three experts were asked to segment all twenty data sets with the proposed method. Results: Compared to the independent standard, the relative volumetric segmentation overlap error averaged over all three experts and all twenty data sets was 3.74%. Liver segmentation required on average 16 min of user interaction per case. The calculated relative volumetric overlap errors were not found to be significantly different [analysis of variance (ANOVA) test, p = 0.82] between experts who utilized the proposed 3D system. In contrast, the time required by each expert for segmentation was found to be significantly different (ANOVA test, p = 0.0009). Major differences between generated segmentations and independent references were observed in areas were vessels enter or leave the liver and no accepted criteria for defining liver boundaries exist. In comparison, slice-by-slice based generation of the independent standard utilizing a live wire tool took 70.1 min on average. A standard 2D segmentation refinement approach applied to all twenty data sets required on average 38.2 min of

  20. Liver segmentation in contrast enhanced CT data using graph cuts and interactive 3D segmentation refinement methods.

    Science.gov (United States)

    Beichel, Reinhard; Bornik, Alexander; Bauer, Christian; Sorantin, Erich

    2012-03-01

    Liver segmentation is an important prerequisite for the assessment of liver cancer treatment options like tumor resection, image-guided radiation therapy (IGRT), radiofrequency ablation, etc. The purpose of this work was to evaluate a new approach for liver segmentation. A graph cuts segmentation method was combined with a three-dimensional virtual reality based segmentation refinement approach. The developed interactive segmentation system allowed the user to manipulate volume chunks and∕or surfaces instead of 2D contours in cross-sectional images (i.e, slice-by-slice). The method was evaluated on twenty routinely acquired portal-phase contrast enhanced multislice computed tomography (CT) data sets. An independent reference was generated by utilizing a currently clinically utilized slice-by-slice segmentation method. After 1 h of introduction to the developed segmentation system, three experts were asked to segment all twenty data sets with the proposed method. Compared to the independent standard, the relative volumetric segmentation overlap error averaged over all three experts and all twenty data sets was 3.74%. Liver segmentation required on average 16 min of user interaction per case. The calculated relative volumetric overlap errors were not found to be significantly different [analysis of variance (ANOVA) test, p = 0.82] between experts who utilized the proposed 3D system. In contrast, the time required by each expert for segmentation was found to be significantly different (ANOVA test, p = 0.0009). Major differences between generated segmentations and independent references were observed in areas were vessels enter or leave the liver and no accepted criteria for defining liver boundaries exist. In comparison, slice-by-slice based generation of the independent standard utilizing a live wire tool took 70.1 min on average. A standard 2D segmentation refinement approach applied to all twenty data sets required on average 38.2 min of user interaction

  1. Cluster Ensemble-Based Image Segmentation

    Directory of Open Access Journals (Sweden)

    Xiaoru Wang

    2013-07-01

    Full Text Available Image segmentation is the foundation of computer vision applications. In this paper, we propose a new cluster ensemble-based image segmentation algorithm, which overcomes several problems of traditional methods. We make two main contributions in this paper. First, we introduce the cluster ensemble concept to fuse the segmentation results from different types of visual features effectively, which can deliver a better final result and achieve a much more stable performance for broad categories of images. Second, we exploit the PageRank idea from Internet applications and apply it to the image segmentation task. This can improve the final segmentation results by combining the spatial information of the image and the semantic similarity of regions. Our experiments on four public image databases validate the superiority of our algorithm over conventional single type of feature or multiple types of features-based algorithms, since our algorithm can fuse multiple types of features effectively for better segmentation results. Moreover, our method is also proved to be very competitive in comparison with other state-of-the-art segmentation algorithms.

  2. A multi-segment soft actuator for biomedical applications based on IPMCs

    Science.gov (United States)

    Zhao, Dongxu; Wang, Yanjie; Liu, Jiayu; Luo, Meng; Li, Dichen; Chen, Hualing

    2015-04-01

    With rapid progress of biomedical devices towards miniaturization, flexibility, multifunction and low cost, the restrictions of traditional mechanical structures become particularly apparent, while soft materials become research focus in broad fields. As one of the most attractive soft materials, Ionic Polymer-Metal Composite (IPMC) is widely used as artificial muscles and actuators, with the advantages of low driving-voltage, high efficiency of electromechanical transduction and functional stabilization. In this paper, a new intuitive control method was presented to achieve the omnidirectional bending movements and was applied on a representative actuation structure of a multi-degree-offreedom soft actuator composed of two segments bar-shaped IPMC with a square cross section. Firstly, the bar-shaped IPMCs were fabricated by the solution casting method, reducing plating, autocatalytic plating method and cut into shapes successively. The connectors of the multi-segment IPMC actuator were fabricated by 3D printing. Then, a new control method was introduced to realize the intuitive mapping relationship between the actuator and the joystick manipulator. The control circuit was designed and tested. Finally, the multi-degree-of-freedom actuator of 2 segments bar-shaped IPMCs was implemented and omnidirectional bending movements were achieved, which could be a promising actuator for biomedical applications, such as endoscope, catheterism, laparoscopy and the surgical resection of tumors.

  3. Albedo estimation for scene segmentation

    Energy Technology Data Exchange (ETDEWEB)

    Lee, C H; Rosenfeld, A

    1983-03-01

    Standard methods of image segmentation do not take into account the three-dimensional nature of the underlying scene. For example, histogram-based segmentation tacitly assumes that the image intensity is piecewise constant, and this is not true when the scene contains curved surfaces. This paper introduces a method of taking 3d information into account in the segmentation process. The image intensities are adjusted to compensate for the effects of estimated surface orientation; the adjusted intensities can be regarded as reflectivity estimates. When histogram-based segmentation is applied to these new values, the image is segmented into parts corresponding to surfaces of constant reflectivity in the scene. 7 references.

  4. Rapid changes in protein phosphorylation associated with gravity perception in corn roots

    International Nuclear Information System (INIS)

    McFadden, J.J.; Poovaiah, B.W.

    1987-01-01

    A previous paper from this laboratory showed calcium- and calmodulin-dependent in vivo protein phosphorylation in corn root tips. The authors show that rapid changes in calcium-dependent protein phosphorylation are involved in light-dependent graviperception in corn root tips. Corn seedlings (Zea mays L, cv Merit) were grown in the dark for 3 d, then apical root segments were harvested in dim green light to measure in vivo protein phosphorylation. Segments were incubated with 0.5 mCi 32 P for 1 h, then immediately frozen in liquid N 2 or first treated with either 7 min light, or 7 min light plus 1 mM EGTA and 10 μM A23187. Labeled proteins were separated by 2D gel electrophoresis and detected by autoradiography. Light caused rapid and specific promotion of phosphorylation of 5 polypeptides. The increases in protein phosphorylation were reversed by treating with EGTA and A23187. The authors postulate that these changes in protein phosphorylation are an essential part of the light-dependent gravity response in Merit roots

  5. Proceedings of the Canadian Institute's 4. annual oil sands supply and infrastructure conference : maximizing opportunity and mitigating risks in a rapidly growing market

    International Nuclear Information System (INIS)

    2006-01-01

    This conference addressed the challenges facing oil sands development, with particular reference to supply and infrastructure issues. Updates on oil sands markets and opportunities were presented along with strategies for mitigating risks in a rapidly growing market. The best practices for supplying a demanding market through supply shortages and high prices were identified along with policies that should be implemented to help overcome labour shortages. Some presentations expressed how commodities pricing and trends can impact business. Others showed how markets in China and the United States are prepared for oilsands products. The views of other international companies on oil sands was also discussed along with proposed plans to eliminate the infrastructure congestion and risks caused by expanding oil sands development. The challenges and benefits of investing in Alberta's oil sands were reviewed along with strategies to enhance upgrading and refining capacity in the province. Economic drivers and the creation of new markets were examined, and various export opportunities were reviewed along with industry management challenges concerning human resources, labour supply, training and education. The conference featured 10 presentations, of which 3 have been catalogued separately for inclusion in this database. refs., tabs., figs

  6. Automated temporal tracking and segmentation of lymphoma on serial CT examinations

    Energy Technology Data Exchange (ETDEWEB)

    Xu Jiajing; Greenspan, Hayit; Napel, Sandy; Rubin, Daniel L. [Department of Electrical Engineering, Stanford University, Stanford, California 94305 (United States); Department of Biomedical Engineering, Tel Aviv University, Tel Aviv, 69978 (Israel); Department of Electrical Engineering, Stanford University, Stanford, California 94305 and Department of Radiology, Stanford University, Stanford, California 94305 (United States); Department of Radiology, Stanford University, Stanford, California 94305 (United States)

    2011-11-15

    Purpose: It is challenging to reproducibly measure and compare cancer lesions on numerous follow-up studies; the process is time-consuming and error-prone. In this paper, we show a method to automatically and reproducibly identify and segment abnormal lymph nodes in serial computed tomography (CT) exams. Methods: Our method leverages initial identification of enlarged (abnormal) lymph nodes in the baseline scan. We then identify an approximate region for the node in the follow-up scans using nonrigid image registration. The baseline scan is also used to locate regions of normal, non-nodal tissue surrounding the lymph node and to map them onto the follow-up scans, in order to reduce the search space to locate the lymph node on the follow-up scans. Adaptive region-growing and clustering algorithms are then used to obtain the final contours for segmentation. We applied our method to 24 distinct enlarged lymph nodes at multiple time points from 14 patients. The scan at the earlier time point was used as the baseline scan to be used in evaluating the follow-up scan, resulting in 70 total test cases (e.g., a series of scans obtained at 4 time points results in 3 test cases). For each of the 70 cases, a ''reference standard'' was obtained by manual segmentation by a radiologist. Assessment according to response evaluation criteria in solid tumors (RECIST) using our method agreed with RECIST assessments made using the reference standard segmentations in all test cases, and by calculating node overlap ratio and Hausdorff distance between the computer and radiologist-generated contours. Results: Compared to the reference standard, our method made the correct RECIST assessment for all 70 cases. The average overlap ratio was 80.7 {+-} 9.7% s.d., and the average Hausdorff distance was 3.2 {+-} 1.8 mm s.d. The concordance correlation between automated and manual segmentations was 0.978 (95% confidence interval 0.962, 0.984). The 100% agreement in our sample

  7. Segmenting the Adult Education Market.

    Science.gov (United States)

    Aurand, Tim

    1994-01-01

    Describes market segmentation and how the principles of segmentation can be applied to the adult education market. Indicates that applying segmentation techniques to adult education programs results in programs that are educationally and financially satisfying and serve an appropriate population. (JOW)

  8. Gamifying Video Object Segmentation.

    Science.gov (United States)

    Spampinato, Concetto; Palazzo, Simone; Giordano, Daniela

    2017-10-01

    Video object segmentation can be considered as one of the most challenging computer vision problems. Indeed, so far, no existing solution is able to effectively deal with the peculiarities of real-world videos, especially in cases of articulated motion and object occlusions; limitations that appear more evident when we compare the performance of automated methods with the human one. However, manually segmenting objects in videos is largely impractical as it requires a lot of time and concentration. To address this problem, in this paper we propose an interactive video object segmentation method, which exploits, on one hand, the capability of humans to identify correctly objects in visual scenes, and on the other hand, the collective human brainpower to solve challenging and large-scale tasks. In particular, our method relies on a game with a purpose to collect human inputs on object locations, followed by an accurate segmentation phase achieved by optimizing an energy function encoding spatial and temporal constraints between object regions as well as human-provided location priors. Performance analysis carried out on complex video benchmarks, and exploiting data provided by over 60 users, demonstrated that our method shows a better trade-off between annotation times and segmentation accuracy than interactive video annotation and automated video object segmentation approaches.

  9. Automatic speech signal segmentation based on the innovation adaptive filter

    Directory of Open Access Journals (Sweden)

    Makowski Ryszard

    2014-06-01

    Full Text Available Speech segmentation is an essential stage in designing automatic speech recognition systems and one can find several algorithms proposed in the literature. It is a difficult problem, as speech is immensely variable. The aim of the authors’ studies was to design an algorithm that could be employed at the stage of automatic speech recognition. This would make it possible to avoid some problems related to speech signal parametrization. Posing the problem in such a way requires the algorithm to be capable of working in real time. The only such algorithm was proposed by Tyagi et al., (2006, and it is a modified version of Brandt’s algorithm. The article presents a new algorithm for unsupervised automatic speech signal segmentation. It performs segmentation without access to information about the phonetic content of the utterances, relying exclusively on second-order statistics of a speech signal. The starting point for the proposed method is time-varying Schur coefficients of an innovation adaptive filter. The Schur algorithm is known to be fast, precise, stable and capable of rapidly tracking changes in second order signal statistics. A transfer from one phoneme to another in the speech signal always indicates a change in signal statistics caused by vocal track changes. In order to allow for the properties of human hearing, detection of inter-phoneme boundaries is performed based on statistics defined on the mel spectrum determined from the reflection coefficients. The paper presents the structure of the algorithm, defines its properties, lists parameter values, describes detection efficiency results, and compares them with those for another algorithm. The obtained segmentation results, are satisfactory.

  10. Object-Based Change Detection in Urban Areas: The Effects of Segmentation Strategy, Scale, and Feature Space on Unsupervised Methods

    Directory of Open Access Journals (Sweden)

    Lei Ma

    2016-09-01

    Full Text Available Object-based change detection (OBCD has recently been receiving increasing attention as a result of rapid improvements in the resolution of remote sensing data. However, some OBCD issues relating to the segmentation of high-resolution images remain to be explored. For example, segmentation units derived using different segmentation strategies, segmentation scales, feature space, and change detection methods have rarely been assessed. In this study, we have tested four common unsupervised change detection methods using different segmentation strategies and a series of segmentation scale parameters on two WorldView-2 images of urban areas. We have also evaluated the effect of adding extra textural and Normalized Difference Vegetation Index (NDVI information instead of using only spectral information. Our results indicated that change detection methods performed better at a medium scale than at a fine scale where close to the pixel size. Multivariate Alteration Detection (MAD always outperformed the other methods tested, at the same confidence level. The overall accuracy appeared to benefit from using a two-date segmentation strategy rather than single-date segmentation. Adding textural and NDVI information appeared to reduce detection accuracy, but the magnitude of this reduction was not consistent across the different unsupervised methods and segmentation strategies. We conclude that a two-date segmentation strategy is useful for change detection in high-resolution imagery, but that the optimization of thresholds is critical for unsupervised change detection methods. Advanced methods need be explored that can take advantage of additional textural or other parameters.

  11. Microbial transmutation of 137Cs and LENR in growing biological systems

    International Nuclear Information System (INIS)

    Vysotskii, V.I.; Kornilova, A.A.

    2015-01-01

    This article presents the results of long-term investigations of stable and radioactive isotopes transmutation in growing microbiological cultures. It is shown that transmutation during growth of microbiological associations is 20 times more effective than the same process in the form of 'clean' microbiological culture. In this work, the process of controlled decontamination of highly active reactor isotopes (reactor waste) through the process of growing microbiological associations has been studied. The most rapidly increasing decay rate of 137 Cs isotope, which occurred with the 'effective' half life τ* ≈ 310 days (involving an increase in rate and decrease in half life by a factor of 35) was observed in the presence of Ca salt in closed flask with active water containing 137 Cs solution and optimal microbiological association. (author)

  12. U.S. Army Custom Segmentation System

    Science.gov (United States)

    2007-06-01

    segmentation is individual or intergroup differences in response to marketing - mix variables. Presumptions about segments: •different demands in a...product or service category, •respond differently to changes in the marketing mix Criteria for segments: •The segments must exist in the environment

  13. Automatic MPST-cut for segmentation of carpal bones from MR volumes.

    Science.gov (United States)

    Gemme, Laura; Nardotto, Sonia; Dellepiane, Silvana G

    2017-08-01

    In the context of rheumatic diseases, several studies suggest that Magnetic Resonance Imaging (MRI) allows the detection of the three main signs of Rheumatoid Arthritis (RA) at higher sensitivities than available through conventional radiology. The rapid, accurate segmentation of bones is an essential preliminary step for quantitative diagnosis, erosion evaluation, and multi-temporal data fusion. In the present paper, a new, semi-automatic, 3D graph-based segmentation method to extract carpal bone data is proposed. The method is unsupervised, does not employ any a priori model or knowledge, and is adaptive to the individual variability of the acquired data. After selecting one source point inside the Region of Interest (ROI), a segmentation process is initiated, which consists of two automatic stages: a cost-labeling phase and a graph-cutting phase. The algorithm finds optimal paths based on a new cost function by creating a Minimum Path Spanning Tree (MPST). To extract the region, a cut of the obtained tree is necessary. A new criterion of the MPST-cut based on compactness shape factor was conceived and developed. The proposed approach is applied to a large database of 96 T1-weighted MR bone volumes. Performance quality is evaluated by comparing the results with gold-standard bone volumes manually defined by rheumatologists through the computation of metrics extracted from the confusion matrix. Furthermore, comparisons with the existing literature are carried out. The results show that this method is efficient and provides satisfactory performance for bone segmentation on low-field MR volumes. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. Mycobacterium stephanolepidis sp. nov., a rapidly growing species related to Mycobacterium chelonae, isolated from marine teleost fish, Stephanolepis cirrhifer.

    Science.gov (United States)

    Fukano, Hanako; Wada, Shinpei; Kurata, Osamu; Katayama, Kinya; Fujiwara, Nagatoshi; Hoshino, Yoshihiko

    2017-08-01

    A previously undescribed rapidly growing, non-pigmented mycobacterium was identified based on biochemical and nucleic acid analyses, as well as growth characteristics. Seven isolates were cultured from samples collected from five thread-sail filefish (Stephanolepis cirrhifer) and two farmed black scraper (Thamnaconus modestus). Bacterial growth occurred at 15-35 °C on Middlebrook 7H11 agar. The bacteria were positive for catalase activity at 68 °C and urease activity, intermediate for iron uptake, and negative for Tween 80 hydrolysis, nitrate reduction, semi-quantitative catalase activity and arylsulfatase activity at day 3. No growth was observed on Middlebrook 7H11 agar supplemented with picric acid, and very little growth was observed in the presence of 5 % NaCl. α- and α'-mycolates were identified in the cell walls, and a unique profile of the fatty acid methyl esters and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) profiles of the protein and cell-wall lipids were acquired. Sequence analysis revealed that the seven isolates shared identical sequences for the 16S rRNA, rpoB, hsp65, recA and sodA genes. Phylogenetic analysis of the five gene sequences confirmed that the isolates were unique, but closely related to Mycobacterium chelonae. Antibiotic susceptibility testing revealed the minimum inhibitory concentration (MIC) of clarithromycin against this novel species was Mycobacterium salmoniphilum. The hsp65 PCR restriction enzyme analysis pattern differed from those of M. chelonae and M. salmoniphilum. Based on these findings, the name Mycobacterium stephanolepidis sp. nov. is proposed for this novel species, with the type strain being NJB0901 T (=JCM 31611 T =KCTC 39843 T ).

  15. The economic case for low-carbon development in rapidly growing developing world cities: A case study of Palembang, Indonesia

    International Nuclear Information System (INIS)

    Colenbrander, Sarah; Gouldson, Andy; Sudmant, Andrew Heshedahl; Papargyropoulou, Effie

    2015-01-01

    Where costs or risks are higher, evidence is lacking or supporting institutions are less developed, policymakers can struggle to make the case for low-carbon investment. This is especially the case in developing world cities where decision-makers struggle to keep up with the pace and scale of change. Focusing on Palembang in Indonesia, this paper considers the economic case for proactive investment in low-carbon development. We find that a rapidly growing industrial city in a developing country can reduce emissions by 24.1% in 2025, relative to business as usual levels, with investments of USD405.6 million that would reduce energy expenditure in the city by USD436.8 million. Emissions from the regional grid could be reduced by 12.2% in 2025, relative to business as usual trends, with investments of USD2.9 billion that would generate annual savings of USD175 million. These estimates understate the savings from reduced expenditure on energy subsidies and energy infrastructure. The compelling economic case for mainstreaming climate mitigation in this developing country city suggests that the constraints on climate action can be political and institutional rather than economic. There is therefore a need for more effective energy governance to drive the transition to a low-carbon economy. - Highlights: • We evaluate the economic case for low carbon investment in a developing world city. • Cost-effective measures could reduce emissions by 24.1% relative to BAU levels. • These pay for themselves in <1 year and generate savings throughout their lifetime. • Further savings come from reduced expenditure on energy infrastructure, subsidies. • Limitations on climate action seem to be political/institutional – not economic

  16. Rapid reconnection of flux lines

    International Nuclear Information System (INIS)

    Samain, A.

    1982-01-01

    The rapid reconnection of flux lines in an incompressible fluid through a singular layer of the current density is discussed. It is shown that the liberated magnetic energy must partially appear in the form of plasma kinetic energy. A laminar structure of the flow is possible, but Alfven velocity must be achieved in eddies of growing size at the ends of the layer. The gross structure of the flow and the magnetic configuration may be obtained from variational principles. (author)

  17. Regional Advection Perturbations in an Irrigated Desert (RAPID) Experiment

    NARCIS (Netherlands)

    Debruin, H.A.R.; Hartogensis, O.K.; Allen, R.G.; Kramer, J.W.J.L.

    2005-01-01

    The RAPID field experiment took place in August - September 1999 at a site 25km south of Twin Falls, Idaho, USA. The experiment concerned micrometeorological observations over extensive, well-irrigated fields covered with the fast-growing crop alfalfa. During daytime, on a number of days the

  18. A big data management platform for rapidly changing environments

    NARCIS (Netherlands)

    Zahedi, P.

    2014-01-01

    Big data is now a reality. Storing, managing, and analyzing very large amount of data is a common challenge in the world of technology where digital content is rapidly growing. In recent years, FEI advanced electron microscopes, with their unsurpassed magnification and resolving power brought an

  19. Poly(ether amide) segmented block copolymers with adipicacid based tetra amide segments

    NARCIS (Netherlands)

    Biemond, G.J.E.; Feijen, Jan; Gaymans, R.J.

    2007-01-01

    Poly(tetramethylene oxide)-based poly(ether ester amide)s with monodisperse tetraamide segments were synthesized. The tetraamide segment was based on adipic acid, terephthalic acid, and hexamethylenediamine. The synthesis method of the copolymers and the influence of the tetraamide concentration,

  20. Segmenting by Risk Perceptions: Predicting Young Adults’ Genetic-Belief Profiles with Health and Opinion-Leader Covariates

    Science.gov (United States)

    Smith, Rachel A.; Greenberg, Marisa; Parrott, Roxanne L.

    2014-01-01

    With a growing interest in using genetic information to motivate young adults’ health behaviors, audience segmentation is needed for effective campaign design. Using latent class analysis, this study identifies segments based on young adults’ (N = 327) beliefs about genetic threats to their health and personal efficacy over genetic influences on their health. A four-class model was identified. The model indicators fit the risk perception attitude framework (Rimal & Real, 2003), but the covariates (e.g., current health behaviors) did not. In addition, opinion leader qualities covaried with one profile: those in this profile engaged in fewer preventative behaviors and more dangerous treatment options, and also liked to persuade others, making them a particularly salient group for campaign efforts. The implications for adult-onset disorders, like alpha-1 antitrypsin deficiency are discussed. PMID:24111749

  1. Nanomaterial-enabled Rapid Detection of Water Contaminants.

    Science.gov (United States)

    Mao, Shun; Chang, Jingbo; Zhou, Guihua; Chen, Junhong

    2015-10-28

    Water contaminants, e.g., inorganic chemicals and microorganisms, are critical metrics for water quality monitoring and have significant impacts on human health and plants/organisms living in water. The scope and focus of this review is nanomaterial-based optical, electronic, and electrochemical sensors for rapid detection of water contaminants, e.g., heavy metals, anions, and bacteria. These contaminants are commonly found in different water systems. The importance of water quality monitoring and control demands significant advancement in the detection of contaminants in water because current sensing technologies for water contaminants have limitations. The advantages of nanomaterial-based sensing technologies are highlighted and recent progress on nanomaterial-based sensors for rapid water contaminant detection is discussed. An outlook for future research into this rapidly growing field is also provided. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. Metric Learning for Hyperspectral Image Segmentation

    Science.gov (United States)

    Bue, Brian D.; Thompson, David R.; Gilmore, Martha S.; Castano, Rebecca

    2011-01-01

    We present a metric learning approach to improve the performance of unsupervised hyperspectral image segmentation. Unsupervised spatial segmentation can assist both user visualization and automatic recognition of surface features. Analysts can use spatially-continuous segments to decrease noise levels and/or localize feature boundaries. However, existing segmentation methods use tasks-agnostic measures of similarity. Here we learn task-specific similarity measures from training data, improving segment fidelity to classes of interest. Multiclass Linear Discriminate Analysis produces a linear transform that optimally separates a labeled set of training classes. The defines a distance metric that generalized to a new scenes, enabling graph-based segmentation that emphasizes key spectral features. We describe tests based on data from the Compact Reconnaissance Imaging Spectrometer (CRISM) in which learned metrics improve segment homogeneity with respect to mineralogical classes.

  3. Market Segmentation for Information Services.

    Science.gov (United States)

    Halperin, Michael

    1981-01-01

    Discusses the advantages and limitations of market segmentation as strategy for the marketing of information services made available by nonprofit organizations, particularly libraries. Market segmentation is defined, a market grid for libraries is described, and the segmentation of information services is outlined. A 16-item reference list is…

  4. Probabilistic Segmentation of Folk Music Recordings

    Directory of Open Access Journals (Sweden)

    Ciril Bohak

    2016-01-01

    Full Text Available The paper presents a novel method for automatic segmentation of folk music field recordings. The method is based on a distance measure that uses dynamic time warping to cope with tempo variations and a dynamic programming approach to handle pitch drifting for finding similarities and estimating the length of repeating segment. A probabilistic framework based on HMM is used to find segment boundaries, searching for optimal match between the expected segment length, between-segment similarities, and likely locations of segment beginnings. Evaluation of several current state-of-the-art approaches for segmentation of commercial music is presented and their weaknesses when dealing with folk music are exposed, such as intolerance to pitch drift and variable tempo. The proposed method is evaluated and its performance analyzed on a collection of 206 folk songs of different ensemble types: solo, two- and three-voiced, choir, instrumental, and instrumental with singing. It outperforms current commercial music segmentation methods for noninstrumental music and is on a par with the best for instrumental recordings. The method is also comparable to a more specialized method for segmentation of solo singing folk music recordings.

  5. Automated medical image segmentation techniques

    Directory of Open Access Journals (Sweden)

    Sharma Neeraj

    2010-01-01

    Full Text Available Accurate segmentation of medical images is a key step in contouring during radiotherapy planning. Computed topography (CT and Magnetic resonance (MR imaging are the most widely used radiographic techniques in diagnosis, clinical studies and treatment planning. This review provides details of automated segmentation methods, specifically discussed in the context of CT and MR images. The motive is to discuss the problems encountered in segmentation of CT and MR images, and the relative merits and limitations of methods currently available for segmentation of medical images.

  6. Prognostic validation of a 17-segment score derived from a 20-segment score for myocardial perfusion SPECT interpretation.

    Science.gov (United States)

    Berman, Daniel S; Abidov, Aiden; Kang, Xingping; Hayes, Sean W; Friedman, John D; Sciammarella, Maria G; Cohen, Ishac; Gerlach, James; Waechter, Parker B; Germano, Guido; Hachamovitch, Rory

    2004-01-01

    Recently, a 17-segment model of the left ventricle has been recommended as an optimally weighted approach for interpreting myocardial perfusion single photon emission computed tomography (SPECT). Methods to convert databases from previous 20- to new 17-segment data and criteria for abnormality for the 17-segment scores are needed. Initially, for derivation of the conversion algorithm, 65 patients were studied (algorithm population) (pilot group, n = 28; validation group, n = 37). Three conversion algorithms were derived: algorithm 1, which used mid, distal, and apical scores; algorithm 2, which used distal and apical scores alone; and algorithm 3, which used maximal scores of the distal septal, lateral, and apical segments in the 20-segment model for 3 corresponding segments of the 17-segment model. The prognosis population comprised 16,020 consecutive patients (mean age, 65 +/- 12 years; 41% women) who had exercise or vasodilator stress technetium 99m sestamibi myocardial perfusion SPECT and were followed up for 2.1 +/- 0.8 years. In this population, 17-segment scores were derived from 20-segment scores by use of algorithm 2, which demonstrated the best agreement with expert 17-segment reading in the algorithm population. The prognostic value of the 20- and 17-segment scores was compared by converting the respective summed scores into percent myocardium abnormal. Conversion algorithm 2 was found to be highly concordant with expert visual analysis by the 17-segment model (r = 0.982; kappa = 0.866) in the algorithm population. In the prognosis population, 456 cardiac deaths occurred during follow-up. When the conversion algorithm was applied, extent and severity of perfusion defects were nearly identical by 20- and derived 17-segment scores. The receiver operating characteristic curve areas by 20- and 17-segment perfusion scores were identical for predicting cardiac death (both 0.77 +/- 0.02, P = not significant). The optimal prognostic cutoff value for either 20

  7. Segmentation algorithm of colon based on multi-slice CT colonography

    Science.gov (United States)

    Hu, Yizhong; Ahamed, Mohammed Shabbir; Takahashi, Eiji; Suzuki, Hidenobu; Kawata, Yoshiki; Niki, Noboru; Suzuki, Masahiro; Iinuma, Gen; Moriyama, Noriyuki

    2012-02-01

    CT colonography is a radiology test that looks at people's large intestines(colon). CT colonography can screen many options of colon cancer. This test is used to detect polyps or cancers of the colon. CT colonography is safe and reliable. It can be used if people are too sick to undergo other forms of colon cancer screening. In our research, we proposed a method for automatic segmentation of the colon from abdominal computed Tomography (CT) images. Our multistage detection method extracted colon and spited colon into different parts according to the colon anatomy information. We found that among the five segmented parts of the colon, sigmoid (20%) and rectum (50%) are more sensitive toward polyps and masses than the other three parts. Our research focused on detecting the colon by the individual diagnosis of sigmoid and rectum. We think it would make the rapid and easy diagnosis of colon in its earlier stage and help doctors for analysis of correct position of each part and detect the colon rectal cancer much easier.

  8. NUCLEAR SEGMENTATION IN MICROSCOPE CELL IMAGES: A HAND-SEGMENTED DATASET AND COMPARISON OF ALGORITHMS

    OpenAIRE

    Coelho, Luís Pedro; Shariff, Aabid; Murphy, Robert F.

    2009-01-01

    Image segmentation is an essential step in many image analysis pipelines and many algorithms have been proposed to solve this problem. However, they are often evaluated subjectively or based on a small number of examples. To fill this gap, we hand-segmented a set of 97 fluorescence microscopy images (a total of 4009 cells) and objectively evaluated some previously proposed segmentation algorithms.

  9. Principle and realization of segmenting contour series algorithm in reverse engineering based on X-ray computerized tomography

    International Nuclear Information System (INIS)

    Wang Yanfang; Liu Li; Yan Yonglian; Shan Baoci; Tang Xiaowei

    2007-01-01

    A new algorithm of segmenting contour series of images is presented, which can achieve three dimension reconstruction with parametric recognition in Reverse Engineering based on X-ray CT. First, in order to get the nested relationship between contours, a method of a certain angle ray is used. Second, for realizing the contour location in one slice, another approach is presented to generate the contour tree by scanning the relevant vector only once. Last, a judge algorithm is put forward to accomplish the contour match between slices by adopting the qualitative and quantitative properties. The example shows that this algorithm can segment contour series of CT parts rapidly and precisely. (authors)

  10. Growing media [Chapter 5

    Science.gov (United States)

    Douglass F. Jacobs; Thomas D. Landis; Tara Luna

    2009-01-01

    Selecting the proper growing medium is one of the most important considerations in nursery plant production. A growing medium can be defined as a substance through which roots grow and extract water and nutrients. In native plant nurseries, a growing medium can consist of native soil but is more commonly an "artificial soil" composed of materials such as peat...

  11. Generalized pixel profiling and comparative segmentation with application to arteriovenous malformation segmentation.

    Science.gov (United States)

    Babin, D; Pižurica, A; Bellens, R; De Bock, J; Shang, Y; Goossens, B; Vansteenkiste, E; Philips, W

    2012-07-01

    Extraction of structural and geometric information from 3-D images of blood vessels is a well known and widely addressed segmentation problem. The segmentation of cerebral blood vessels is of great importance in diagnostic and clinical applications, with a special application in diagnostics and surgery on arteriovenous malformations (AVM). However, the techniques addressing the problem of the AVM inner structure segmentation are rare. In this work we present a novel method of pixel profiling with the application to segmentation of the 3-D angiography AVM images. Our algorithm stands out in situations with low resolution images and high variability of pixel intensity. Another advantage of our method is that the parameters are set automatically, which yields little manual user intervention. The results on phantoms and real data demonstrate its effectiveness and potentials for fine delineation of AVM structure. Copyright © 2012 Elsevier B.V. All rights reserved.

  12. Robust shape regression for supervised vessel segmentation and its application to coronary segmentation in CTA

    DEFF Research Database (Denmark)

    Schaap, Michiel; van Walsum, Theo; Neefjes, Lisan

    2011-01-01

    This paper presents a vessel segmentation method which learns the geometry and appearance of vessels in medical images from annotated data and uses this knowledge to segment vessels in unseen images. Vessels are segmented in a coarse-to-fine fashion. First, the vessel boundaries are estimated...

  13. Automatic data-driven real-time segmentation and recognition of surgical workflow.

    Science.gov (United States)

    Dergachyova, Olga; Bouget, David; Huaulmé, Arnaud; Morandi, Xavier; Jannin, Pierre

    2016-06-01

    With the intention of extending the perception and action of surgical staff inside the operating room, the medical community has expressed a growing interest towards context-aware systems. Requiring an accurate identification of the surgical workflow, such systems make use of data from a diverse set of available sensors. In this paper, we propose a fully data-driven and real-time method for segmentation and recognition of surgical phases using a combination of video data and instrument usage signals, exploiting no prior knowledge. We also introduce new validation metrics for assessment of workflow detection. The segmentation and recognition are based on a four-stage process. Firstly, during the learning time, a Surgical Process Model is automatically constructed from data annotations to guide the following process. Secondly, data samples are described using a combination of low-level visual cues and instrument information. Then, in the third stage, these descriptions are employed to train a set of AdaBoost classifiers capable of distinguishing one surgical phase from others. Finally, AdaBoost responses are used as input to a Hidden semi-Markov Model in order to obtain a final decision. On the MICCAI EndoVis challenge laparoscopic dataset we achieved a precision and a recall of 91 % in classification of 7 phases. Compared to the analysis based on one data type only, a combination of visual features and instrument signals allows better segmentation, reduction of the detection delay and discovery of the correct phase order.

  14. Automatic 2D segmentation of airways in thorax computed tomography images; Segmentacao automatica 2D de vias aereas em imagens de tomografia computadorizada do torax

    Energy Technology Data Exchange (ETDEWEB)

    Cavalcante, Tarique da Silveira; Cortez, Paulo Cesar; Almeida, Thomaz Maia de, E-mail: tarique@lesc.ufc.br [Universidade Federal do Ceara (UFC), Fortaleza, CE (Brazil). Dept. de Engenharia de Teleinformatica; Felix, John Hebert da Silva [Universidade da Integracao Internacional da Lusofonia Afro-Brasileira (UNILAB), Redencao, CE (Brazil). Departamento de Energias; Holanda, Marcelo Alcantara [Universidade Federal do Ceara (UFC), Fortaleza, CE (Brazil). Fac. de Medicina

    2013-07-01

    Introduction: much of the world population is affected by pulmonary diseases, such as the bronchial asthma, bronchitis and bronchiectasis. The bronchial diagnosis is based on the airways state. In this sense, the automatic segmentation of the airways in Computed Tomography (CT) scans is a critical step in the aid to diagnosis of these diseases. Methods: this paper evaluates algorithms for airway automatic segmentation, using Neural Network Multilayer Perceptron (MLP) and Lung Densities Analysis (LDA) for detecting airways, along with Region Growing (RG), Active Contour Method (ACM) Balloon and Topology Adaptive to segment them. Results: we obtained results in three stages: comparative analysis of the detection algorithms MLP and LDA, with a gold standard acquired by three physicians with expertise in CT imaging of the chest; comparative analysis of segmentation algorithms ACM Balloon, ACM Topology Adaptive, MLP and RG; and evaluation of possible combinations between segmentation and detection algorithms, resulting in the complete method for automatic segmentation of the airways in 2D. Conclusion: the low incidence of false negative and the significant reduction of false positive, results in similarity coefficient and sensitivity exceeding 91% and 87% respectively, for a combination of algorithms with satisfactory segmentation quality. (author)

  15. Segmentation and morphometric analysis of cells from fluorescence microscopy images of cytoskeletons.

    Science.gov (United States)

    Ujihara, Yoshihiro; Nakamura, Masanori; Miyazaki, Hiroshi; Wada, Shigeo

    2013-01-01

    We developed a method to reconstruct cell geometry from confocal fluorescence microscopy images of the cytoskeleton. In the method, region growing was implemented twice. First, it was applied to the extracellular regions to differentiate them from intracellular noncytoskeletal regions, which both appear black in fluorescence microscopy imagery, and then to cell regions for cell identification. Analysis of morphological parameters revealed significant changes in cell shape associated with cytoskeleton disruption, which offered insight into the mechanical role of the cytoskeleton in maintaining cell shape. The proposed segmentation method is promising for investigations on cell morphological changes with respect to internal cytoskeletal structures.

  16. A hierarchical 3D segmentation method and the definition of vertebral body coordinate systems for QCT of the lumbar spine.

    Science.gov (United States)

    Mastmeyer, André; Engelke, Klaus; Fuchs, Christina; Kalender, Willi A

    2006-08-01

    We have developed a new hierarchical 3D technique to segment the vertebral bodies in order to measure bone mineral density (BMD) with high trueness and precision in volumetric CT datasets. The hierarchical approach starts with a coarse separation of the individual vertebrae, applies a variety of techniques to segment the vertebral bodies with increasing detail and ends with the definition of an anatomic coordinate system for each vertebral body, relative to which up to 41 trabecular and cortical volumes of interest are positioned. In a pre-segmentation step constraints consisting of Boolean combinations of simple geometric shapes are determined that enclose each individual vertebral body. Bound by these constraints viscous deformable models are used to segment the main shape of the vertebral bodies. Volume growing and morphological operations then capture the fine details of the bone-soft tissue interface. In the volumes of interest bone mineral density and content are determined. In addition, in the segmented vertebral bodies geometric parameters such as volume or the length of the main axes of inertia can be measured. Intra- and inter-operator precision errors of the segmentation procedure were analyzed using existing clinical patient datasets. Results for segmented volume, BMD, and coordinate system position were below 2.0%, 0.6%, and 0.7%, respectively. Trueness was analyzed using phantom scans. The bias of the segmented volume was below 4%; for BMD it was below 1.5%. The long-term goal of this work is improved fracture prediction and patient monitoring in the field of osteoporosis. A true 3D segmentation also enables an accurate measurement of geometrical parameters that may augment the clinical value of a pure BMD analysis.

  17. Physics-Based Image Segmentation Using First Order Statistical Properties and Genetic Algorithm for Inductive Thermography Imaging.

    Science.gov (United States)

    Gao, Bin; Li, Xiaoqing; Woo, Wai Lok; Tian, Gui Yun

    2018-05-01

    Thermographic inspection has been widely applied to non-destructive testing and evaluation with the capabilities of rapid, contactless, and large surface area detection. Image segmentation is considered essential for identifying and sizing defects. To attain a high-level performance, specific physics-based models that describe defects generation and enable the precise extraction of target region are of crucial importance. In this paper, an effective genetic first-order statistical image segmentation algorithm is proposed for quantitative crack detection. The proposed method automatically extracts valuable spatial-temporal patterns from unsupervised feature extraction algorithm and avoids a range of issues associated with human intervention in laborious manual selection of specific thermal video frames for processing. An internal genetic functionality is built into the proposed algorithm to automatically control the segmentation threshold to render enhanced accuracy in sizing the cracks. Eddy current pulsed thermography will be implemented as a platform to demonstrate surface crack detection. Experimental tests and comparisons have been conducted to verify the efficacy of the proposed method. In addition, a global quantitative assessment index F-score has been adopted to objectively evaluate the performance of different segmentation algorithms.

  18. Structure-properties relationships of novel poly(carbonate-co-amide) segmented copolymers with polyamide-6 as hard segments and polycarbonate as soft segments

    Science.gov (United States)

    Yang, Yunyun; Kong, Weibo; Yuan, Ye; Zhou, Changlin; Cai, Xufu

    2018-04-01

    Novel poly(carbonate-co-amide) (PCA) block copolymers are prepared with polycarbonate diol (PCD) as soft segments, polyamide-6 (PA6) as hard segments and 4,4'-diphenylmethane diisocyanate (MDI) as coupling agent through reactive processing. The reactive processing strategy is eco-friendly and resolve the incompatibility between polyamide segments and PCD segments in preparation processing. The chemical structure, crystalline properties, thermal properties, mechanical properties and water resistance were extensively studied by Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), Differential scanning calorimetry (DSC), Thermal gravity analysis (TGA), Dynamic mechanical analysis (DMA), tensile testing, water contact angle and water absorption, respectively. The as-prepared PCAs exhibit obvious microphase separation between the crystalline hard PA6 phase and amorphous PCD soft segments. Meanwhile, PCAs showed outstanding mechanical with the maximum tensile strength of 46.3 MPa and elongation at break of 909%. The contact angle and water absorption results indicate that PCAs demonstrate outstanding water resistance even though possess the hydrophilic surfaces. The TGA measurements prove that the thermal stability of PCA can satisfy the requirement of multiple-processing without decomposition.

  19. Segmentation and informality in Vietnam : a survey of the literature: country case study on labour market segmentation

    OpenAIRE

    Cling, Jean-Pierre; Razafindrakoto, Mireille; Roubaud, François

    2014-01-01

    Labour market segmentation is usually defined as the division of the labour markets into separate sub-markets or segments, distinguished by different characteristics and behavioural rules (incomes, contracts, etc.). The economic debate on the segmentation issue has been focusing in developed countries, and especially in Europe, on contractual segmentation and dualism.

  20. Segmentation by Large Scale Hypothesis Testing - Segmentation as Outlier Detection

    DEFF Research Database (Denmark)

    Darkner, Sune; Dahl, Anders Lindbjerg; Larsen, Rasmus

    2010-01-01

    a microscope and we show how the method can handle transparent particles with significant glare point. The method generalizes to other problems. THis is illustrated by applying the method to camera calibration images and MRI of the midsagittal plane for gray and white matter separation and segmentation......We propose a novel and efficient way of performing local image segmentation. For many applications a threshold of pixel intensities is sufficient but determine the appropriate threshold value can be difficult. In cases with large global intensity variation the threshold value has to be adapted...... locally. We propose a method based on large scale hypothesis testing with a consistent method for selecting an appropriate threshold for the given data. By estimating the background distribution we characterize the segment of interest as a set of outliers with a certain probability based on the estimated...

  1. FAST AND ROBUST SEGMENTATION AND CLASSIFICATION FOR CHANGE DETECTION IN URBAN POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    X. Roynard

    2016-06-01

    Full Text Available Change detection is an important issue in city monitoring to analyse street furniture, road works, car parking, etc. For example, parking surveys are needed but are currently a laborious task involving sending operators in the streets to identify the changes in car locations. In this paper, we propose a method that performs a fast and robust segmentation and classification of urban point clouds, that can be used for change detection. We apply this method to detect the cars, as a particular object class, in order to perform parking surveys automatically. A recently proposed method already addresses the need for fast segmentation and classification of urban point clouds, using elevation images. The interest to work on images is that processing is much faster, proven and robust. However there may be a loss of information in complex 3D cases: for example when objects are one above the other, typically a car under a tree or a pedestrian under a balcony. In this paper we propose a method that retain the three-dimensional information while preserving fast computation times and improving segmentation and classification accuracy. It is based on fast region-growing using an octree, for the segmentation, and specific descriptors with Random-Forest for the classification. Experiments have been performed on large urban point clouds acquired by Mobile Laser Scanning. They show that the method is as fast as the state of the art, and that it gives more robust results in the complex 3D cases.

  2. A study of riders' noise exposure on Bay Area Rapid Transit trains.

    Science.gov (United States)

    Dinno, Alexis; Powell, Cynthia; King, Margaret Mary

    2011-02-01

    Excessive noise exposure may present a hazard to hearing, cardiovascular, and psychosomatic health. Mass transit systems, such as the Bay Area Rapid Transit (BART) system, are potential sources of excessive noise. The purpose of this study was to characterize transit noise and riders' exposure to noise on the BART system using three dosimetry metrics. We made 268 dosimetry measurements on a convenience sample of 51 line segments. Dosimetry measures were modeled using linear and nonlinear multiple regression as functions of average velocity, tunnel enclosure, flooring, and wet weather conditions and presented visually on a map of the BART system. This study provides evidence of levels of hazardous levels of noise exposure in all three dosimetry metrics. L(eq) and L(max) measures indicate exposures well above ranges associated with increased cardiovascular and psychosomatic health risks in the published literature. L(peak) indicate acute exposures hazardous to adult hearing on about 1% of line segment rides and acute exposures hazardous to child hearing on about 2% of such rides. The noise to which passengers are exposed may be due to train-specific conditions (velocity and flooring), but also to rail conditions (velocity and tunnels). These findings may point at possible remediation (revised speed limits on longer segments and those segments enclosed by tunnels). The findings also suggest that specific rail segments could be improved for noise.

  3. Pavement management segment consolidation

    Science.gov (United States)

    1998-01-01

    Dividing roads into "homogeneous" segments has been a major problem for all areas of highway engineering. SDDOT uses Deighton Associates Limited software, dTIMS, to analyze life-cycle costs for various rehabilitation strategies on each segment of roa...

  4. Automatic segmentation of vertebrae from radiographs

    DEFF Research Database (Denmark)

    Mysling, Peter; Petersen, Peter Kersten; Nielsen, Mads

    2011-01-01

    Segmentation of vertebral contours is an essential task in the design of automatic tools for vertebral fracture assessment. In this paper, we propose a novel segmentation technique which does not require operator interaction. The proposed technique solves the segmentation problem in a hierarchical...... is constrained by a conditional shape model, based on the variability of the coarse spine location estimates. The technique is evaluated on a data set of manually annotated lumbar radiographs. The results compare favorably to the previous work in automatic vertebra segmentation, in terms of both segmentation...

  5. Clinical utility of anterior segment swept-source optical coherence tomography in glaucoma

    Directory of Open Access Journals (Sweden)

    Dewang Angmo

    2016-01-01

    Full Text Available Optical coherence tomography (OCT, a noninvasive imaging modality that uses low-coherence light to obtain a high-resolution cross-section of biological structures, has evolved dramatically over the years. The Swept-source OCT (SS-OCT makes use of a single detector with a rapidly tunable laser as a light source. The Casia SS-1000 OCT is a Fourier-domain, SS-OCT designed specifically for imaging the anterior segment. This system achieves high resolution imaging of 10΅m (Axial and 30΅m (Transverse and high speed scanning of 30,000 A-scans per second. With a substantial improvement in scan speed, the anterior chamber angles can be imaged 360 degrees in 128 cross sections (each with 512 A-scans in about 2.4 seconds. We summarize the clinical applications of anterior segment SS-OCT in Glaucoma. Literature search: We searched PubMed and included Medline using the phrases anterior segment optical coherence tomography in ophthalmology, swept-source OCT, use of AS-OCT in glaucoma, use of swept-source AS-OCT in glaucoma, quantitative assessment of angle, filtering bleb in AS-OCT, comparison of AS-OCT with gonioscopy and comparison of AS-OCT with UBM. Search was made for articles dating 1990 to August 2015.

  6. A combined segmenting and non-segmenting approach to signal quality estimation for ambulatory photoplethysmography

    International Nuclear Information System (INIS)

    Wander, J D; Morris, D

    2014-01-01

    Continuous cardiac monitoring of healthy and unhealthy patients can help us understand the progression of heart disease and enable early treatment. Optical pulse sensing is an excellent candidate for continuous mobile monitoring of cardiovascular health indicators, but optical pulse signals are susceptible to corruption from a number of noise sources, including motion artifact. Therefore, before higher-level health indicators can be reliably computed, corrupted data must be separated from valid data. This is an especially difficult task in the presence of artifact caused by ambulation (e.g. walking or jogging), which shares significant spectral energy with the true pulsatile signal. In this manuscript, we present a machine-learning-based system for automated estimation of signal quality of optical pulse signals that performs well in the presence of periodic artifact. We hypothesized that signal processing methods that identified individual heart beats (segmenting approaches) would be more error-prone than methods that did not (non-segmenting approaches) when applied to data contaminated by periodic artifact. We further hypothesized that a fusion of segmenting and non-segmenting approaches would outperform either approach alone. Therefore, we developed a novel non-segmenting approach to signal quality estimation that we then utilized in combination with a traditional segmenting approach. Using this system we were able to robustly detect differences in signal quality as labeled by expert human raters (Pearson’s r = 0.9263). We then validated our original hypotheses by demonstrating that our non-segmenting approach outperformed the segmenting approach in the presence of contaminated signal, and that the combined system outperformed either individually. Lastly, as an example, we demonstrated the utility of our signal quality estimation system in evaluating the trustworthiness of heart rate measurements derived from optical pulse signals. (paper)

  7. Rhythm-based segmentation of Popular Chinese Music

    DEFF Research Database (Denmark)

    Jensen, Karl Kristoffer

    2005-01-01

    We present a new method to segment popular music based on rhythm. By computing a shortest path based on the self-similarity matrix calculated from a model of rhythm, segmenting boundaries are found along the di- agonal of the matrix. The cost of a new segment is opti- mized by matching manual...... and automatic segment boundaries. We compile a small song database of 21 randomly selected popular Chinese songs which come from Chinese Mainland, Taiwan and Hong Kong. The segmenting results on the small corpus show that 78% manual segmentation points are detected and 74% auto- matic segmentation points...

  8. Unsupervised Performance Evaluation of Image Segmentation

    Directory of Open Access Journals (Sweden)

    Chabrier Sebastien

    2006-01-01

    Full Text Available We present in this paper a study of unsupervised evaluation criteria that enable the quantification of the quality of an image segmentation result. These evaluation criteria compute some statistics for each region or class in a segmentation result. Such an evaluation criterion can be useful for different applications: the comparison of segmentation results, the automatic choice of the best fitted parameters of a segmentation method for a given image, or the definition of new segmentation methods by optimization. We first present the state of art of unsupervised evaluation, and then, we compare six unsupervised evaluation criteria. For this comparative study, we use a database composed of 8400 synthetic gray-level images segmented in four different ways. Vinet's measure (correct classification rate is used as an objective criterion to compare the behavior of the different criteria. Finally, we present the experimental results on the segmentation evaluation of a few gray-level natural images.

  9. A systematic review of image segmentation methodology, used in the additive manufacture of patient-specific 3D printed models of the cardiovascular system

    Directory of Open Access Journals (Sweden)

    N Byrne

    2016-04-01

    Full Text Available Background Shortcomings in existing methods of image segmentation preclude the widespread adoption of patient-specific 3D printing as a routine decision-making tool in the care of those with congenital heart disease. We sought to determine the range of cardiovascular segmentation methods and how long each of these methods takes. Methods A systematic review of literature was undertaken. Medical imaging modality, segmentation methods, segmentation time, segmentation descriptive quality (SDQ and segmentation software were recorded. Results Totally 136 studies met the inclusion criteria (1 clinical trial; 80 journal articles; 55 conference, technical and case reports. The most frequently used image segmentation methods were brightness thresholding, region growing and manual editing, as supported by the most popular piece of proprietary software: Mimics (Materialise NV, Leuven, Belgium, 1992–2015. The use of bespoke software developed by individual authors was not uncommon. SDQ indicated that reporting of image segmentation methods was generally poor with only one in three accounts providing sufficient detail for their procedure to be reproduced. Conclusions and implication of key findings Predominantly anecdotal and case reporting precluded rigorous assessment of risk of bias and strength of evidence. This review finds a reliance on manual and semi-automated segmentation methods which demand a high level of expertise and a significant time commitment on the part of the operator. In light of the findings, we have made recommendations regarding reporting of 3D printing studies. We anticipate that these findings will encourage the development of advanced image segmentation methods.

  10. The end of surplus and a growing role in world markets

    International Nuclear Information System (INIS)

    Eklof, W.D.

    1991-01-01

    Rapid economic growth in Asia in recent years has rekindled the region's appetite for energy. This surge in energy consumption since the oil price collapse in 1986 has brought into sharp focus critical challenges facing Asian governments and commercial organizations in the 1990's--challenges that must be met if the economic success of recent years is to continue. Yet supplying energy to fuel economic growth will be more difficult than in the past. Oil reserves in the region are inadequate to support the anticipated growth in demands, and new discoveries may be modest. Gas reserves are plentiful, but not well located to meet the energy needs of major markets. Added to difficulties associated with these resource-based limitations new challenges are emerging: growing consumer demands for transportation fuels and electricity, a growing concern for the environmental impact of energy production and consumption, and the need to rethink long-standing energy policies that were based on expectations of very high future oil prices. These new factors will complicate policy decisions and place new constraints on available energy options. This paper addresses the future development of Asian oil and gas markets in light of these challenges, and provides an assessment of the potential growth of gas markets, the need for growing oil imports into the region, and the need for new refining capacity to meet the growing demand for transportation fuels

  11. Methods of evaluating segmentation characteristics and segmentation of major faults

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Kie Hwa; Chang, Tae Woo; Kyung, Jai Bok [Seoul National Univ., Seoul (Korea, Republic of)] (and others)

    2000-03-15

    Seismological, geological, and geophysical studies were made for reasonable segmentation of the Ulsan fault and the results are as follows. One- and two- dimensional electrical surveys revealed clearly the fault fracture zone enlarges systematically northward and southward from the vicinity of Mohwa-ri, indicating Mohwa-ri is at the seismic segment boundary. Field Geological survey and microscope observation of fault gouge indicates that the Quaternary faults in the area are reactivated products of the preexisting faults. Trench survey of the Chonbuk fault Galgok-ri revealed thrust faults and cumulative vertical displacement due to faulting during the late Quaternary with about 1.1-1.9 m displacement per event; the latest event occurred from 14000 to 25000 yrs. BP. The seismic survey showed the basement surface os cut by numerous reverse faults and indicated the possibility that the boundary between Kyeongsangbukdo and Kyeongsannamdo may be segment boundary.

  12. Methods of evaluating segmentation characteristics and segmentation of major faults

    International Nuclear Information System (INIS)

    Lee, Kie Hwa; Chang, Tae Woo; Kyung, Jai Bok

    2000-03-01

    Seismological, geological, and geophysical studies were made for reasonable segmentation of the Ulsan fault and the results are as follows. One- and two- dimensional electrical surveys revealed clearly the fault fracture zone enlarges systematically northward and southward from the vicinity of Mohwa-ri, indicating Mohwa-ri is at the seismic segment boundary. Field Geological survey and microscope observation of fault gouge indicates that the Quaternary faults in the area are reactivated products of the preexisting faults. Trench survey of the Chonbuk fault Galgok-ri revealed thrust faults and cumulative vertical displacement due to faulting during the late Quaternary with about 1.1-1.9 m displacement per event; the latest event occurred from 14000 to 25000 yrs. BP. The seismic survey showed the basement surface os cut by numerous reverse faults and indicated the possibility that the boundary between Kyeongsangbukdo and Kyeongsannamdo may be segment boundary

  13. A new framework for interactive images segmentation

    International Nuclear Information System (INIS)

    Ashraf, M.; Sarim, M.; Shaikh, A.B.

    2017-01-01

    Image segmentation has become a widely studied research problem in image processing. There exist different graph based solutions for interactive image segmentation but the domain of image segmentation still needs persistent improvements. The segmentation quality of existing techniques generally depends on the manual input provided in beginning, therefore, these algorithms may not produce quality segmentation with initial seed labels provided by a novice user. In this work we investigated the use of cellular automata in image segmentation and proposed a new algorithm that follows a cellular automaton in label propagation. It incorporates both the pixel's local and global information in the segmentation process. We introduced the novel global constraints in automata evolution rules; hence proposed scheme of automata evolution is more effective than the automata based earlier evolution schemes. Global constraints are also effective in deceasing the sensitivity towards small changes made in manual input; therefore proposed approach is less dependent on label seed marks. It can produce the quality segmentation with modest user efforts. Segmentation results indicate that the proposed algorithm performs better than the earlier segmentation techniques. (author)

  14. A region-based segmentation method for ultrasound images in HIFU therapy

    International Nuclear Information System (INIS)

    Zhang, Dong; Liu, Yu; Yang, Yan; Xu, Menglong; Yan, Yu; Qin, Qianqing

    2016-01-01

    Purpose: Precisely and efficiently locating a tumor with less manual intervention in ultrasound-guided high-intensity focused ultrasound (HIFU) therapy is one of the keys to guaranteeing the therapeutic result and improving the efficiency of the treatment. The segmentation of ultrasound images has always been difficult due to the influences of speckle, acoustic shadows, and signal attenuation as well as the variety of tumor appearance. The quality of HIFU guidance images is even poorer than that of conventional diagnostic ultrasound images because the ultrasonic probe used for HIFU guidance usually obtains images without making contact with the patient’s body. Therefore, the segmentation becomes more difficult. To solve the segmentation problem of ultrasound guidance image in the treatment planning procedure for HIFU therapy, a novel region-based segmentation method for uterine fibroids in HIFU guidance images is proposed. Methods: Tumor partitioning in HIFU guidance image without manual intervention is achieved by a region-based split-and-merge framework. A new iterative multiple region growing algorithm is proposed to first split the image into homogenous regions (superpixels). The features extracted within these homogenous regions will be more stable than those extracted within the conventional neighborhood of a pixel. The split regions are then merged by a superpixel-based adaptive spectral clustering algorithm. To ensure the superpixels that belong to the same tumor can be clustered together in the merging process, a particular construction strategy for the similarity matrix is adopted for the spectral clustering, and the similarity matrix is constructed by taking advantage of a combination of specifically selected first-order and second-order texture features computed from the gray levels and the gray level co-occurrence matrixes, respectively. The tumor region is picked out automatically from the background regions by an algorithm according to a priori

  15. A region-based segmentation method for ultrasound images in HIFU therapy

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Dong, E-mail: dongz@whu.edu.cn; Liu, Yu; Yang, Yan; Xu, Menglong; Yan, Yu [School of Physics and Technology, Wuhan University, Wuhan 430072 (China); Qin, Qianqing [State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072 (China)

    2016-06-15

    Purpose: Precisely and efficiently locating a tumor with less manual intervention in ultrasound-guided high-intensity focused ultrasound (HIFU) therapy is one of the keys to guaranteeing the therapeutic result and improving the efficiency of the treatment. The segmentation of ultrasound images has always been difficult due to the influences of speckle, acoustic shadows, and signal attenuation as well as the variety of tumor appearance. The quality of HIFU guidance images is even poorer than that of conventional diagnostic ultrasound images because the ultrasonic probe used for HIFU guidance usually obtains images without making contact with the patient’s body. Therefore, the segmentation becomes more difficult. To solve the segmentation problem of ultrasound guidance image in the treatment planning procedure for HIFU therapy, a novel region-based segmentation method for uterine fibroids in HIFU guidance images is proposed. Methods: Tumor partitioning in HIFU guidance image without manual intervention is achieved by a region-based split-and-merge framework. A new iterative multiple region growing algorithm is proposed to first split the image into homogenous regions (superpixels). The features extracted within these homogenous regions will be more stable than those extracted within the conventional neighborhood of a pixel. The split regions are then merged by a superpixel-based adaptive spectral clustering algorithm. To ensure the superpixels that belong to the same tumor can be clustered together in the merging process, a particular construction strategy for the similarity matrix is adopted for the spectral clustering, and the similarity matrix is constructed by taking advantage of a combination of specifically selected first-order and second-order texture features computed from the gray levels and the gray level co-occurrence matrixes, respectively. The tumor region is picked out automatically from the background regions by an algorithm according to a priori

  16. Mycobacterium saopaulense sp. nov., a rapidly growing mycobacterium closely related to members of the Mycobacterium chelonae--Mycobacterium abscessus group.

    Science.gov (United States)

    Nogueira, Christiane Lourenço; Whipps, Christopher M; Matsumoto, Cristianne Kayoko; Chimara, Erica; Droz, Sara; Tortoli, Enrico; de Freitas, Denise; Cnockaert, Margo; Palomino, Juan Carlos; Martin, Anandi; Vandamme, Peter; Leão, Sylvia Cardoso

    2015-12-01

    Five isolates of non-pigmented, rapidly growing mycobacteria were isolated from three patients and,in an earlier study, from zebrafish. Phenotypic and molecular tests confirmed that these isolates belong to the Mycobacterium chelonae-Mycobacterium abscessus group, but they could not be confidently assigned to any known species of this group. Phenotypic analysis and biochemical tests were not helpful for distinguishing these isolates from other members of the M. chelonae–M.abscessus group. The isolates presented higher drug resistance in comparison with other members of the group, showing susceptibility only to clarithromycin. The five isolates showed a unique PCR restriction analysis pattern of the hsp65 gene, 100 % similarity in 16S rRNA gene and hsp65 sequences and 1-2 nt differences in rpoB and internal transcribed spacer (ITS) sequences.Phylogenetic analysis of a concatenated dataset including 16S rRNA gene, hsp65, and rpoB sequences from type strains of more closely related species placed the five isolates together, as a distinct lineage from previously described species, suggesting a sister relationship to a group consisting of M. chelonae, Mycobacterium salmoniphilum, Mycobacterium franklinii and Mycobacterium immunogenum. DNA–DNA hybridization values .70 % confirmed that the five isolates belong to the same species, while values ,70 % between one of the isolates and the type strains of M. chelonae and M. abscessus confirmed that the isolates belong to a distinct species. The polyphasic characterization of these isolates, supported by DNA–DNA hybridization results,demonstrated that they share characteristics with M. chelonae–M. abscessus members, butconstitute a different species, for which the name Mycobacterium saopaulense sp. nov. is proposed. The type strain is EPM10906T (5CCUG 66554T5LMG 28586T5INCQS 0733T).

  17. International EUREKA: Initialization Segment

    International Nuclear Information System (INIS)

    1982-02-01

    The Initialization Segment creates the starting description of the uranium market. The starting description includes the international boundaries of trade, the geologic provinces, resources, reserves, production, uranium demand forecasts, and existing market transactions. The Initialization Segment is designed to accept information of various degrees of detail, depending on what is known about each region. It must transform this information into a specific data structure required by the Market Segment of the model, filling in gaps in the information through a predetermined sequence of defaults and built in assumptions. A principal function of the Initialization Segment is to create diagnostic messages indicating any inconsistencies in data and explaining which assumptions were used to organize the data base. This permits the user to manipulate the data base until such time the user is satisfied that all the assumptions used are reasonable and that any inconsistencies are resolved in a satisfactory manner

  18. Image Segmentation Using Minimum Spanning Tree

    Science.gov (United States)

    Dewi, M. P.; Armiati, A.; Alvini, S.

    2018-04-01

    This research aim to segmented the digital image. The process of segmentation is to separate the object from the background. So the main object can be processed for the other purposes. Along with the development of technology in digital image processing application, the segmentation process becomes increasingly necessary. The segmented image which is the result of the segmentation process should accurate due to the next process need the interpretation of the information on the image. This article discussed the application of minimum spanning tree on graph in segmentation process of digital image. This method is able to separate an object from the background and the image will change to be the binary images. In this case, the object that being the focus is set in white, while the background is black or otherwise.

  19. Surgically assisted rapid maxillary expansion in adults.

    Science.gov (United States)

    Pogrel, M A; Kaban, L B; Vargervik, K; Baumrind, S

    1992-01-01

    Twelve adults with maxillary width discrepancy of greater than 5 mm were treated by surgically assisted rapid maxillary expansion. The procedure consisted of bilateral zygomatic buttress and midpalatal osteotomies combined with the use of a tooth-borne orthopedic device postoperatively. Mean palatal expansion of 7.5 mm (range of 6 to 13 mm), measured in the first molar region, was achieved within 3 weeks in all patients. Expansion remained stable during the 12-month study period, with a mean relapse for the entire group of 0.88 +/- 0.48 mm. Morbidity was limited to mild postoperative discomfort. The results of this preliminary study indicated that surgically assisted rapid maxillary expansion is a safe, simple, and reliable procedure for achieving a permanent increase in skeletal maxillary width in adults. Further study is necessary to document the three-dimensional movements of the maxillary segments and long-term stability of the skeletal and dental changes.

  20. Morphotectonic Index Analysis as an Indicator of Neotectonic Segmentation of the Nicoya Peninsula, Costa Rica

    Science.gov (United States)

    Morrish, S.; Marshall, J. S.

    2013-12-01

    The Nicoya Peninsula lies within the Costa Rican forearc where the Cocos plate subducts under the Caribbean plate at ~8.5 cm/yr. Rapid plate convergence produces frequent large earthquakes (~50yr recurrence interval) and pronounced crustal deformation (0.1-2.0m/ky uplift). Seven uplifted segments have been identified in previous studies using broad geomorphic surfaces (Hare & Gardner 1984) and late Quaternary marine terraces (Marshall et al. 2010). These surfaces suggest long term net uplift and segmentation of the peninsula in response to contrasting domains of subducting seafloor (EPR, CNS-1, CNS-2). In this study, newer 10m contour digital topographic data (CENIGA- Terra Project) will be used to characterize and delineate this segmentation using morphotectonic analysis of drainage basins and correlation of fluvial terrace/ geomorphic surface elevations. The peninsula has six primary watersheds which drain into the Pacific Ocean; the Río Andamojo, Río Tabaco, Río Nosara, Río Ora, Río Bongo, and Río Ario which range in area from 200 km2 to 350 km2. The trunk rivers follow major lineaments that define morphotectonic segment boundaries and in turn their drainage basins are bisected by them. Morphometric analysis of the lower (1st and 2nd) order drainage basins will provide insight into segmented tectonic uplift and deformation by comparing values of drainage basin asymmetry, stream length gradient, and hypsometry with respect to margin segmentation and subducting seafloor domain. A general geomorphic analysis will be conducted alongside the morphometric analysis to map previously recognized (Morrish et al. 2010) but poorly characterized late Quaternary fluvial terraces. Stream capture and drainage divide migration are common processes throughout the peninsula in response to the ongoing deformation. Identification and characterization of basin piracy throughout the peninsula will provide insight into the history of landscape evolution in response to

  1. Mild toxic anterior segment syndrome mimicking delayed onset toxic anterior segment syndrome after cataract surgery

    Directory of Open Access Journals (Sweden)

    Su-Na Lee

    2014-01-01

    Full Text Available Toxic anterior segment syndrome (TASS is an acute sterile postoperative anterior segment inflammation that may occur after anterior segment surgery. I report herein a case that developed mild TASS in one eye after bilateral uneventful cataract surgery, which was masked during early postoperative period under steroid eye drop and mimicking delayed onset TASS after switching to weaker steroid eye drop.

  2. Scorpion image segmentation system

    Science.gov (United States)

    Joseph, E.; Aibinu, A. M.; Sadiq, B. A.; Bello Salau, H.; Salami, M. J. E.

    2013-12-01

    Death as a result of scorpion sting has been a major public health problem in developing countries. Despite the high rate of death as a result of scorpion sting, little report exists in literature of intelligent device and system for automatic detection of scorpion. This paper proposed a digital image processing approach based on the floresencing characteristics of Scorpion under Ultra-violet (UV) light for automatic detection and identification of scorpion. The acquired UV-based images undergo pre-processing to equalize uneven illumination and colour space channel separation. The extracted channels are then segmented into two non-overlapping classes. It has been observed that simple thresholding of the green channel of the acquired RGB UV-based image is sufficient for segmenting Scorpion from other background components in the acquired image. Two approaches to image segmentation have also been proposed in this work, namely, the simple average segmentation technique and K-means image segmentation. The proposed algorithm has been tested on over 40 UV scorpion images obtained from different part of the world and results obtained show an average accuracy of 97.7% in correctly classifying the pixel into two non-overlapping clusters. The proposed 1system will eliminate the problem associated with some of the existing manual approaches presently in use for scorpion detection.

  3. Brain Tumor Image Segmentation in MRI Image

    Science.gov (United States)

    Peni Agustin Tjahyaningtijas, Hapsari

    2018-04-01

    Brain tumor segmentation plays an important role in medical image processing. Treatment of patients with brain tumors is highly dependent on early detection of these tumors. Early detection of brain tumors will improve the patient’s life chances. Diagnosis of brain tumors by experts usually use a manual segmentation that is difficult and time consuming because of the necessary automatic segmentation. Nowadays automatic segmentation is very populer and can be a solution to the problem of tumor brain segmentation with better performance. The purpose of this paper is to provide a review of MRI-based brain tumor segmentation methods. There are number of existing review papers, focusing on traditional methods for MRI-based brain tumor image segmentation. this paper, we focus on the recent trend of automatic segmentation in this field. First, an introduction to brain tumors and methods for brain tumor segmentation is given. Then, the state-of-the-art algorithms with a focus on recent trend of full automatic segmentaion are discussed. Finally, an assessment of the current state is presented and future developments to standardize MRI-based brain tumor segmentation methods into daily clinical routine are addressed.

  4. A rapid assessment of avoidable blindness in Southern Zambia.

    Directory of Open Access Journals (Sweden)

    Robert Lindfield

    Full Text Available INTRODUCTION: A rapid assessment of avoidable blindness (RAAB was conducted in Southern Zambia to establish the prevalence and causes of blindness in order to plan effective services and advocate for support for eye care to achieve the goals of VISION 2020: the right to sight. METHODS: Cluster randomisation was used to select villages in the survey area. These were further subdivided into segments. One segment was selected randomly and a survey team moved from house to house examining everyone over the age of 50 years. Each individual received a visual acuity assessment and simple ocular examination. Data was recorded on a standard proforma and entered into an established software programme for analysis. RESULTS: 2.29% of people over the age of 50 were found to be blind (VA <3/60 in the better eye with available correction. The major cause of blindness was cataract (47.2% with posterior segment disease being the next main cause (18.8%. 113 eyes had received cataract surgery with 30.1% having a poor outcome (VA <6/60 following surgery. Cataract surgical coverage showed that men (72% received more surgery than women (65%. DISCUSSION: The results from the RAAB survey in Zambia were very similar to the results from a similar survey in Malawi, where the main cause of blindness was cataract but posterior segment disease was also a significant contributor. Blindness in this part of Zambia is mainly avoidable and there is a need for comprehensive eye care services that can address both cataract and posterior segment disease in the population if the aim of VISION 2020 is to be achieved. Services should focus on quality and gender equity of cataract surgery.

  5. Hospital process intervals, not EMS time intervals, are the most important predictors of rapid reperfusion in EMS Patients with ST-segment elevation myocardial infarction.

    Science.gov (United States)

    Clark, Carol Lynn; Berman, Aaron D; McHugh, Ann; Roe, Edward Jedd; Boura, Judith; Swor, Robert A

    2012-01-01

    To assess the relationship of emergency medical services (EMS) intervals and internal hospital intervals to the rapid reperfusion of patients with ST-segment elevation myocardial infarction (STEMI). We performed a secondary analysis of a prospectively collected database of STEMI patients transported to a large academic community hospital between January 1, 2004, and December 31, 2009. EMS and hospital data intervals included EMS scene time, transport time, hospital arrival to myocardial infarction (MI) team activation (D2Page), page to catheterization laboratory arrival (P2Lab), and catheterization laboratory arrival to reperfusion (L2B). We used two outcomes: EMS scene arrival to reperfusion (S2B) ≤90 minutes and hospital arrival to reperfusion (D2B) ≤90 minutes. Means and proportions are reported. Pearson chi-square and multivariate regression were used for analysis. During the study period, we included 313 EMS-transported STEMI patients with 298 (95.2%) MI team activations. Of these STEMI patients, 295 (94.2%) were taken to the cardiac catheterization laboratory and 244 (78.0%) underwent percutaneous coronary intervention (PCI). For the patients who underwent PCI, 127 (52.5%) had prehospital EMS activation, 202 (82.8%) had D2B ≤90 minutes, and 72 (39%) had S2B ≤90 minutes. In a multivariate analysis, hospital processes EMS activation (OR 7.1, 95% CI 2.7, 18.4], Page to Lab [6.7, 95% CI 2.3, 19.2] and Lab arrival to Reperfusion [18.5, 95% CI 6.1, 55.6]) were the most important predictors of Scene to Balloon ≤ 90 minutes. EMS scene and transport intervals also had a modest association with rapid reperfusion (OR 0.85, 95% CI 0.78, 0.93 and OR 0.89, 95% CI 0.83, 0.95, respectively). In a secondary analysis, Hospital processes (Door to Page [OR 44.8, 95% CI 8.6, 234.4], Page 2 Lab [OR 5.4, 95% CI 1.9, 15.3], and Lab arrival to Reperfusion [OR 14.6 95% CI 2.5, 84.3]), but not EMS scene and transport intervals were the most important predictors D2B ≤90

  6. Colour application on mammography image segmentation

    Science.gov (United States)

    Embong, R.; Aziz, N. M. Nik Ab.; Karim, A. H. Abd; Ibrahim, M. R.

    2017-09-01

    The segmentation process is one of the most important steps in image processing and computer vision since it is vital in the initial stage of image analysis. Segmentation of medical images involves complex structures and it requires precise segmentation result which is necessary for clinical diagnosis such as the detection of tumour, oedema, and necrotic tissues. Since mammography images are grayscale, researchers are looking at the effect of colour in the segmentation process of medical images. Colour is known to play a significant role in the perception of object boundaries in non-medical colour images. Processing colour images require handling more data, hence providing a richer description of objects in the scene. Colour images contain ten percent (10%) additional edge information as compared to their grayscale counterparts. Nevertheless, edge detection in colour image is more challenging than grayscale image as colour space is considered as a vector space. In this study, we implemented red, green, yellow, and blue colour maps to grayscale mammography images with the purpose of testing the effect of colours on the segmentation of abnormality regions in the mammography images. We applied the segmentation process using the Fuzzy C-means algorithm and evaluated the percentage of average relative error of area for each colour type. The results showed that all segmentation with the colour map can be done successfully even for blurred and noisy images. Also the size of the area of the abnormality region is reduced when compare to the segmentation area without the colour map. The green colour map segmentation produced the smallest percentage of average relative error (10.009%) while yellow colour map segmentation gave the largest percentage of relative error (11.367%).

  7. What are Segments in Google Analytics

    Science.gov (United States)

    Segments find all sessions that meet a specific condition. You can then apply this segment to any report in Google Analytics (GA). Segments are a way of identifying sessions and users while filters identify specific events, like pageviews.

  8. Segmentation-less Digital Rock Physics

    Science.gov (United States)

    Tisato, N.; Ikeda, K.; Goldfarb, E. J.; Spikes, K. T.

    2017-12-01

    In the last decade, Digital Rock Physics (DRP) has become an avenue to investigate physical and mechanical properties of geomaterials. DRP offers the advantage of simulating laboratory experiments on numerical samples that are obtained from analytical methods. Potentially, DRP could allow sparing part of the time and resources that are allocated to perform complicated laboratory tests. Like classic laboratory tests, the goal of DRP is to estimate accurately physical properties of rocks like hydraulic permeability or elastic moduli. Nevertheless, the physical properties of samples imaged using micro-computed tomography (μCT) are estimated through segmentation of the μCT dataset. Segmentation proves to be a challenging and arbitrary procedure that typically leads to inaccurate estimates of physical properties. Here we present a novel technique to extract physical properties from a μCT dataset without the use of segmentation. We show examples in which we use segmentation-less method to simulate elastic wave propagation and pressure wave diffusion to estimate elastic properties and permeability, respectively. The proposed method takes advantage of effective medium theories and uses the density and the porosity that are measured in the laboratory to constrain the results. We discuss the results and highlight that segmentation-less DRP is more accurate than segmentation based DRP approaches and theoretical modeling for the studied rock. In conclusion, the segmentation-less approach here presented seems to be a promising method to improve accuracy and to ease the overall workflow of DRP.

  9. Segmentation, advertising and prices

    NARCIS (Netherlands)

    Galeotti, Andrea; Moraga González, José

    This paper explores the implications of market segmentation on firm competitiveness. In contrast to earlier work, here market segmentation is minimal in the sense that it is based on consumer attributes that are completely unrelated to tastes. We show that when the market is comprised by two

  10. Chromosome condensation and segmentation

    International Nuclear Information System (INIS)

    Viegas-Pequignot, E.M.

    1981-01-01

    Some aspects of chromosome condensation in mammalians -humans especially- were studied by means of cytogenetic techniques of chromosome banding. Two further approaches were adopted: a study of normal condensation as early as prophase, and an analysis of chromosome segmentation induced by physical (temperature and γ-rays) or chemical agents (base analogues, antibiotics, ...) in order to show out the factors liable to affect condensation. Here 'segmentation' means an abnormal chromosome condensation appearing systematically and being reproducible. The study of normal condensation was made possible by the development of a technique based on cell synchronization by thymidine and giving prophasic and prometaphasic cells. Besides, the possibility of inducing R-banding segmentations on these cells by BrdU (5-bromodeoxyuridine) allowed a much finer analysis of karyotypes. Another technique was developed using 5-ACR (5-azacytidine), it allowed to induce a segmentation similar to the one obtained using BrdU and identify heterochromatic areas rich in G-C bases pairs [fr

  11. Growing Region Segmentation Software (GRES) for quantitative magnetic resonance imaging of multiple sclerosis: intra- and inter-observer agreement variability: a comparison with manual contouring method

    International Nuclear Information System (INIS)

    Parodi, Roberto C.; Sardanelli, Francesco; Renzetti, Paolo; Rosso, Elisabetta; Losacco, Caterina; Ferrari, Alessandra; Levrero, Fabrizio; Pilot, Alberto; Inglese, Matilde; Mancardi, Giovanni L.

    2002-01-01

    Lesion area measurement in multiple sclerosis (MS) is one of the key points in evaluating the natural history and in monitoring the efficacy of treatments. This study was performed to check the intra- and inter-observer agreement variability of a locally developed Growing Region Segmentation Software (GRES), comparing them to those obtained using manual contouring (MC). From routine 1.5-T MRI study of clinically definite multiple sclerosis patients, 36 lesions seen on proton-density-weighted images (PDWI) and 36 enhancing lesion on Gd-DTPA-BMA-enhanced T1-weighted images (Gd-T1WI) were randomly chosen and were evaluated by three observers. The mean range of lesion size was 9.9-536.0 mm 2 on PDWI and 3.6-57.2 mm 2 on Gd-T1WI. The median intra- and inter-observer agreement were, respectively, 97.1 and 90.0% using GRES on PDWI, 81.0 and 70.0% using MC on PDWI, 88.8 and 80.0% using GRES on Gd-T1WI, and 85.8 and 70.0% using MC on Gd-T1WI. The intra- and inter-observer agreements were significantly greater for GRES compared with MC (P<0.0001 and P=0.0023, respectively) for PDWI, while no difference was found between GRES an MC for Gd-T1WI. The intra-observer variability for GRES was significantly lower on both PDWI (P=0.0001) and Gd-T1WI (P=0.0067), whereas for MC the same result was found only for PDWI (P=0.0147). These data indicate that GRES reduces both the intra- and the inter-observer variability in assessing the area of MS lesions on PDWI and may prove useful in multicentre studies. (orig.)

  12. Track segment synthesis method for NTA film

    International Nuclear Information System (INIS)

    Kumazawa, Shigeru

    1980-03-01

    A method is presented for synthesizing track segments extracted from a gray-level digital picture of NTA film in automatic counting system. In order to detect each track in an arbitrary direction, even if it has some gaps, as a set of the track segments, the method links extracted segments along the track, in succession, to the linked track segments, according to whether each extracted segment bears a similarity of direction to the track or not and whether it is connected with the linked track segments or not. In the case of a large digital picture, the method is applied to each subpicture, which is a strip of the picture, and then concatenates subsets of track segments linked at each subpicture as a set of track segments belonging to a track. The method was applied to detecting tracks in various directions over the eight 364 x 40-pixel subpictures with the gray scale of 127/pixel (picture element) of the microphotograph of NTA film. It was proved to be able to synthesize track segments correctly for every track in the picture. (author)

  13. Ethanol synthesis and aerobic respiration in the laboratory by leader segments of Douglas-fir seedlings from winter and spring.

    Science.gov (United States)

    Joseph, Gladwin; Kelsey, Rick G

    2004-05-01

    Stem segments from terminal leaders of Douglas-fir, Pseudotsuga menziesii (Mirb.) Franco, seedlings were sampled in mid-December when cambial cells were dormant. The residual, debudded leaders were resampled again in early May when the cambium was metabolically active. May stems had higher constitutive ethanol concentrations than December stems. This was not the result of cambial hypoxia generated by rapid spring respiration rates, because when aerobic respiration was stimulated by incubating the stems in air at 30 degrees C ethanol production was induced in December, but not in May. Rapid respiration rates at 30 degrees C may have depleted O(2) supplies and induced ethanol production in December stems because dormant, thick-walled cambial cells may be less permeable to CO(2) and O(2), compared with metabolically active, thin-walled cambial cells in May. December stem segments incubated in a N(2) atmosphere at 30 degrees C synthesized 1.8 times more ethanol than segments from May, most likely because spring growth had reduced the soluble sugars available for fermentation. CO(2) efflux from May stems (after 5.5 h of incubation at 30 degrees C) was equal to December stems per unit volume, but greater than December stems per unit surface area. N(2)-induced ethanol concentrations were positively related with CO(2) efflux per unit volume, indicating that rapidly respiring leaders can maintain rapid fermentation rates, provided soluble sugars are readily available. N(2)-induced ethanol and CO(2) efflux per unit volume declined with increasing leader diameter in both seasons, whereas there were no relationships between CO(2) efflux per unit surface area and diameter. Cambium physiology and phenology influence the induction of fermentation and concentrations of ethanol produced in terminal leaders of Douglas-fir, and probably other conifers as well. This needs to be considered when comparing fermentation among species, or comparing individuals from different seasons, or

  14. A travel clinic in your office: grow your practice and protect international travelers.

    Science.gov (United States)

    Kirsch, Michael

    2009-01-01

    Medical practices today face economic challenges from declining reimbursements and rising overhead costs. Physicians need to develop new income sources to invigorate their practices and remain viable. Travel medicine-advising and immunizing international travelers-is a rapidly growing specialty in the United States that generates substantial cash reimbursements and professional satisfaction. Travel Clinics of America, a physician-operated company, specializes in helping physicians to incorporate travel medicine into their existing practices.

  15. Growing Degree Vegetation Production Index (GDVPI): A Novel and Data-Driven Approach to Delimit Season Cycles

    Science.gov (United States)

    Graham, W. D.; Spruce, J.; Ross, K. W.; Gasser, J.; Grulke, N.

    2014-12-01

    Growing Degree Vegetation Production Index (GDVPI) is a parametric approach to delimiting vegetation seasonal growth and decline cycles using incremental growing degree days (GDD), and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) 8-day composite cumulative integral data. We obtain a specific location's daily minimum and maximum temperatures from the nearest National Oceanic and Atmospheric Administration (NOAA) weather stations posted on the National Climate Data Center (NCDC) Climate Data Online (CDO) archive and compute GDD. The date range for this study is January 1, 2000 through December 31, 2012. We employ a novel process, a repeating logistic product (RLP), to compensate for short-term weather variability and data drops from the recording stations and fit a curve to the median daily GDD values, adjusting for asymmetry, amplitude, and phase shift that minimize the sum of squared errors when comparing the observed and predicted GDD. The resulting curve, here referred to as the surrogate GDD, is the time-temperature phasing parameter used to convert Cartesian NDVI values into polar coordinate pairs, multiplying the NDVI values as the radial by the cosine and sine of the surrogate GDD as the angular. Depending on the vegetation type and the original NDVI curve, the polar NDVI curve may be nearly circular, kidney-shaped, or pear-shaped in the case of conifers, deciduous, or agriculture, respectively. We examine the points of tangency about the polar coordinate NDVI curve, identifying values of 1, 0, -1, or infinity, as each of these represent natural inflection points. Lines connecting the origin to each tangent point illustrate and quantify the parametrically segmentation of the growing season based on the GDD and NDVI ostensible dependency. Furthermore, the area contained by each segment represents the apparent vegetation production. A particular benefit is that the inflection points are determined

  16. High cut-off haemodialysis induces remission of recurrent idiopathic focal segmental glomerulosclerosis after renal transplantation but is no alternative to plasmapheresis

    NARCIS (Netherlands)

    I. Noorlander (Iris); D.A. Hesselink (Dennis); M. Wabbijn (Marike); M.G.H. Betjes (Michiel)

    2011-01-01

    textabstractA 26-year-old male experienced a recurrence of idiopathic focal segmental glomerulosclerosis (iFSGS) after his second renal transplant. Reduction of proteinuria was rapidly induced by plasmapheresis (PP) and the patient has remained in remission with a once-weekly PP regimen, which has

  17. A multi-atlas based method for automated anatomical rat brain MRI segmentation and extraction of PET activity.

    Science.gov (United States)

    Lancelot, Sophie; Roche, Roxane; Slimen, Afifa; Bouillot, Caroline; Levigoureux, Elise; Langlois, Jean-Baptiste; Zimmer, Luc; Costes, Nicolas

    2014-01-01

    Preclinical in vivo imaging requires precise and reproducible delineation of brain structures. Manual segmentation is time consuming and operator dependent. Automated segmentation as usually performed via single atlas registration fails to account for anatomo-physiological variability. We present, evaluate, and make available a multi-atlas approach for automatically segmenting rat brain MRI and extracting PET activies. High-resolution 7T 2DT2 MR images of 12 Sprague-Dawley rat brains were manually segmented into 27-VOI label volumes using detailed protocols. Automated methods were developed with 7/12 atlas datasets, i.e. the MRIs and their associated label volumes. MRIs were registered to a common space, where an MRI template and a maximum probability atlas were created. Three automated methods were tested: 1/registering individual MRIs to the template, and using a single atlas (SA), 2/using the maximum probability atlas (MP), and 3/registering the MRIs from the multi-atlas dataset to an individual MRI, propagating the label volumes and fusing them in individual MRI space (propagation & fusion, PF). Evaluation was performed on the five remaining rats which additionally underwent [18F]FDG PET. Automated and manual segmentations were compared for morphometric performance (assessed by comparing volume bias and Dice overlap index) and functional performance (evaluated by comparing extracted PET measures). Only the SA method showed volume bias. Dice indices were significantly different between methods (PF>MP>SA). PET regional measures were more accurate with multi-atlas methods than with SA method. Multi-atlas methods outperform SA for automated anatomical brain segmentation and PET measure's extraction. They perform comparably to manual segmentation for FDG-PET quantification. Multi-atlas methods are suitable for rapid reproducible VOI analyses.

  18. Fruit-Growing in Latvia – Industry and Science

    Directory of Open Access Journals (Sweden)

    Kaufmane Edīte

    2017-06-01

    Full Text Available In all times, fruit trees for family use have been grown at Latvian farms. Yet these fruits obtained market value only after the land ownership reform in 19th century. This facilitated rapid area increase of different fruit crops, allowing supply with fruits not only the local market, but also for export to the largest cities of Russia. Especially fast development of fruit-growing was observed during the first independent republic (1919–1940. The demand for planting material increased, and plants were imported from Western Europe. Choice of unsuitable cultivars and rootstocks was the main reason of the massive orchard area loss during the following severe winters. After the Second World War, the Soviet powers supported only the establishment of large orchards for processing needs, 200-300 ha, which were unsuitable for the Latvian climate and terrain. At the same time, numbers of allotment gardens rapidly increased and part of their produce was sold also on the market. After regaining of independence and private property, interest in fresh fruit and berry production for market, as well as processing, renewed. It was hindered by lack of continuity in experience and knowledge. Diversity of terrain, soils and climate all demand considerate choice of suitable orchard location and cultivars. Direct use of foreign experience often led to failure. At present, development of the fruit industry is most of all hindered by lack of qualified specialists of different levels, which does not allow to establish an appropriate consulting system. Cooperation of growers for easier marketing also is developing too slowly. Insufficient economic and market research does not allow to balance the demand with increase of plantation area, especially for large-scale processing and export, so strategic guidance of the fruit industry is not possible. Development of fruit-growing is hindered also by a lack of continuous long-term support to horticultural science. As a

  19. LIFE-STYLE SEGMENTATION WITH TAILORED INTERVIEWING

    NARCIS (Netherlands)

    KAMAKURA, WA; WEDEL, M

    The authors present a tailored interviewing procedure for life-style segmentation. The procedure assumes that a life-style measurement instrument has been designed. A classification of a sample of consumers into life-style segments is obtained using a latent-class model. With these segments, the

  20. Segmented rail linear induction motor

    Science.gov (United States)

    Cowan, Jr., Maynard; Marder, Barry M.

    1996-01-01

    A segmented rail linear induction motor has a segmented rail consisting of a plurality of nonferrous electrically conductive segments aligned along a guideway. The motor further includes a carriage including at least one pair of opposed coils fastened to the carriage for moving the carriage. A power source applies an electric current to the coils to induce currents in the conductive surfaces to repel the coils from adjacent edges of the conductive surfaces.

  1. Deformable segmentation via sparse shape representation.

    Science.gov (United States)

    Zhang, Shaoting; Zhan, Yiqiang; Dewan, Maneesh; Huang, Junzhou; Metaxas, Dimitris N; Zhou, Xiang Sean

    2011-01-01

    Appearance and shape are two key elements exploited in medical image segmentation. However, in some medical image analysis tasks, appearance cues are weak/misleading due to disease/artifacts and often lead to erroneous segmentation. In this paper, a novel deformable model is proposed for robust segmentation in the presence of weak/misleading appearance cues. Owing to the less trustable appearance information, this method focuses on the effective shape modeling with two contributions. First, a shape composition method is designed to incorporate shape prior on-the-fly. Based on two sparsity observations, this method is robust to false appearance information and adaptive to statistically insignificant shape modes. Second, shape priors are modeled and used in a hierarchical fashion. More specifically, by using affinity propagation method, our deformable surface is divided into multiple partitions, on which local shape models are built independently. This scheme facilitates a more compact shape prior modeling and hence a more robust and efficient segmentation. Our deformable model is applied on two very diverse segmentation problems, liver segmentation in PET-CT images and rodent brain segmentation in MR images. Compared to state-of-art methods, our method achieves better performance in both studies.

  2. Segmenting hospitals for improved management strategy.

    Science.gov (United States)

    Malhotra, N K

    1989-09-01

    The author presents a conceptual framework for the a priori and clustering-based approaches to segmentation and evaluates them in the context of segmenting institutional health care markets. An empirical study is reported in which the hospital market is segmented on three state-of-being variables. The segmentation approach also takes into account important organizational decision-making variables. The sophisticated Thurstone Case V procedure is employed. Several marketing implications for hospitals, other health care organizations, hospital suppliers, and donor publics are identified.

  3. On the Modelling of Creative Behavior,

    Science.gov (United States)

    1981-11-01

    growing consensus that AI should be concerned with intelligence, not uniquely with human intelligence [1]. This consensus has cleared the way for a...34paging" rapidly growing data-structures to disk. By contrast, the line-segments generated in the drawing of a single animal--leaving aside the...assumptions. Since the "absolutely correct representation" of a position is, like Thurber’s unicorn , a mythical animal, I may seem to be arguing that

  4. Three-Dimensional Evaluation of the Upper Airway Morphological Changes in Growing Patients with Skeletal Class III Malocclusion Treated by Protraction Headgear and Rapid Palatal Expansion: A Comparative Research.

    Directory of Open Access Journals (Sweden)

    Xueling Chen

    Full Text Available The aim of this study was to evaluate the morphological changes of upper airway after protraction headgear and rapid maxillary expansion (PE treatment in growing patients with Class III malocclusion and maxillary skeletal deficiency compared with untreated Class III patients by cone-beam computed tomography (CBCT.Thirty growing patients who have completed PE therapy were included in PE group. The control group (n = 30 was selected from the growing untreated patients with the same diagnosis. The CBCT scans of the pre-treatment (T1 and post-treatment (T2 of PE group and the control group were collected. Reconstruction and registration of the 3D models of T1 and T2 were completed. By comparing the data obtained from T1, T2 and control group, the morphological changes of the upper airway during the PE treatment were evaluated.Comparing with the data from T1 group, the subspinale (A of maxilla and the upper incisor (UI of the T2 group were moved in the anterior direction. The gnathion (Gn of mandible was moved in the posterior-inferior direction. The displacement of the hyoid bone as well as the length and width of dental arch showed significant difference. The volume and mean cross-sectional area of nasopharynx, velopharynx and glossopharynx region showed significant difference. The largest anteroposterior/the largest lateral (AP/LR ratios of the velopharynx and glossopharynx were increased, but the AP/LR ratio of the hypopharynx was decreased. In addition, the length and width of the maxillary dental arch, the displacement of the hyoid bone, the volume of nasopharynx and velopharynx, and the AP/LR ratio of the hypopharynx and velopharynx showed significant difference between the data from control and T2 group.The PE treatment of Class III malocclusion with maxillary skeletal hypoplasia leads to a significant increase in the volume of nasopharynx and velopharynx.

  5. Review of segmentation process in consumer markets

    Directory of Open Access Journals (Sweden)

    Veronika Jadczaková

    2013-01-01

    Full Text Available Although there has been a considerable debate on market segmentation over five decades, attention was merely devoted to single stages of the segmentation process. In doing so, stages as segmentation base selection or segments profiling have been heavily covered in the extant literature, whereas stages as implementation of the marketing strategy or market definition were of a comparably lower interest. Capitalizing on this shortcoming, this paper strives to close the gap and provide each step of the segmentation process with equal treatment. Hence, the objective of this paper is two-fold. First, a snapshot of the segmentation process in a step-by-step fashion will be provided. Second, each step (where possible will be evaluated on chosen criteria by means of description, comparison, analysis and synthesis of 32 academic papers and 13 commercial typology systems. Ultimately, the segmentation stages will be discussed with empirical findings prevalent in the segmentation studies and last but not least suggestions calling for further investigation will be presented. This seven-step-framework may assist when segmenting in practice allowing for more confidential targeting which in turn might prepare grounds for creating of a differential advantage.

  6. Online Speech/Music Segmentation Based on the Variance Mean of Filter Bank Energy

    Directory of Open Access Journals (Sweden)

    Zdravko Kačič

    2009-01-01

    Full Text Available This paper presents a novel feature for online speech/music segmentation based on the variance mean of filter bank energy (VMFBE. The idea that encouraged the feature's construction is energy variation in a narrow frequency sub-band. The energy varies more rapidly, and to a greater extent for speech than for music. Therefore, an energy variance in such a sub-band is greater for speech than for music. The radio broadcast database and the BNSI broadcast news database were used for feature discrimination and segmentation ability evaluation. The calculation procedure of the VMFBE feature has 4 out of 6 steps in common with the MFCC feature calculation procedure. Therefore, it is a very convenient speech/music discriminator for use in real-time automatic speech recognition systems based on MFCC features, because valuable processing time can be saved, and computation load is only slightly increased. Analysis of the feature's speech/music discriminative ability shows an average error rate below 10% for radio broadcast material and it outperforms other features used for comparison, by more than 8%. The proposed feature as a stand-alone speech/music discriminator in a segmentation system achieves an overall accuracy of over 94% on radio broadcast material.

  7. Software Development for the Hobby-Eberly Telescope's Segment Alignment Maintenance System using LABView

    Science.gov (United States)

    Hall, Drew P.; Ly, William; Howard, Richard T.; Weir, John; Rakoczy, John; Roe, Fred (Technical Monitor)

    2002-01-01

    The software development for an upgrade to the Hobby-Eberly Telescope (HET) was done in LABView. In order to improve the performance of the HET at the McDonald Observatory, a closed-loop system had to be implemented to keep the mirror segments aligned during periods of observation. The control system, called the Segment Alignment Maintenance System (SAMs), utilized inductive sensors to measure the relative motions of the mirror segments. Software was developed in LABView to tie the sensors, operator interface, and mirror-control motors together. Developing the software in LABView allowed the system to be flexible, understandable, and able to be modified by the end users. Since LABView is built using block diagrams, the software naturally followed the designed control system's block and flow diagrams, and individual software blocks could be easily verified. LABView's many built-in display routines allowed easy visualization of diagnostic and health-monitoring data during testing. Also, since LABView is a multi-platform software package, different programmers could develop the code remotely on various types of machines. LABView s ease of use facilitated rapid prototyping and field testing. There were some unanticipated difficulties in the software development, but the use of LABView as the software "language" for the development of SAMs contributed to the overall success of the project.

  8. Online Speech/Music Segmentation Based on the Variance Mean of Filter Bank Energy

    Science.gov (United States)

    Kos, Marko; Grašič, Matej; Kačič, Zdravko

    2009-12-01

    This paper presents a novel feature for online speech/music segmentation based on the variance mean of filter bank energy (VMFBE). The idea that encouraged the feature's construction is energy variation in a narrow frequency sub-band. The energy varies more rapidly, and to a greater extent for speech than for music. Therefore, an energy variance in such a sub-band is greater for speech than for music. The radio broadcast database and the BNSI broadcast news database were used for feature discrimination and segmentation ability evaluation. The calculation procedure of the VMFBE feature has 4 out of 6 steps in common with the MFCC feature calculation procedure. Therefore, it is a very convenient speech/music discriminator for use in real-time automatic speech recognition systems based on MFCC features, because valuable processing time can be saved, and computation load is only slightly increased. Analysis of the feature's speech/music discriminative ability shows an average error rate below 10% for radio broadcast material and it outperforms other features used for comparison, by more than 8%. The proposed feature as a stand-alone speech/music discriminator in a segmentation system achieves an overall accuracy of over 94% on radio broadcast material.

  9. Primary focal segmental glomerulosclerosis recurring rapidly as collapsing glomerulopathy in a renal allograft recipient

    Directory of Open Access Journals (Sweden)

    Vinita Agrawal

    2017-01-01

    Full Text Available Recurrent focal segmental glomerulosclerosis (FSGS develops in about 30%-40% of patients of FSGS undergoing renal transplantation. We report a patient who received a live- related renal transplant for end-stage renal disease due to a primary FSGS (not otherwise specified in the native kidney and presented with graft dysfunction in the immediate posttransplant period. The first and the second biopsy showed no evidence of rejection or glomerular lesion. A repeat biopsy done on the 30th day revealed recurrent FSGS morphologically presenting as collapsing variant. The patient was found to have massive proteinuria. Electron microscopy done retrospectively showed glomerular foot process effacement even in the first biopsy. This case highlights the presence of an early minimal change disease-like phase in recurrent FSGS and the necessity of evaluation for proteinuria even in immediate and early posttransplant period. It also shows that different variants of FSGS may represent a spectrum of the same disease and suggests a likely role of a pathogenic circulating factor even in collapsing FSGS requiring further evaluation.

  10. Polyether based segmented copolymers with uniform aramid units

    NARCIS (Netherlands)

    Niesten, M.C.E.J.

    2000-01-01

    Segmented copolymers with short, glassy or crystalline hard segments and long, amorphous soft segments (multi-block copolymers) are thermoplastic elastomers (TPE’s). The hard segments form physical crosslinks for the amorphous (rubbery) soft segments. As a result, this type of materials combines

  11. Low-complexity atlas-based prostate segmentation by combining global, regional, and local metrics

    Energy Technology Data Exchange (ETDEWEB)

    Xie, Qiuliang; Ruan, Dan, E-mail: druan@mednet.ucla.edu [The Department of Radiation Oncology, University of California Los Angeles, California 90095 (United States)

    2014-04-15

    registrations, independent of atlas size, providing desirable scalability especially important for a large or growing atlas. When applied to prostate segmentation, the method achieved better performance to the state-of-the-art atlas-based approaches, with significant improvement in computation efficiency. The proposed rationale of utilizing jointly global, regional, and local metrics, based on the information characteristic and surrogate behavior for registration and fusion subtasks, can be extended naturally to similarity metrics beyond MSE, such as correlation or mutual information types.

  12. Three-dimensional segmentation and skeletonization to build an airway tree data structure for small animals

    International Nuclear Information System (INIS)

    Chaturvedi, Ashutosh; Lee, Zhenghong

    2005-01-01

    Quantitative analysis of intrathoracic airway tree geometry is important for objective evaluation of bronchial tree structure and function. Currently, there is more human data than small animal data on airway morphometry. In this study, we implemented a semi-automatic approach to quantitatively describe airway tree geometry by using high-resolution computed tomography (CT) images to build a tree data structure for small animals such as rats and mice. Silicon lung casts of the excised lungs from a canine and a mouse were used for micro-CT imaging of the airway trees. The programming language IDL was used to implement a 3D region-growing threshold algorithm for segmenting out the airway lung volume from the CT data. Subsequently, a fully-parallel 3D thinning algorithm was implemented in order to complete the skeletonization of the segmented airways. A tree data structure was then created and saved by parsing through the skeletonized volume using the Python programming language. Pertinent information such as the length of all airway segments was stored in the data structure. This approach was shown to be accurate and efficient for up to six generations for the canine lung cast and ten generations for the mouse lung cast

  13. Simultaneous hierarchical segmentation and vectorization of satellite images through combined data sampling and anisotropic triangulation

    Energy Technology Data Exchange (ETDEWEB)

    Grazzini, Jacopo [Los Alamos National Laboratory; Prasad, Lakshman [Los Alamos National Laboratory; Dillard, Scott [PNNL

    2010-10-21

    The automatic detection, recognition , and segmentation of object classes in remote sensed images is of crucial importance for scene interpretation and understanding. However, it is a difficult task because of the high variability of satellite data. Indeed, the observed scenes usually exhibit a high degree of complexity, where complexity refers to the large variety of pictorial representations of objects with the same semantic meaning and also to the extensive amount of available det.ails. Therefore, there is still a strong demand for robust techniques for automatic information extraction and interpretation of satellite images. In parallel, there is a growing interest in techniques that can extract vector features directly from such imagery. In this paper, we investigate the problem of automatic hierarchical segmentation and vectorization of multispectral satellite images. We propose a new algorithm composed of the following steps: (i) a non-uniform sampling scheme extracting most salient pixels in the image, (ii) an anisotropic triangulation constrained by the sampled pixels taking into account both strength and directionality of local structures present in the image, (iii) a polygonal grouping scheme merging, through techniques based on perceptual information , the obtained segments to a smaller quantity of superior vectorial objects. Besides its computational efficiency, this approach provides a meaningful polygonal representation for subsequent image analysis and/or interpretation.

  14. Unsupervised motion-based object segmentation refined by color

    Science.gov (United States)

    Piek, Matthijs C.; Braspenning, Ralph; Varekamp, Chris

    2003-06-01

    For various applications, such as data compression, structure from motion, medical imaging and video enhancement, there is a need for an algorithm that divides video sequences into independently moving objects. Because our focus is on video enhancement and structure from motion for consumer electronics, we strive for a low complexity solution. For still images, several approaches exist based on colour, but these lack in both speed and segmentation quality. For instance, colour-based watershed algorithms produce a so-called oversegmentation with many segments covering each single physical object. Other colour segmentation approaches exist which somehow limit the number of segments to reduce this oversegmentation problem. However, this often results in inaccurate edges or even missed objects. Most likely, colour is an inherently insufficient cue for real world object segmentation, because real world objects can display complex combinations of colours. For video sequences, however, an additional cue is available, namely the motion of objects. When different objects in a scene have different motion, the motion cue alone is often enough to reliably distinguish objects from one another and the background. However, because of the lack of sufficient resolution of efficient motion estimators, like the 3DRS block matcher, the resulting segmentation is not at pixel resolution, but at block resolution. Existing pixel resolution motion estimators are more sensitive to noise, suffer more from aperture problems or have less correspondence to the true motion of objects when compared to block-based approaches or are too computationally expensive. From its tendency to oversegmentation it is apparent that colour segmentation is particularly effective near edges of homogeneously coloured areas. On the other hand, block-based true motion estimation is particularly effective in heterogeneous areas, because heterogeneous areas improve the chance a block is unique and thus decrease the

  15. Marital Quality in Interracial Relationships: The Role of Sex Role Ideology and Perceived Fairness

    Science.gov (United States)

    Forry, Nicole D.; Leslie, Leigh A.; Letiecq, Bethany L.

    2007-01-01

    African American/White interracial couples are a rapidly growing segment of the population. However, little is known about factors related to marital quality for these couples. The authors examine the relationships between sex role ideology, perception of relationship unfairness, and marital quality among a sample of 76 married African…

  16. Mitigating Litigation for Adventure Recreation Operators: The Ski Safety Act

    Science.gov (United States)

    Brgoch, Shea; Lower, Leeann M.

    2017-01-01

    Adventure tourism is a rapidly growing segment of the tourism industry, which can be regarded as specific activities that are alluring for their uncertain and potentially dangerous outcomes. Risk-taking attitudes and behaviors may be common among adventure recreationists and increase the potential for litigation against recreation operators. In…

  17. Market Segmentation from a Behavioral Perspective

    Science.gov (United States)

    Wells, Victoria K.; Chang, Shing Wan; Oliveira-Castro, Jorge; Pallister, John

    2010-01-01

    A segmentation approach is presented using both traditional demographic segmentation bases (age, social class/occupation, and working status) and a segmentation by benefits sought. The benefits sought in this case are utilitarian and informational reinforcement, variables developed from the Behavioral Perspective Model (BPM). Using data from 1,847…

  18. Reduced trace element concentrations in fast-growing juvenile Atlantic salmon in natural streams.

    Science.gov (United States)

    Ward, Darren M; Nislow, Keith H; Chen, Celia Y; Folt, Carol L

    2010-05-01

    To assess the effect of rapid individual growth on trace element concentrations in fish, we measured concentrations of seven trace elements (As, Cd, Cs, Hg, Pb, Se, Zn) in stream-dwelling Atlantic salmon (Salmo salar) from 15 sites encompassing a 10-fold range in salmon growth. All salmon were hatched under uniform conditions, released into streams, and sampled approximately 120 days later for trace element analysis. For most elements, element concentrations in salmon tracked those in their prey. Fast-growing salmon had lower concentrations of all elements than slow growers, after accounting for prey concentrations. This pattern held for essential and nonessential elements, as well as elements that accumulate from food and those that can accumulate from water. At the sites with the fastest salmon growth, trace element concentrations in salmon were 37% (Cs) to 86% (Pb) lower than at sites where growth was suppressed. Given that concentrations were generally below levels harmful to salmon and that the pattern was consistent across all elements, we suggest that dilution of elements in larger biomass led to lower concentrations in fast-growing fish. Streams that foster rapid, efficient fish growth may produce fish with lower concentrations of elements potentially toxic for human and wildlife consumers.

  19. Computerized analysis of coronary artery disease: Performance evaluation of segmentation and tracking of coronary arteries in CT angiograms

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Chuan, E-mail: chuan@umich.edu; Chan, Heang-Ping; Chughtai, Aamer; Kuriakose, Jean; Agarwal, Prachi; Kazerooni, Ella A.; Hadjiiski, Lubomir M.; Patel, Smita; Wei, Jun [Department of Radiology, University of Michigan, Ann Arbor, Michigan 48109 (United States)

    2014-08-15

    Purpose: The authors are developing a computer-aided detection system to assist radiologists in analysis of coronary artery disease in coronary CT angiograms (cCTA). This study evaluated the accuracy of the authors’ coronary artery segmentation and tracking method which are the essential steps to define the search space for the detection of atherosclerotic plaques. Methods: The heart region in cCTA is segmented and the vascular structures are enhanced using the authors’ multiscale coronary artery response (MSCAR) method that performed 3D multiscale filtering and analysis of the eigenvalues of Hessian matrices. Starting from seed points at the origins of the left and right coronary arteries, a 3D rolling balloon region growing (RBG) method that adapts to the local vessel size segmented and tracked each of the coronary arteries and identifies the branches along the tracked vessels. The branches are queued and subsequently tracked until the queue is exhausted. With Institutional Review Board approval, 62 cCTA were collected retrospectively from the authors’ patient files. Three experienced cardiothoracic radiologists manually tracked and marked center points of the coronary arteries as reference standard following the 17-segment model that includes clinically significant coronary arteries. Two radiologists visually examined the computer-segmented vessels and marked the mistakenly tracked veins and noisy structures as false positives (FPs). For the 62 cases, the radiologists marked a total of 10191 center points on 865 visible coronary artery segments. Results: The computer-segmented vessels overlapped with 83.6% (8520/10191) of the center points. Relative to the 865 radiologist-marked segments, the sensitivity reached 91.9% (795/865) if a true positive is defined as a computer-segmented vessel that overlapped with at least 10% of the reference center points marked on the segment. When the overlap threshold is increased to 50% and 100%, the sensitivities were 86

  20. Skip segment Hirschsprung disease and Waardenburg syndrome

    OpenAIRE

    Gross, Erica R.; Geddes, Gabrielle C.; McCarrier, Julie A.; Jarzembowski, Jason A.; Arca, Marjorie J.

    2015-01-01

    Skip segment Hirschsprung disease describes a segment of ganglionated bowel between two segments of aganglionated bowel. It is a rare phenomenon that is difficult to diagnose. We describe a recent case of skip segment Hirschsprung disease in a neonate with a family history of Waardenburg syndrome and the genetic profile that was identified.

  1. Clinical effects of posterior pedicle screw fixation on spinal deformity in growing period: a report of 360 cases

    Directory of Open Access Journals (Sweden)

    Zheng-lei WANG

    2011-08-01

    Full Text Available Objective To observe the effect of a new kind of pedicle screw frame system with sliding terminus and locked middle segment on spinal deformity in growing period.Methods Three hundred and sixty patients in growing period were involved in the present study,and among them 82 were suffering from congenital scoliosis,218 idiopathic scoliosis and 60 kyphosis.All the patients were treated with the pedicle screw frame system with sliding terminus and locked middle segment.The treatment effects and postoperative complications were observed,and the Cobb angle before and after the operation was compared.Results The Cobb angle of 300 scoliosis patients was corrected from 53°±3° to 8°±2°,and the Cobb angle of 60 kyphosis patients was corrected from 60°±2° to 25°±3°,and the corrective effect was satisfactory.The correction rate of patients with Cobb angle ≤50° was 80%.Two hundred and ten patients were followed-up for 1 to 6 years,and the longitudinal growth of spine was 1.5-4.0cm.No severe complication,such as screw fracture,rod fracture or nerve injury,occurred.Conclusion The pedicle screw frame system with sliding terminus had a favorable three-dimensional correction effect,and the spine growth would not be restricted,and there was no stiffness,vertebral rotation,or distortion of shaft after operation.

  2. Spinal cord grey matter segmentation challenge.

    Science.gov (United States)

    Prados, Ferran; Ashburner, John; Blaiotta, Claudia; Brosch, Tom; Carballido-Gamio, Julio; Cardoso, Manuel Jorge; Conrad, Benjamin N; Datta, Esha; Dávid, Gergely; Leener, Benjamin De; Dupont, Sara M; Freund, Patrick; Wheeler-Kingshott, Claudia A M Gandini; Grussu, Francesco; Henry, Roland; Landman, Bennett A; Ljungberg, Emil; Lyttle, Bailey; Ourselin, Sebastien; Papinutto, Nico; Saporito, Salvatore; Schlaeger, Regina; Smith, Seth A; Summers, Paul; Tam, Roger; Yiannakas, Marios C; Zhu, Alyssa; Cohen-Adad, Julien

    2017-05-15

    An important image processing step in spinal cord magnetic resonance imaging is the ability to reliably and accurately segment grey and white matter for tissue specific analysis. There are several semi- or fully-automated segmentation methods for cervical cord cross-sectional area measurement with an excellent performance close or equal to the manual segmentation. However, grey matter segmentation is still challenging due to small cross-sectional size and shape, and active research is being conducted by several groups around the world in this field. Therefore a grey matter spinal cord segmentation challenge was organised to test different capabilities of various methods using the same multi-centre and multi-vendor dataset acquired with distinct 3D gradient-echo sequences. This challenge aimed to characterize the state-of-the-art in the field as well as identifying new opportunities for future improvements. Six different spinal cord grey matter segmentation methods developed independently by various research groups across the world and their performance were compared to manual segmentation outcomes, the present gold-standard. All algorithms provided good overall results for detecting the grey matter butterfly, albeit with variable performance in certain quality-of-segmentation metrics. The data have been made publicly available and the challenge web site remains open to new submissions. No modifications were introduced to any of the presented methods as a result of this challenge for the purposes of this publication. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  3. Coronary artery analysis: Computer-assisted selection of best-quality segments in multiple-phase coronary CT angiography

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Chuan, E-mail: chuan@umich.edu; Chan, Heang-Ping; Hadjiyski, Lubomir M.; Chughtai, Aamer; Wei, Jun; Kazerooni, Ella A. [Department of Radiology, The University of Michigan, Ann Arbor, Michigan 48109-0904 (United States)

    2016-10-15

    Purpose: The authors are developing an automated method to identify the best-quality coronary arterial segment from multiple-phase coronary CT angiography (cCTA) acquisitions, which may be used by either interpreting physicians or computer-aided detection systems to optimally and efficiently utilize the diagnostic information available in multiple-phase cCTA for the detection of coronary artery disease. Methods: After initialization with a manually identified seed point, each coronary artery tree is automatically extracted from multiple cCTA phases using our multiscale coronary artery response enhancement and 3D rolling balloon region growing vessel segmentation and tracking method. The coronary artery trees from multiple phases are then aligned by a global registration using an affine transformation with quadratic terms and nonlinear simplex optimization, followed by a local registration using a cubic B-spline method with fast localized optimization. The corresponding coronary arteries among the available phases are identified using a recursive coronary segment matching method. Each of the identified vessel segments is transformed by the curved planar reformation (CPR) method. Four features are extracted from each corresponding segment as quality indicators in the original computed tomography volume and the straightened CPR volume, and each quality indicator is used as a voting classifier for the arterial segment. A weighted voting ensemble (WVE) classifier is designed to combine the votes of the four voting classifiers for each corresponding segment. The segment with the highest WVE vote is then selected as the best-quality segment. In this study, the training and test sets consisted of 6 and 20 cCTA cases, respectively, each with 6 phases, containing a total of 156 cCTA volumes and 312 coronary artery trees. An observer preference study was also conducted with one expert cardiothoracic radiologist and four nonradiologist readers to visually rank vessel segment

  4. Coronary artery analysis: Computer-assisted selection of best-quality segments in multiple-phase coronary CT angiography

    International Nuclear Information System (INIS)

    Zhou, Chuan; Chan, Heang-Ping; Hadjiyski, Lubomir M.; Chughtai, Aamer; Wei, Jun; Kazerooni, Ella A.

    2016-01-01

    Purpose: The authors are developing an automated method to identify the best-quality coronary arterial segment from multiple-phase coronary CT angiography (cCTA) acquisitions, which may be used by either interpreting physicians or computer-aided detection systems to optimally and efficiently utilize the diagnostic information available in multiple-phase cCTA for the detection of coronary artery disease. Methods: After initialization with a manually identified seed point, each coronary artery tree is automatically extracted from multiple cCTA phases using our multiscale coronary artery response enhancement and 3D rolling balloon region growing vessel segmentation and tracking method. The coronary artery trees from multiple phases are then aligned by a global registration using an affine transformation with quadratic terms and nonlinear simplex optimization, followed by a local registration using a cubic B-spline method with fast localized optimization. The corresponding coronary arteries among the available phases are identified using a recursive coronary segment matching method. Each of the identified vessel segments is transformed by the curved planar reformation (CPR) method. Four features are extracted from each corresponding segment as quality indicators in the original computed tomography volume and the straightened CPR volume, and each quality indicator is used as a voting classifier for the arterial segment. A weighted voting ensemble (WVE) classifier is designed to combine the votes of the four voting classifiers for each corresponding segment. The segment with the highest WVE vote is then selected as the best-quality segment. In this study, the training and test sets consisted of 6 and 20 cCTA cases, respectively, each with 6 phases, containing a total of 156 cCTA volumes and 312 coronary artery trees. An observer preference study was also conducted with one expert cardiothoracic radiologist and four nonradiologist readers to visually rank vessel segment

  5. Multi-scale Modelling of Segmentation

    DEFF Research Database (Denmark)

    Hartmann, Martin; Lartillot, Olivier; Toiviainen, Petri

    2016-01-01

    pieces. In a second experiment on non-real-time segmentation, musicians indicated boundaries and their strength for six examples. Kernel density estimation was used to develop multi-scale segmentation models. Contrary to previous research, no relationship was found between boundary strength and boundary......While listening to music, people often unwittingly break down musical pieces into constituent chunks such as verses and choruses. Music segmentation studies have suggested that some consensus regarding boundary perception exists, despite individual differences. However, neither the effects...

  6. Skip segment Hirschsprung disease and Waardenburg syndrome

    Directory of Open Access Journals (Sweden)

    Erica R. Gross

    2015-04-01

    Full Text Available Skip segment Hirschsprung disease describes a segment of ganglionated bowel between two segments of aganglionated bowel. It is a rare phenomenon that is difficult to diagnose. We describe a recent case of skip segment Hirschsprung disease in a neonate with a family history of Waardenburg syndrome and the genetic profile that was identified.

  7. A workflow for the automatic segmentation of organelles in electron microscopy image stacks

    Science.gov (United States)

    Perez, Alex J.; Seyedhosseini, Mojtaba; Deerinck, Thomas J.; Bushong, Eric A.; Panda, Satchidananda; Tasdizen, Tolga; Ellisman, Mark H.

    2014-01-01

    Electron microscopy (EM) facilitates analysis of the form, distribution, and functional status of key organelle systems in various pathological processes, including those associated with neurodegenerative disease. Such EM data often provide important new insights into the underlying disease mechanisms. The development of more accurate and efficient methods to quantify changes in subcellular microanatomy has already proven key to understanding the pathogenesis of Parkinson's and Alzheimer's diseases, as well as glaucoma. While our ability to acquire large volumes of 3D EM data is progressing rapidly, more advanced analysis tools are needed to assist in measuring precise three-dimensional morphologies of organelles within data sets that can include hundreds to thousands of whole cells. Although new imaging instrument throughputs can exceed teravoxels of data per day, image segmentation and analysis remain significant bottlenecks to achieving quantitative descriptions of whole cell structural organellomes. Here, we present a novel method for the automatic segmentation of organelles in 3D EM image stacks. Segmentations are generated using only 2D image information, making the method suitable for anisotropic imaging techniques such as serial block-face scanning electron microscopy (SBEM). Additionally, no assumptions about 3D organelle morphology are made, ensuring the method can be easily expanded to any number of structurally and functionally diverse organelles. Following the presentation of our algorithm, we validate its performance by assessing the segmentation accuracy of different organelle targets in an example SBEM dataset and demonstrate that it can be efficiently parallelized on supercomputing resources, resulting in a dramatic reduction in runtime. PMID:25426032

  8. Segmentation-Based And Segmentation-Free Methods for Spotting Handwritten Arabic Words

    OpenAIRE

    Ball , Gregory R.; Srihari , Sargur N.; Srinivasan , Harish

    2006-01-01

    http://www.suvisoft.com; Given a set of handwritten documents, a common goal is to search for a relevant subset. Attempting to find a query word or image in such a set of documents is called word spotting. Spotting handwritten words in documents written in the Latin alphabet, and more recently in Arabic, has received considerable attention. One issue is generating candidate word regions on a page. Attempting to definitely segment the document into such regions (automatic segmentation) can mee...

  9. Axonal Membranes and Their Domains: Assembly and Function of the Axon Initial Segment and Node of Ranvier

    Directory of Open Access Journals (Sweden)

    Andrew D. Nelson

    2017-05-01

    Full Text Available Neurons are highly specialized cells of the nervous system that receive, process and transmit electrical signals critical for normal brain function. Here, we review the intricate organization of axonal membrane domains that facilitate rapid action potential conduction underlying communication between complex neuronal circuits. Two critical excitable domains of vertebrate axons are the axon initial segment (AIS and the nodes of Ranvier, which are characterized by the high concentrations of voltage-gated ion channels, cell adhesion molecules and specialized cytoskeletal networks. The AIS is located at the proximal region of the axon and serves as the site of action potential initiation, while nodes of Ranvier, gaps between adjacent myelin sheaths, allow rapid propagation of the action potential through saltatory conduction. The AIS and nodes of Ranvier are assembled by ankyrins, spectrins and their associated binding partners through the clustering of membrane proteins and connection to the underlying cytoskeleton network. Although the AIS and nodes of Ranvier share similar protein composition, their mechanisms of assembly are strikingly different. Here we will cover the mechanisms of formation and maintenance of these axonal excitable membrane domains, specifically highlighting the similarities and differences between them. We will also discuss recent advances in super resolution fluorescence imaging which have elucidated the arrangement of the submembranous axonal cytoskeleton revealing a surprising structural organization necessary to maintain axonal organization and function. Finally, human mutations in axonal domain components have been associated with a growing number of neurological disorders including severe cognitive dysfunction, epilepsy, autism, neurodegenerative diseases and psychiatric disorders. Overall, this review highlights the assembly, maintenance and function of axonal excitable domains, particularly the AIS and nodes of

  10. Monitoring fish distributions along electrofishing segments

    Science.gov (United States)

    Miranda, Leandro E.

    2014-01-01

    Electrofishing is widely used to monitor fish species composition and relative abundance in streams and lakes. According to standard protocols, multiple segments are selected in a body of water to monitor population relative abundance as the ratio of total catch to total sampling effort. The standard protocol provides an assessment of fish distribution at a macrohabitat scale among segments, but not within segments. An ancillary protocol was developed for assessing fish distribution at a finer scale within electrofishing segments. The ancillary protocol was used to estimate spacing, dispersion, and association of two species along shore segments in two local reservoirs. The added information provided by the ancillary protocol may be useful for assessing fish distribution relative to fish of the same species, to fish of different species, and to environmental or habitat characteristics.

  11. Color image Segmentation using automatic thresholding techniques

    International Nuclear Information System (INIS)

    Harrabi, R.; Ben Braiek, E.

    2011-01-01

    In this paper, entropy and between-class variance based thresholding methods for color images segmentation are studied. The maximization of the between-class variance (MVI) and the entropy (ME) have been used as a criterion functions to determine an optimal threshold to segment images into nearly homogenous regions. Segmentation results from the two methods are validated and the segmentation sensitivity for the test data available is evaluated, and a comparative study between these methods in different color spaces is presented. The experimental results demonstrate the superiority of the MVI method for color image segmentation.

  12. Process Segmentation Typology in Czech Companies

    Directory of Open Access Journals (Sweden)

    Tucek David

    2016-03-01

    Full Text Available This article describes process segmentation typology during business process management implementation in Czech companies. Process typology is important for a manager’s overview of process orientation as well as for a manager’s general understanding of business process management. This article provides insight into a process-oriented organizational structure. The first part analyzes process segmentation typology itself as well as some original results of quantitative research evaluating process segmentation typology in the specific context of Czech company strategies. Widespread data collection was carried out in 2006 and 2013. The analysis of this data showed that managers have more options regarding process segmentation and its selection. In terms of practicality and ease of use, the most frequently used method of process segmentation (managerial, main, and supportive stems directly from the requirements of ISO 9001. Because of ISO 9001:2015, managers must now apply risk planning in relation to the selection of processes that are subjected to process management activities. It is for this fundamental reason that this article focuses on process segmentation typology.

  13. Auxin-induced modifications of cell wall polysaccharides in cat coleoptile segments. Effect of galactose

    International Nuclear Information System (INIS)

    Yamamoto, R.; Masuda, Y.

    1984-01-01

    Galactose inhibits auxin-induced cell elongation in oat coleoptile segments. Cell elongation induced by exogenously applied auxin is controlled by factors such as auxin uptake, cell wall loosening, osmotic concentration of sap and hydraulic conductivity. However, galactose does not have any effect on these factors. The results discussed in this paper led to the conclusion that galactose does not affect cell wall loosening which controls rapid growth, but inhibits cell wall synthesis which is required to maintain long-term growth

  14. Algorithms for Cytoplasm Segmentation of Fluorescence Labelled Cells

    Directory of Open Access Journals (Sweden)

    Carolina Wählby

    2002-01-01

    Full Text Available Automatic cell segmentation has various applications in cytometry, and while the nucleus is often very distinct and easy to identify, the cytoplasm provides a lot more challenge. A new combination of image analysis algorithms for segmentation of cells imaged by fluorescence microscopy is presented. The algorithm consists of an image pre‐processing step, a general segmentation and merging step followed by a segmentation quality measurement. The quality measurement consists of a statistical analysis of a number of shape descriptive features. Objects that have features that differ to that of correctly segmented single cells can be further processed by a splitting step. By statistical analysis we therefore get a feedback system for separation of clustered cells. After the segmentation is completed, the quality of the final segmentation is evaluated. By training the algorithm on a representative set of training images, the algorithm is made fully automatic for subsequent images created under similar conditions. Automatic cytoplasm segmentation was tested on CHO‐cells stained with calcein. The fully automatic method showed between 89% and 97% correct segmentation as compared to manual segmentation.

  15. Benchmarking of Remote Sensing Segmentation Methods

    Czech Academy of Sciences Publication Activity Database

    Mikeš, Stanislav; Haindl, Michal; Scarpa, G.; Gaetano, R.

    2015-01-01

    Roč. 8, č. 5 (2015), s. 2240-2248 ISSN 1939-1404 R&D Projects: GA ČR(CZ) GA14-10911S Institutional support: RVO:67985556 Keywords : benchmark * remote sensing segmentation * unsupervised segmentation * supervised segmentation Subject RIV: BD - Theory of Information Impact factor: 2.145, year: 2015 http://library.utia.cas.cz/separaty/2015/RO/haindl-0445995.pdf

  16. Clinical utility of RapidArc™ radiotherapy technology

    International Nuclear Information System (INIS)

    Infusino, Erminia

    2015-01-01

    RapidArc™ is a radiation technique that delivers highly conformal dose distributions through the complete rotation (360°) and speed variation of the linear accelerator gantry. This technique, called volumetric modulated arc therapy (VMAT), compared with conventional radiotherapy techniques, can achieve high-target volume coverage and sparing damage to normal tissues. RapidArc delivers precise dose distribution and conformity similar to or greater than intensity-modulated radiation therapy in a short time, generally a few minutes, to which image-guided radiation therapy is added. RapidArc has become a currently used technology in many centers, which use RapidArc technology to treat a large number of patients. Large and small hospitals use it to treat the most challenging cases, but more and more frequently for the most common cancers. The clinical use of RapidArc and VMAT technology is constantly growing. At present, a limited number of clinical data are published, mostly concerning planning and feasibility studies. Clinical outcome data are increasing for a few tumor sites, even if only a little. The purpose of this work is to discuss the current status of VMAT techniques in clinical use through a review of the published data of planning systems and clinical outcomes in several tumor sites. The study consisted of a systematic review based on analysis of manuscripts retrieved from the PubMed, BioMed Central, and Scopus databases by searching for the keywords “RapidArc”, “Volumetric modulated arc radiotherapy”, and “Intensity-modulated radiotherapy”

  17. Unsupervised Retinal Vessel Segmentation Using Combined Filters.

    Directory of Open Access Journals (Sweden)

    Wendeson S Oliveira

    Full Text Available Image segmentation of retinal blood vessels is a process that can help to predict and diagnose cardiovascular related diseases, such as hypertension and diabetes, which are known to affect the retinal blood vessels' appearance. This work proposes an unsupervised method for the segmentation of retinal vessels images using a combined matched filter, Frangi's filter and Gabor Wavelet filter to enhance the images. The combination of these three filters in order to improve the segmentation is the main motivation of this work. We investigate two approaches to perform the filter combination: weighted mean and median ranking. Segmentation methods are tested after the vessel enhancement. Enhanced images with median ranking are segmented using a simple threshold criterion. Two segmentation procedures are applied when considering enhanced retinal images using the weighted mean approach. The first method is based on deformable models and the second uses fuzzy C-means for the image segmentation. The procedure is evaluated using two public image databases, Drive and Stare. The experimental results demonstrate that the proposed methods perform well for vessel segmentation in comparison with state-of-the-art methods.

  18. Older-Adult Playfulness: An Innovative Construct and Measurement for Healthy Aging Research

    Science.gov (United States)

    Yarnal, Careen; Qian, Xinyi

    2011-01-01

    Few studies of adult playfulness exist, but limited research on older adults and playfulness suggests that playfulness in later life improves cognitive, emotional, social, and psychological functioning and healthy aging overall. Older adults represent a rapidly growing segment of the U.S. population, underscoring the need to understand the aging…

  19. Automatic segmentation of psoriasis lesions

    Science.gov (United States)

    Ning, Yang; Shi, Chenbo; Wang, Li; Shu, Chang

    2014-10-01

    The automatic segmentation of psoriatic lesions is widely researched these years. It is an important step in Computer-aid methods of calculating PASI for estimation of lesions. Currently those algorithms can only handle single erythema or only deal with scaling segmentation. In practice, scaling and erythema are often mixed together. In order to get the segmentation of lesions area - this paper proposes an algorithm based on Random forests with color and texture features. The algorithm has three steps. The first step, the polarized light is applied based on the skin's Tyndall-effect in the imaging to eliminate the reflection and Lab color space are used for fitting the human perception. The second step, sliding window and its sub windows are used to get textural feature and color feature. In this step, a feature of image roughness has been defined, so that scaling can be easily separated from normal skin. In the end, Random forests will be used to ensure the generalization ability of the algorithm. This algorithm can give reliable segmentation results even the image has different lighting conditions, skin types. In the data set offered by Union Hospital, more than 90% images can be segmented accurately.

  20. World NGL markets continue rapid expansion

    International Nuclear Information System (INIS)

    Otto, K.; Gist, R.; Whitley, C.; Haun, R.

    1998-01-01

    The international LPG industry has expanded rapidly during the 1990s and undergone significant changes. LPG consumption has expanded at nearly twice the rate of world petroleum demand. In particular, LPG use in residential and commercial markets has more than doubled in many developing countries. Markets for LPG and other petroleum products have been opened in many countries, accelerating demand growth and creating investment opportunities in all downstream segments. This has led to an overall strengthening of global LPG pricing and the development of many new export gas-processing projects. The paper discusses world LPG demand in residential and commercial markets and in petrochemicals, world LPG supply, regional increases, international trade, the US situation in natural gas, NGL supply, and NGL demand

  1. Crowdsourcing image annotation for nucleus detection and segmentation in computational pathology: evaluating experts, automated methods, and the crowd.

    Science.gov (United States)

    Irshad, H; Montaser-Kouhsari, L; Waltz, G; Bucur, O; Nowak, J A; Dong, F; Knoblauch, N W; Beck, A H

    2015-01-01

    The development of tools in computational pathology to assist physicians and biomedical scientists in the diagnosis of disease requires access to high-quality annotated images for algorithm learning and evaluation. Generating high-quality expert-derived annotations is time-consuming and expensive. We explore the use of crowdsourcing for rapidly obtaining annotations for two core tasks in com- putational pathology: nucleus detection and nucleus segmentation. We designed and implemented crowdsourcing experiments using the CrowdFlower platform, which provides access to a large set of labor channel partners that accesses and manages millions of contributors worldwide. We obtained annotations from four types of annotators and compared concordance across these groups. We obtained: crowdsourced annotations for nucleus detection and segmentation on a total of 810 images; annotations using automated methods on 810 images; annotations from research fellows for detection and segmentation on 477 and 455 images, respectively; and expert pathologist-derived annotations for detection and segmentation on 80 and 63 images, respectively. For the crowdsourced annotations, we evaluated performance across a range of contributor skill levels (1, 2, or 3). The crowdsourced annotations (4,860 images in total) were completed in only a fraction of the time and cost required for obtaining annotations using traditional methods. For the nucleus detection task, the research fellow-derived annotations showed the strongest concordance with the expert pathologist- derived annotations (F-M =93.68%), followed by the crowd-sourced contributor levels 1,2, and 3 and the automated method, which showed relatively similar performance (F-M = 87.84%, 88.49%, 87.26%, and 86.99%, respectively). For the nucleus segmentation task, the crowdsourced contributor level 3-derived annotations, research fellow-derived annotations, and automated method showed the strongest concordance with the expert pathologist

  2. Simultaneous minimizing monitor units and number of segments without leaf end abutment for segmental intensity modulated radiation therapy delivery

    International Nuclear Information System (INIS)

    Li Kaile; Dai Jianrong; Ma Lijun

    2004-01-01

    Leaf end abutment is seldom studied when delivering segmental intensity modulated radiation therapy (IMRT) fields. We developed an efficient leaf sequencing method to eliminate leaf end abutment for segmental IMRT delivery. Our method uses simple matrix and sorting operations to obtain a solution that simultaneously minimizes total monitor units and number of segments without leaf end abutment between segments. We implemented and demonstrated our method for multiple clinical cases. We compared the results of our method with the results from exhaustive search method. We found that our solution without leaf end abutment produced equivalent results to the unconstrained solutions in terms of minimum total monitor units and minimum number of leaf segments. We conclude that the leaf end abutment fields can be avoided without affecting the efficiency of segmental IMRT delivery. The major strength of our method is its simplicity and high computing speed. This potentially provides a useful means for generating segmental IMRT fields that require high spatial resolution or complex intensity distributions

  3. Hierarchical image segmentation for learning object priors

    Energy Technology Data Exchange (ETDEWEB)

    Prasad, Lakshman [Los Alamos National Laboratory; Yang, Xingwei [TEMPLE UNIV.; Latecki, Longin J [TEMPLE UNIV.; Li, Nan [TEMPLE UNIV.

    2010-11-10

    The proposed segmentation approach naturally combines experience based and image based information. The experience based information is obtained by training a classifier for each object class. For a given test image, the result of each classifier is represented as a probability map. The final segmentation is obtained with a hierarchial image segmentation algorithm that considers both the probability maps and the image features such as color and edge strength. We also utilize image region hierarchy to obtain not only local but also semi-global features as input to the classifiers. Moreover, to get robust probability maps, we take into account the region context information by averaging the probability maps over different levels of the hierarchical segmentation algorithm. The obtained segmentation results are superior to the state-of-the-art supervised image segmentation algorithms.

  4. Effect of the average soft-segment length on the morphology and properties of segmented polyurethane nanocomposites

    International Nuclear Information System (INIS)

    Finnigan, Bradley; Halley, Peter; Jack, Kevin; McDowell, Alasdair; Truss, Rowan; Casey, Phil; Knott, Robert; Martin, Darren

    2006-01-01

    Two organically modified layered silicates (with small and large diameters) were incorporated into three segmented polyurethanes with various degrees of microphase separation. Microphase separation increased with the molecular weight of the poly(hexamethylene oxide) soft segment. The molecular weight of the soft segment did not influence the amount of polyurethane intercalating the interlayer spacing. Small-angle neutron scattering and differential scanning calorimetry data indicated that the layered silicates did not affect the microphase morphology of any host polymer, regardless of the particle diameter. The stiffness enhancement on filler addition increased as the microphase separation of the polyurethane decreased, presumably because a greater number of urethane linkages were available to interact with the filler. For comparison, the small nanofiller was introduced into a polyurethane with a poly(tetramethylene oxide) soft segment, and a significant increase in the tensile strength and a sharper upturn in the stress-strain curve resulted. No such improvement occurred in the host polymers with poly(hexamethylene oxide) soft segments. It is proposed that the nanocomposite containing the more hydrophilic and mobile poly(tetramethylene oxide) soft segment is capable of greater secondary bonding between the polyurethane chains and the organosilicate surface, resulting in improved stress transfer to the filler and reduced molecular slippage.

  5. Essays in international market segmentation

    NARCIS (Netherlands)

    Hofstede, ter F.

    1999-01-01

    The primary objective of this thesis is to develop and validate new methodologies to improve the effectiveness of international segmentation strategies. The current status of international market segmentation research is reviewed in an introductory chapter, which provided a number of

  6. Advances in developing rapid, reliable and portable detection systems for alcohol.

    Science.gov (United States)

    Thungon, Phurpa Dema; Kakoti, Ankana; Ngashangva, Lightson; Goswami, Pranab

    2017-11-15

    Development of portable, reliable, sensitive, simple, and inexpensive detection system for alcohol has been an instinctive demand not only in traditional brewing, pharmaceutical, food and clinical industries but also in rapidly growing alcohol based fuel industries. Highly sensitive, selective, and reliable alcohol detections are currently amenable typically through the sophisticated instrument based analyses confined mostly to the state-of-art analytical laboratory facilities. With the growing demand of rapid and reliable alcohol detection systems, an all-round attempt has been made over the past decade encompassing various disciplines from basic and engineering sciences. Of late, the research for developing small-scale portable alcohol detection system has been accelerated with the advent of emerging miniaturization techniques, advanced materials and sensing platforms such as lab-on-chip, lab-on-CD, lab-on-paper etc. With these new inter-disciplinary approaches along with the support from the parallel knowledge growth on rapid detection systems being pursued for various targets, the progress on translating the proof-of-concepts to commercially viable and environment friendly portable alcohol detection systems is gaining pace. Here, we summarize the progress made over the years on the alcohol detection systems, with a focus on recent advancement towards developing portable, simple and efficient alcohol sensors. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. Rapid Prototyping: Technologies, Materials and Advances

    Directory of Open Access Journals (Sweden)

    Dudek P.

    2016-06-01

    Full Text Available In the context of product development, the term rapid prototyping (RP is widely used to describe technologies which create physical prototypes directly from digital data. Recently, this technology has become one of the fastest-growing methods of manufacturing parts. The paper provides brief notes on the creation of composites using RP methods, such as stereolithography, selective laser sintering or melting, laminated object modelling, fused deposition modelling or three-dimensional printing. The emphasis of this work is on the methodology of composite fabrication and the variety of materials used in these technologies.

  8. Roentgenological diagnoss of central segmental lung cancer

    International Nuclear Information System (INIS)

    Gurevich, L.A.; Fedchenko, G.G.

    1984-01-01

    Basing on an analysis of the results of clinicoroentgenological examination of 268 patments roentgenological semiotics of segmental lung cancer is presented. Some peculiarities of the X-ray picture of cancer of different segments of the lungs were revealed depending on tumor site and growth type. For the syndrome of segmental darkening the comprehensive X-ray methods where the chief method is tomography of the segmental bronchi are proposed

  9. Method of manufacturing a large-area segmented photovoltaic module

    Science.gov (United States)

    Lenox, Carl

    2013-11-05

    One embodiment of the invention relates to a segmented photovoltaic (PV) module which is manufactured from laminate segments. The segmented PV module includes rectangular-shaped laminate segments formed from rectangular-shaped PV laminates and further includes non-rectangular-shaped laminate segments formed from rectangular-shaped and approximately-triangular-shaped PV laminates. The laminate segments are mechanically joined and electrically interconnected to form the segmented module. Another embodiment relates to a method of manufacturing a large-area segmented photovoltaic module from laminate segments of various shapes. Other embodiments relate to processes for providing a photovoltaic array for installation at a site. Other embodiments and features are also disclosed.

  10. Study of the morphology exhibited by linear segmented polyurethanes

    International Nuclear Information System (INIS)

    Pereira, I.M.; Orefice, R.L.

    2009-01-01

    Five series of segmented polyurethanes with different hard segment content were prepared by the prepolymer mixing method. The nano-morphology of the obtained polyurethanes and their microphase separation were investigated by infrared spectroscopy, modulated differential scanning calorimetry and small-angle X-ray scattering. Although highly hydrogen bonded hard segments were formed, high hard segment contents promoted phase mixture and decreased the chain mobility, decreasing the hard segment domain precipitation and the soft segments crystallization. The applied techniques were able to show that the hard-segment content and the hard-segment interactions were the two controlling factors for determining the structure of segmented polyurethanes. (author)

  11. The Bright Lights Grow Fainter - livelihoods, migration and a small town in Zimbabwe

    OpenAIRE

    Andersson, Agnes

    2002-01-01

    The Aids pandemic and structural adjustment policies (SAP) have had effects on lower income households in Zimbabwe which have been devastating and people have been required to adapt their livelihood strategies. Small towns meahnwhile are growing rapidly in Zimbabwe and mobility towards these towns may be connected with the changes being forged by SAP on the economic landscape. This study seeks to establish how the individual migrant uses mobility tot negotiate this landscape. This involves mo...

  12. Biotechnology and genetic optimization of fast-growing hardwoods

    Energy Technology Data Exchange (ETDEWEB)

    Garton, S.; Syrkin-Wurtele, E.; Griffiths, H.; Schell, J.; Van Camp, L.; Bulka, K. (NPI, Salt Lake City, UT (United States))

    1991-02-01

    A biotechnology research program was initiated to develop new clones of fast-growing Populus clones resistant to the herbicide glyphosate and resistant to the leaf-spot and canker disease caused by the fungus Septoria musiva. Glyphosate-resistant callus was selected from stem segments cultured in vitro on media supplemented with the herbicide. Plants were regenerated from the glyphosate-resistant callus tissue. A portion of plants reverted to a glyphosate susceptible phenotype during organogenesis. A biologically active filtrate was prepared from S. musiva and influenced fresh weight of Populus callus tissue. Disease-resistant plants were produced through somaclonal variation when shoots developed on stem internodes cultured in vitro. Plantlets were screened for disease symptoms after spraying with a suspension of fungal spores. A frequency of 0.83 percent variant production was observed. Genetically engineered plants were produced after treatment of plant tissue with Agrobacterium tumefasciens strains carrying plasmid genes for antibiotic resistance. Transformers were selected on media enriched with the antibiotic, kanamycin. Presence of foreign DNA was confirmed by Southern blot analysis. Protoplasts of popular were produced but did not regenerate into plant organs. 145 refs., 12 figs., 36 tabs.

  13. Significant Change Spotting for Periodic Human Motion Segmentation of Cleaning Tasks Using Wearable Sensors

    Directory of Open Access Journals (Sweden)

    Kai-Chun Liu

    2017-01-01

    Full Text Available The proportion of the aging population is rapidly increasing around the world, which will cause stress on society and healthcare systems. In recent years, advances in technology have created new opportunities for automatic activities of daily living (ADL monitoring to improve the quality of life and provide adequate medical service for the elderly. Such automatic ADL monitoring requires reliable ADL information on a fine-grained level, especially for the status of interaction between body gestures and the environment in the real-world. In this work, we propose a significant change spotting mechanism for periodic human motion segmentation during cleaning task performance. A novel approach is proposed based on the search for a significant change of gestures, which can manage critical technical issues in activity recognition, such as continuous data segmentation, individual variance, and category ambiguity. Three typical machine learning classification algorithms are utilized for the identification of the significant change candidate, including a Support Vector Machine (SVM, k-Nearest Neighbors (kNN, and Naive Bayesian (NB algorithm. Overall, the proposed approach achieves 96.41% in the F1-score by using the SVM classifier. The results show that the proposed approach can fulfill the requirement of fine-grained human motion segmentation for automatic ADL monitoring.

  14. Prototype implementation of segment assembling software

    Directory of Open Access Journals (Sweden)

    Pešić Đorđe

    2018-01-01

    Full Text Available IT education is very important and a lot of effort is put into the development of tools for helping students to acquire programming knowledge and for helping teachers in automating the examination process. This paper describes a prototype of the program segment assembling software used in the context of making tests in the field of algorithmic complexity. The proposed new program segment assembling model uses rules and templates. A template is a simple program segment. A rule defines combining method and data dependencies if they exist. One example of program segment assembling by the proposed system is given. Graphical user interface is also described.

  15. Smart markers for watershed-based cell segmentation.

    Directory of Open Access Journals (Sweden)

    Can Fahrettin Koyuncu

    Full Text Available Automated cell imaging systems facilitate fast and reliable analysis of biological events at the cellular level. In these systems, the first step is usually cell segmentation that greatly affects the success of the subsequent system steps. On the other hand, similar to other image segmentation problems, cell segmentation is an ill-posed problem that typically necessitates the use of domain-specific knowledge to obtain successful segmentations even by human subjects. The approaches that can incorporate this knowledge into their segmentation algorithms have potential to greatly improve segmentation results. In this work, we propose a new approach for the effective segmentation of live cells from phase contrast microscopy. This approach introduces a new set of "smart markers" for a marker-controlled watershed algorithm, for which the identification of its markers is critical. The proposed approach relies on using domain-specific knowledge, in the form of visual characteristics of the cells, to define the markers. We evaluate our approach on a total of 1,954 cells. The experimental results demonstrate that this approach, which uses the proposed definition of smart markers, is quite effective in identifying better markers compared to its counterparts. This will, in turn, be effective in improving the segmentation performance of a marker-controlled watershed algorithm.

  16. Smart markers for watershed-based cell segmentation.

    Science.gov (United States)

    Koyuncu, Can Fahrettin; Arslan, Salim; Durmaz, Irem; Cetin-Atalay, Rengul; Gunduz-Demir, Cigdem

    2012-01-01

    Automated cell imaging systems facilitate fast and reliable analysis of biological events at the cellular level. In these systems, the first step is usually cell segmentation that greatly affects the success of the subsequent system steps. On the other hand, similar to other image segmentation problems, cell segmentation is an ill-posed problem that typically necessitates the use of domain-specific knowledge to obtain successful segmentations even by human subjects. The approaches that can incorporate this knowledge into their segmentation algorithms have potential to greatly improve segmentation results. In this work, we propose a new approach for the effective segmentation of live cells from phase contrast microscopy. This approach introduces a new set of "smart markers" for a marker-controlled watershed algorithm, for which the identification of its markers is critical. The proposed approach relies on using domain-specific knowledge, in the form of visual characteristics of the cells, to define the markers. We evaluate our approach on a total of 1,954 cells. The experimental results demonstrate that this approach, which uses the proposed definition of smart markers, is quite effective in identifying better markers compared to its counterparts. This will, in turn, be effective in improving the segmentation performance of a marker-controlled watershed algorithm.

  17. An unsupervised strategy for biomedical image segmentation

    Directory of Open Access Journals (Sweden)

    Roberto Rodríguez

    2010-09-01

    Full Text Available Roberto Rodríguez1, Rubén Hernández21Digital Signal Processing Group, Institute of Cybernetics, Mathematics, and Physics, Havana, Cuba; 2Interdisciplinary Professional Unit of Engineering and Advanced Technology, IPN, MexicoAbstract: Many segmentation techniques have been published, and some of them have been widely used in different application problems. Most of these segmentation techniques have been motivated by specific application purposes. Unsupervised methods, which do not assume any prior scene knowledge can be learned to help the segmentation process, and are obviously more challenging than the supervised ones. In this paper, we present an unsupervised strategy for biomedical image segmentation using an algorithm based on recursively applying mean shift filtering, where entropy is used as a stopping criterion. This strategy is proven with many real images, and a comparison is carried out with manual segmentation. With the proposed strategy, errors less than 20% for false positives and 0% for false negatives are obtained.Keywords: segmentation, mean shift, unsupervised segmentation, entropy

  18. MOVING WINDOW SEGMENTATION FRAMEWORK FOR POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    G. Sithole

    2012-07-01

    Full Text Available As lidar point clouds become larger streamed processing becomes more attractive. This paper presents a framework for the streamed segmentation of point clouds with the intention of segmenting unstructured point clouds in real-time. The framework is composed of two main components. The first component segments points within a window shifting over the point cloud. The second component stitches the segments within the windows together. In this fashion a point cloud can be streamed through these two components in sequence, thus producing a segmentation. The algorithm has been tested on airborne lidar point cloud and some results of the performance of the framework are presented.

  19. Review of segmentation process in consumer markets

    OpenAIRE

    Veronika Jadczaková

    2013-01-01

    Although there has been a considerable debate on market segmentation over five decades, attention was merely devoted to single stages of the segmentation process. In doing so, stages as segmentation base selection or segments profiling have been heavily covered in the extant literature, whereas stages as implementation of the marketing strategy or market definition were of a comparably lower interest. Capitalizing on this shortcoming, this paper strives to close the gap and provide each step...

  20. IFRS 8 – OPERATING SEGMENTS

    Directory of Open Access Journals (Sweden)

    BOCHIS LEONICA

    2009-05-01

    Full Text Available Segment reporting in accordance with IFRS 8 will be mandatory for annual financial statements covering periods beginning on or after 1 January 2009. The standards replaces IAS 14, Segment Reporting, from that date. The objective of IFRS 8 is to require

  1. The Hierarchy of Segment Reports

    Directory of Open Access Journals (Sweden)

    Danilo Dorović

    2015-05-01

    Full Text Available The article presents an attempt to find the connection between reports created for managers responsible for different business segments. With this purpose, the hierarchy of the business reporting segments is proposed. This can lead to better understanding of the expenses under common responsibility of more than one manager since these expenses should be in more than one report. The structure of cost defined per business segment hierarchy with the aim of new, unusual but relevant cost structure for management can be established. Both could potentially bring new information benefits for management in the context of profit reporting.

  2. Segmental dilatation of the ileum

    Directory of Open Access Journals (Sweden)

    Tune-Yie Shih

    2017-01-01

    Full Text Available A 2-year-old boy was sent to the emergency department with the chief problem of abdominal pain for 1 day. He was just discharged from the pediatric ward with the diagnosis of mycoplasmal pneumonia and paralytic ileus. After initial examinations and radiographic investigations, midgut volvulus was impressed. An emergency laparotomy was performed. Segmental dilatation of the ileum with volvulus was found. The operative procedure was resection of the dilated ileal segment with anastomosis. The postoperative recovery was uneventful. The unique abnormality of gastrointestinal tract – segmental dilatation of the ileum, is described in details and the literature is reviewed.

  3. Expanding the Horizon: For-Profit Degree Granting Institutions in Higher Education. An Annotated Bibliography

    Science.gov (United States)

    Lechuga, Vicente M.; Tierney, William G.; Hentschke, Guilbert C.

    2003-01-01

    In recent years, higher education has witnessed the entry of a new breed of postsecondary education providers. These institutions have reshaped the traditional views of the function and purpose of higher education. For-profit education institutions provide a small but rapidly growing segment of the student population with the knowledge and skills…

  4. Techniques on semiautomatic segmentation using the Adobe Photoshop

    Science.gov (United States)

    Park, Jin Seo; Chung, Min Suk; Hwang, Sung Bae

    2005-04-01

    The purpose of this research is to enable anybody to semiautomatically segment the anatomical structures in the MRIs, CTs, and other medical images on the personal computer. The segmented images are used for making three-dimensional images, which are helpful in medical education and research. To achieve this purpose, the following trials were performed. The entire body of a volunteer was MR scanned to make 557 MRIs, which were transferred to a personal computer. On Adobe Photoshop, contours of 19 anatomical structures in the MRIs were semiautomatically drawn using MAGNETIC LASSO TOOL; successively, manually corrected using either LASSO TOOL or DIRECT SELECTION TOOL to make 557 segmented images. In a likewise manner, 11 anatomical structures in the 8,500 anatomcial images were segmented. Also, 12 brain and 10 heart anatomical structures in anatomical images were segmented. Proper segmentation was verified by making and examining the coronal, sagittal, and three-dimensional images from the segmented images. During semiautomatic segmentation on Adobe Photoshop, suitable algorithm could be used, the extent of automatization could be regulated, convenient user interface could be used, and software bugs rarely occurred. The techniques of semiautomatic segmentation using Adobe Photoshop are expected to be widely used for segmentation of the anatomical structures in various medical images.

  5. Food (In)Security in Rapidly Urbanising, Low-Income Contexts.

    Science.gov (United States)

    Tacoli, Cecilia

    2017-12-11

    Urbanisation in low and middle-income nations presents both opportunities and immense challenges. As urban centres grow rapidly, inadequate housing and the lack of basic infrastructure and services affect a large and growing proportion of their population. There is also a growing body of evidence on urban poverty and its links with environmental hazards. There is, however, limited knowledge of how these challenges affect the ways in which poor urban residents gain access to food and secure healthy and nutritious diets. With some important exceptions, current discussions on food security continue to focus on production, with limited attention to consumption. Moreover, urban consumers are typically treated as a homogenous group and access to food markets is assumed to be sufficient. This paper describes how, for the urban poor in low and middle-income countries, food affordability and utilisation are shaped by the income and non-income dimensions of poverty that include the urban space.

  6. Food (InSecurity in Rapidly Urbanising, Low-Income Contexts

    Directory of Open Access Journals (Sweden)

    Cecilia Tacoli

    2017-12-01

    Full Text Available Urbanisation in low and middle-income nations presents both opportunities and immense challenges. As urban centres grow rapidly, inadequate housing and the lack of basic infrastructure and services affect a large and growing proportion of their population. There is also a growing body of evidence on urban poverty and its links with environmental hazards. There is, however, limited knowledge of how these challenges affect the ways in which poor urban residents gain access to food and secure healthy and nutritious diets. With some important exceptions, current discussions on food security continue to focus on production, with limited attention to consumption. Moreover, urban consumers are typically treated as a homogenous group and access to food markets is assumed to be sufficient. This paper describes how, for the urban poor in low and middle-income countries, food affordability and utilisation are shaped by the income and non-income dimensions of poverty that include the urban space.

  7. CT identification of bronchopulmonary segments: 50 normal subjects

    International Nuclear Information System (INIS)

    Osbourne, D.; Vock, P.; Godwin, J.D.; Silverman, P.M.

    1984-01-01

    A systematic evaluation of the fissures, segmental bronchi and arteries, bronchopulmonary segments, and peripheral pulmonary parenchyma was made from computed tomographic (CT) scans of 50 patients with normal chest radiographs. Seventy percent of the segmental bronchi and 76% of the segmental arteries were identified. Arteries could be traced to their sixth- and seventh-order branches; their orientation to the plane of the CT section allowed gross identification and localization of bronchopulmonary segments

  8. Segmentation of liver tumors on CT images

    International Nuclear Information System (INIS)

    Pescia, D.

    2011-01-01

    This thesis is dedicated to 3D segmentation of liver tumors in CT images. This is a task of great clinical interest since it allows physicians benefiting from reproducible and reliable methods for segmenting such lesions. Accurate segmentation would indeed help them during the evaluation of the lesions, the choice of treatment and treatment planning. Such a complex segmentation task should cope with three main scientific challenges: (i) the highly variable shape of the structures being sought, (ii) their similarity of appearance compared with their surrounding medium and finally (iii) the low signal to noise ratio being observed in these images. This problem is addressed in a clinical context through a two step approach, consisting of the segmentation of the entire liver envelope, before segmenting the tumors which are present within the envelope. We begin by proposing an atlas-based approach for computing pathological liver envelopes. Initially images are pre-processed to compute the envelopes that wrap around binary masks in an attempt to obtain liver envelopes from estimated segmentation of healthy liver parenchyma. A new statistical atlas is then introduced and used to segmentation through its diffeomorphic registration to the new image. This segmentation is achieved through the combination of image matching costs as well as spatial and appearance prior using a multi-scale approach with MRF. The second step of our approach is dedicated to lesions segmentation contained within the envelopes using a combination of machine learning techniques and graph based methods. First, an appropriate feature space is considered that involves texture descriptors being determined through filtering using various scales and orientations. Then, state of the art machine learning techniques are used to determine the most relevant features, as well as the hyper plane that separates the feature space of tumoral voxels to the ones corresponding to healthy tissues. Segmentation is then

  9. Diversity, community composition, and dynamics of nonpigmented and late-pigmenting rapidly growing mycobacteria in an urban tap water production and distribution system.

    Science.gov (United States)

    Dubrou, S; Konjek, J; Macheras, E; Welté, B; Guidicelli, L; Chignon, E; Joyeux, M; Gaillard, J L; Heym, B; Tully, T; Sapriel, G

    2013-09-01

    Nonpigmented and late-pigmenting rapidly growing mycobacteria (RGM) have been reported to commonly colonize water production and distribution systems. However, there is little information about the nature and distribution of RGM species within the different parts of such complex networks or about their clustering into specific RGM species communities. We conducted a large-scale survey between 2007 and 2009 in the Parisian urban tap water production and distribution system. We analyzed 1,418 water samples from 36 sites, covering all production units, water storage tanks, and distribution units; RGM isolates were identified by using rpoB gene sequencing. We detected 18 RGM species and putative new species, with most isolates being Mycobacterium chelonae and Mycobacterium llatzerense. Using hierarchical clustering and principal-component analysis, we found that RGM were organized into various communities correlating with water origin (groundwater or surface water) and location within the distribution network. Water treatment plants were more specifically associated with species of the Mycobacterium septicum group. On average, M. chelonae dominated network sites fed by surface water, and M. llatzerense dominated those fed by groundwater. Overall, the M. chelonae prevalence index increased along the distribution network and was associated with a correlative decrease in the prevalence index of M. llatzerense, suggesting competitive or niche exclusion between these two dominant species. Our data describe the great diversity and complexity of RGM species living in the interconnected environments that constitute the water production and distribution system of a large city and highlight the prevalence index of the potentially pathogenic species M. chelonae in the distribution network.

  10. Efficient Algorithms for Segmentation of Item-Set Time Series

    Science.gov (United States)

    Chundi, Parvathi; Rosenkrantz, Daniel J.

    We propose a special type of time series, which we call an item-set time series, to facilitate the temporal analysis of software version histories, email logs, stock market data, etc. In an item-set time series, each observed data value is a set of discrete items. We formalize the concept of an item-set time series and present efficient algorithms for segmenting a given item-set time series. Segmentation of a time series partitions the time series into a sequence of segments where each segment is constructed by combining consecutive time points of the time series. Each segment is associated with an item set that is computed from the item sets of the time points in that segment, using a function which we call a measure function. We then define a concept called the segment difference, which measures the difference between the item set of a segment and the item sets of the time points in that segment. The segment difference values are required to construct an optimal segmentation of the time series. We describe novel and efficient algorithms to compute segment difference values for each of the measure functions described in the paper. We outline a dynamic programming based scheme to construct an optimal segmentation of the given item-set time series. We use the item-set time series segmentation techniques to analyze the temporal content of three different data sets—Enron email, stock market data, and a synthetic data set. The experimental results show that an optimal segmentation of item-set time series data captures much more temporal content than a segmentation constructed based on the number of time points in each segment, without examining the item set data at the time points, and can be used to analyze different types of temporal data.

  11. Metrology requirements for the serial production of ELT primary mirror segments

    Science.gov (United States)

    Rees, Paul C. T.; Gray, Caroline

    2015-08-01

    The manufacture of the next generation of large astronomical telescopes, the extremely large telescopes (ELT), requires the rapid manufacture of greater than 500 1.44m hexagonal segments for the primary mirror of each telescope. Both leading projects, the Thirty Meter Telescope (TMT) and the European Extremely Large Telescope (E-ELT), have set highly demanding technical requirements for each fabricated segment. These technical requirements, when combined with the anticipated construction schedule for each telescope, suggest that more than one optical fabricator will be involved in the delivery of the primary mirror segments in order to meet the project schedule. For one supplier, the technical specification is challenging and requires highly consistent control of metrology in close coordination with the polishing technologies used in order to optimize production rates. For production using multiple suppliers, however the supply chain is structured, consistent control of metrology along the supply chain will be required. This requires a broader pattern of independent verification than is the case of a single supplier. This paper outlines the metrology requirements for a single supplier throughout all stages of the fabrication process. We identify and outline those areas where metrology accuracy and duration have a significant impact on production efficiency. We use the challenging ESO E-ELT technical specification as an example of our treatment, including actual process data. We further develop this model for the case of a supply chain consisting of multiple suppliers. Here, we emphasize the need to control metrology throughout the supply chain in order to optimize net production efficiency.

  12. Rapid Endovascular Catheter Core Cooling Combined With Cold Saline as an Adjunct to Percutaneous Coronary Intervention for the Treatment of Acute Myocardial Infarction

    DEFF Research Database (Denmark)

    Erlinge, David; Götberg, Matthias; Lang, Irene

    2014-01-01

    : In a multicenter study, 120 patients with ST-segment elevation myocardial infarctions (rapid infusion of 600 to 2,000 ml cold saline and endovascular cooling or standard of care. Hypothermia was initiated...

  13. Reliability of a Seven-Segment Foot Model with Medial and Lateral Midfoot and Forefoot Segments During Walking Gait.

    Science.gov (United States)

    Cobb, Stephen C; Joshi, Mukta N; Pomeroy, Robin L

    2016-12-01

    In-vitro and invasive in-vivo studies have reported relatively independent motion in the medial and lateral forefoot segments during gait. However, most current surface-based models have not defined medial and lateral forefoot or midfoot segments. The purpose of the current study was to determine the reliability of a 7-segment foot model that includes medial and lateral midfoot and forefoot segments during walking gait. Three-dimensional positions of marker clusters located on the leg and 6 foot segments were tracked as 10 participants completed 5 walking trials. To examine the reliability of the foot model, coefficients of multiple correlation (CMC) were calculated across the trials for each participant. Three-dimensional stance time series and range of motion (ROM) during stance were also calculated for each functional articulation. CMCs for all of the functional articulations were ≥ 0.80. Overall, the rearfoot complex (leg-calcaneus segments) was the most reliable articulation and the medial midfoot complex (calcaneus-navicular segments) was the least reliable. With respect to ROM, reliability was greatest for plantarflexion/dorsiflexion and least for abduction/adduction. Further, the stance ROM and time-series patterns results between the current study and previous invasive in-vivo studies that have assessed actual bone motion were generally consistent.

  14. Market Segmentation: An Instructional Module.

    Science.gov (United States)

    Wright, Peter H.

    A concept-based introduction to market segmentation is provided in this instructional module for undergraduate and graduate transportation-related courses. The material can be used in many disciplines including engineering, business, marketing, and technology. The concept of market segmentation is primarily a transportation planning technique by…

  15. Vision 20/20: Perspectives on automated image segmentation for radiotherapy

    Energy Technology Data Exchange (ETDEWEB)

    Sharp, Gregory, E-mail: gcsharp@partners.org; Fritscher, Karl D.; Shusharina, Nadya [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts 02114 (United States); Pekar, Vladimir [Philips Healthcare, Markham, Ontario 6LC 2S3 (Canada); Peroni, Marta [Center for Proton Therapy, Paul Scherrer Institut, 5232 Villigen-PSI (Switzerland); Veeraraghavan, Harini [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York 10065 (United States); Yang, Jinzhong [Department of Radiation Physics, MD Anderson Cancer Center, Houston, Texas 77030 (United States)

    2014-05-15

    Due to rapid advances in radiation therapy (RT), especially image guidance and treatment adaptation, a fast and accurate segmentation of medical images is a very important part of the treatment. Manual delineation of target volumes and organs at risk is still the standard routine for most clinics, even though it is time consuming and prone to intra- and interobserver variations. Automated segmentation methods seek to reduce delineation workload and unify the organ boundary definition. In this paper, the authors review the current autosegmentation methods particularly relevant for applications in RT. The authors outline the methods’ strengths and limitations and propose strategies that could lead to wider acceptance of autosegmentation in routine clinical practice. The authors conclude that currently, autosegmentation technology in RT planning is an efficient tool for the clinicians to provide them with a good starting point for review and adjustment. Modern hardware platforms including GPUs allow most of the autosegmentation tasks to be done in a range of a few minutes. In the nearest future, improvements in CT-based autosegmentation tools will be achieved through standardization of imaging and contouring protocols. In the longer term, the authors expect a wider use of multimodality approaches and better understanding of correlation of imaging with biology and pathology.

  16. Vision 20/20: perspectives on automated image segmentation for radiotherapy.

    Science.gov (United States)

    Sharp, Gregory; Fritscher, Karl D; Pekar, Vladimir; Peroni, Marta; Shusharina, Nadya; Veeraraghavan, Harini; Yang, Jinzhong

    2014-05-01

    Due to rapid advances in radiation therapy (RT), especially image guidance and treatment adaptation, a fast and accurate segmentation of medical images is a very important part of the treatment. Manual delineation of target volumes and organs at risk is still the standard routine for most clinics, even though it is time consuming and prone to intra- and interobserver variations. Automated segmentation methods seek to reduce delineation workload and unify the organ boundary definition. In this paper, the authors review the current autosegmentation methods particularly relevant for applications in RT. The authors outline the methods' strengths and limitations and propose strategies that could lead to wider acceptance of autosegmentation in routine clinical practice. The authors conclude that currently, autosegmentation technology in RT planning is an efficient tool for the clinicians to provide them with a good starting point for review and adjustment. Modern hardware platforms including GPUs allow most of the autosegmentation tasks to be done in a range of a few minutes. In the nearest future, improvements in CT-based autosegmentation tools will be achieved through standardization of imaging and contouring protocols. In the longer term, the authors expect a wider use of multimodality approaches and better understanding of correlation of imaging with biology and pathology.

  17. Vision 20/20: Perspectives on automated image segmentation for radiotherapy

    International Nuclear Information System (INIS)

    Sharp, Gregory; Fritscher, Karl D.; Shusharina, Nadya; Pekar, Vladimir; Peroni, Marta; Veeraraghavan, Harini; Yang, Jinzhong

    2014-01-01

    Due to rapid advances in radiation therapy (RT), especially image guidance and treatment adaptation, a fast and accurate segmentation of medical images is a very important part of the treatment. Manual delineation of target volumes and organs at risk is still the standard routine for most clinics, even though it is time consuming and prone to intra- and interobserver variations. Automated segmentation methods seek to reduce delineation workload and unify the organ boundary definition. In this paper, the authors review the current autosegmentation methods particularly relevant for applications in RT. The authors outline the methods’ strengths and limitations and propose strategies that could lead to wider acceptance of autosegmentation in routine clinical practice. The authors conclude that currently, autosegmentation technology in RT planning is an efficient tool for the clinicians to provide them with a good starting point for review and adjustment. Modern hardware platforms including GPUs allow most of the autosegmentation tasks to be done in a range of a few minutes. In the nearest future, improvements in CT-based autosegmentation tools will be achieved through standardization of imaging and contouring protocols. In the longer term, the authors expect a wider use of multimodality approaches and better understanding of correlation of imaging with biology and pathology

  18. Impacts of bus rapid transit (BRT) on surrounding residential property values : final report.

    Science.gov (United States)

    2017-07-01

    As bus rapid transit (BRT) grows in popularity in the United States, a better understanding of the modes impacts on land uses and property values is needed. Economic theory suggests, and literature has shown, that people are willing to pay higher ...

  19. Medical image segmentation using genetic algorithms.

    Science.gov (United States)

    Maulik, Ujjwal

    2009-03-01

    Genetic algorithms (GAs) have been found to be effective in the domain of medical image segmentation, since the problem can often be mapped to one of search in a complex and multimodal landscape. The challenges in medical image segmentation arise due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries. The resulting search space is therefore often noisy with a multitude of local optima. Not only does the genetic algorithmic framework prove to be effective in coming out of local optima, it also brings considerable flexibility into the segmentation procedure. In this paper, an attempt has been made to review the major applications of GAs to the domain of medical image segmentation.

  20. Remote sensing image segmentation based on Hadoop cloud platform

    Science.gov (United States)

    Li, Jie; Zhu, Lingling; Cao, Fubin

    2018-01-01

    To solve the problem that the remote sensing image segmentation speed is slow and the real-time performance is poor, this paper studies the method of remote sensing image segmentation based on Hadoop platform. On the basis of analyzing the structural characteristics of Hadoop cloud platform and its component MapReduce programming, this paper proposes a method of image segmentation based on the combination of OpenCV and Hadoop cloud platform. Firstly, the MapReduce image processing model of Hadoop cloud platform is designed, the input and output of image are customized and the segmentation method of the data file is rewritten. Then the Mean Shift image segmentation algorithm is implemented. Finally, this paper makes a segmentation experiment on remote sensing image, and uses MATLAB to realize the Mean Shift image segmentation algorithm to compare the same image segmentation experiment. The experimental results show that under the premise of ensuring good effect, the segmentation rate of remote sensing image segmentation based on Hadoop cloud Platform has been greatly improved compared with the single MATLAB image segmentation, and there is a great improvement in the effectiveness of image segmentation.

  1. Metrics for image segmentation

    Science.gov (United States)

    Rees, Gareth; Greenway, Phil; Morray, Denise

    1998-07-01

    An important challenge in mapping image-processing techniques onto applications is the lack of quantitative performance measures. From a systems engineering perspective these are essential if system level requirements are to be decomposed into sub-system requirements which can be understood in terms of algorithm selection and performance optimization. Nowhere in computer vision is this more evident than in the area of image segmentation. This is a vigorous and innovative research activity, but even after nearly two decades of progress, it remains almost impossible to answer the question 'what would the performance of this segmentation algorithm be under these new conditions?' To begin to address this shortcoming, we have devised a well-principled metric for assessing the relative performance of two segmentation algorithms. This allows meaningful objective comparisons to be made between their outputs. It also estimates the absolute performance of an algorithm given ground truth. Our approach is an information theoretic one. In this paper, we describe the theory and motivation of our method, and present practical results obtained from a range of state of the art segmentation methods. We demonstrate that it is possible to measure the objective performance of these algorithms, and to use the information so gained to provide clues about how their performance might be improved.

  2. Incorporation of squalene into rod outer segments

    International Nuclear Information System (INIS)

    Keller, R.K.; Fliesler, S.J.

    1990-01-01

    We have reported previously that squalene is the major radiolabeled nonsaponifiable lipid product derived from [ 3 H]acetate in short term incubations of frog retinas. In the present study, we demonstrate that newly synthesized squalene is incorporated into rod outer segments under similar in vitro conditions. We show further that squalene is an endogenous constituent of frog rod outer segment membranes; its concentration is approximately 9.5 nmol/mumol of phospholipid or about 9% of the level of cholesterol. Pulse-chase experiments with radiolabeled precursors revealed no metabolism of outer segment squalene to sterols in up to 20 h of chase. Taken together with our previous absolute rate studies, these results suggest that most, if not all, of the squalene synthesized by the frog retina is transported to rod outer segments. Synthesis of protein is not required for squalene transport since puromycin had no effect on squalene incorporation into outer segments. Conversely, inhibition of isoprenoid synthesis with mevinolin had no effect on the incorporation of opsin into the outer segment. These latter results support the conclusion that the de novo synthesis and subsequent intracellular trafficking of opsin and isoprenoid lipids destined for the outer segment occur via independent mechanisms

  3. Interactive segmentation techniques algorithms and performance evaluation

    CERN Document Server

    He, Jia; Kuo, C-C Jay

    2013-01-01

    This book focuses on interactive segmentation techniques, which have been extensively studied in recent decades. Interactive segmentation emphasizes clear extraction of objects of interest, whose locations are roughly indicated by human interactions based on high level perception. This book will first introduce classic graph-cut segmentation algorithms and then discuss state-of-the-art techniques, including graph matching methods, region merging and label propagation, clustering methods, and segmentation methods based on edge detection. A comparative analysis of these methods will be provided

  4. Market segmentation using perceived constraints

    Science.gov (United States)

    Jinhee Jun; Gerard Kyle; Andrew Mowen

    2008-01-01

    We examined the practical utility of segmenting potential visitors to Cleveland Metroparks using their constraint profiles. Our analysis identified three segments based on their scores on the dimensions of constraints: Other priorities--visitors who scored the highest on 'other priorities' dimension; Highly Constrained--visitors who scored relatively high on...

  5. Reduplication Facilitates Early Word Segmentation

    Science.gov (United States)

    Ota, Mitsuhiko; Skarabela, Barbora

    2018-01-01

    This study explores the possibility that early word segmentation is aided by infants' tendency to segment words with repeated syllables ("reduplication"). Twenty-four nine-month-olds were familiarized with passages containing one novel reduplicated word and one novel non-reduplicated word. Their central fixation times in response to…

  6. Recognition Using Classification and Segmentation Scoring

    National Research Council Canada - National Science Library

    Kimball, Owen; Ostendorf, Mari; Rohlicek, Robin

    1992-01-01

    .... We describe an approach to connected word recognition that allows the use of segmental information through an explicit decomposition of the recognition criterion into classification and segmentation scoring...

  7. Multifractal-based nuclei segmentation in fish images.

    Science.gov (United States)

    Reljin, Nikola; Slavkovic-Ilic, Marijeta; Tapia, Coya; Cihoric, Nikola; Stankovic, Srdjan

    2017-09-01

    The method for nuclei segmentation in fluorescence in-situ hybridization (FISH) images, based on the inverse multifractal analysis (IMFA) is proposed. From the blue channel of the FISH image in RGB format, the matrix of Holder exponents, with one-by-one correspondence with the image pixels, is determined first. The following semi-automatic procedure is proposed: initial nuclei segmentation is performed automatically from the matrix of Holder exponents by applying predefined hard thresholding; then the user evaluates the result and is able to refine the segmentation by changing the threshold, if necessary. After successful nuclei segmentation, the HER2 (human epidermal growth factor receptor 2) scoring can be determined in usual way: by counting red and green dots within segmented nuclei, and finding their ratio. The IMFA segmentation method is tested over 100 clinical cases, evaluated by skilled pathologist. Testing results show that the new method has advantages compared to already reported methods.

  8. Segmentation of the lumen and media-adventitia boundaries of the common carotid artery from 3D ultrasound images

    Science.gov (United States)

    Ukwatta, E.; Awad, J.; Ward, A. D.; Samarabandu, J.; Krasinski, A.; Parraga, G.; Fenster, A.

    2011-03-01

    Three-dimensional ultrasound (3D US) vessel wall volume (VWV) measurements provide high measurement sensitivity and reproducibility for the monitoring and assessment of carotid atherosclerosis. In this paper, we describe a semiautomated approach based on the level set method to delineate the media-adventitia and lumen boundaries of the common carotid artery from 3D US images to support the computation of VWV. Due to the presence of plaque and US image artifacts, the carotid arteries are challenging to segment using image information alone. Our segmentation framework combines several image cues with domain knowledge and limited user interaction. Our method was evaluated with respect to manually outlined boundaries on 430 2D US images extracted from 3D US images of 30 patients who have carotid stenosis of 60% or more. The VWV given by our method differed from that given by manual segmentation by 6.7% +/- 5.0%. For the media-adventitia and lumen segmentations, respectively, our method yielded Dice coefficients of 95.2% +/- 1.6%, 94.3% +/- 2.6%, mean absolute distances of 0.3 +/- 0.1 mm, 0.2 +/- 0.1 mm, maximum absolute distances of 0.8 +/- 0.4 mm, 0.6 +/- 0.3 mm, and volume differences of 4.2% +/- 3.1%, 3.4% +/- 2.6%. The realization of a semi-automated segmentation method will accelerate the translation of 3D carotid US to clinical care for the rapid, non-invasive, and economical monitoring of atherosclerotic disease progression and regression during therapy.

  9. Effects of floor cooling during high ambient temperatures on the lying behavior and productivity of growing finishing pigs

    NARCIS (Netherlands)

    Huynh Thi Thanh Thuy,; Aarnink, A.J.A.; Spoolder, H.A.M.; Verstegen, M.W.A.; Kemp, B.

    2004-01-01

    Given that exposing rapidly growing pigs to high ambient temperatures can induce heat stress, which reduces their welfare and production, this study looked at the influence of floor cooling on pigs¿ behavior and performance. Pens in room 1 had a solid floor (60%) and a metal slatted floor (40%). The

  10. Tobacco-control policies in tobacco-growing states: where tobacco was king.

    Science.gov (United States)

    Fallin, Amanda; Glantz, Stanton A

    2015-06-01

    POLICY POINTS: The tobacco companies prioritized blocking tobacco-control policies in tobacco-growing states and partnered with tobacco farmers to oppose tobacco-control policies. The 1998 Master Settlement Agreement, which settled state litigation against the cigarette companies, the 2004 tobacco-quota buyout, and the companies' increasing use of foreign tobacco led to a rift between the companies and tobacco farmers. In 2003, the first comprehensive smoke-free local law was passed in a major tobacco-growing state, and there has been steady progress in the region since then. Health advocates should educate the public and policymakers on the changing reality in tobacco-growing states, notably the major reduction in the volume of tobacco produced. The 5 major tobacco-growing states (Kentucky, North Carolina, South Carolina, Tennessee, and Virginia) are disproportionately affected by the tobacco epidemic, with higher rates of smoking and smoking-induced disease. These states also have fewer smoke-free laws and lower tobacco taxes, 2 evidence-based policies that reduce tobacco use. Historically, the tobacco farmers and hospitality associations allied with the tobacco companies to oppose these policies. This research is based on 5 detailed case studies of these states, which included key informant interviews, previously secret tobacco industry documents (available at http://legacy.library.ucsf.edu), and media articles. This was supplemented with additional tobacco document and media searches specifically for this article. The tobacco companies were particularly concerned about blocking tobacco-control policies in the tobacco-growing states by promoting a pro-tobacco culture, beginning in the late 1960s. Nevertheless, since 2003, there has been rapid progress in the tobacco-growing states' passage of smoke-free laws. This progress came after the alliance between the tobacco companies and the tobacco farmers fractured and hospitality organizations stopped opposing smoke

  11. Ethical, moral and social dimensions in farm production practices: a segmentation study to assess Irish consumers’ perceptions of meat quality

    OpenAIRE

    Regan Á.; Henchion M; McIntyre B

    2018-01-01

    Growing consumer concerns with modern farming and food production systems indicate a significant market opportunity for meat production practices that consider ethical, moral and social value traits. In the current study, we aimed to identify and characterise distinct segments of Irish consumers based on their perceptions of the quality of meat from different farm-level production practices (organic farming, high animal welfare standards, free range farming, and “natural”, treatment-free feed...

  12. Unusual fast-growing ovarian cystic teratoma during pregnancy presenting with intracystic fat "floating balls" appearance.

    Science.gov (United States)

    Donnadieu, Anne Claire; Deffieux, Xavier; Le Ray, Camille; Mordefroid, Marie; Frydman, René; Fernandez, Hervé

    2006-12-01

    A large ovarian cyst was diagnosed at 22 weeks' of gestation in a 32-year-old woman. The ultrasonographic appearance of the ovarian cyst was unusual with multiple mobile, spherical echogenic structures floating in the cystic mass, called intracystic "fat balls." Right adnexectomy was performed by laparotomy at 28 weeks' of gestation, because of rapid growth and overall size exceeding 20 cm. Pathological examination confirmed ovarian cystic teratoma. Usually, dermoid cysts are slow-growing, even in premenopausal women. The exact mechanism related to the fast growth during pregnancy is unknown. It could be related to an unusual pattern of estrogen (E)/P receptors expression in the cystic teratoma. This case shows that a fast-growing, mature ovarian cystic teratoma may occur during pregnancy.

  13. The Importance of Marketing Segmentation

    Science.gov (United States)

    Martin, Gillian

    2011-01-01

    The rationale behind marketing segmentation is to allow businesses to focus on their consumers' behaviors and purchasing patterns. If done effectively, marketing segmentation allows an organization to achieve its highest return on investment (ROI) in turn for its marketing and sales expenses. If an organization markets its products or services to…

  14. Capability of ds-DNA duplex structure in growing fluorescent silver nanoclusters

    International Nuclear Information System (INIS)

    Wu, Tao; Lin, Fan; Hu, Yuehua; Wang, Ying; Zhou, Xiaoshun; Shao, Yong

    2016-01-01

    Silver nanoclusters (AgNCs) have attracted wide interests in variant fields due to their easy synthesis and practical tunability in fluorescence properties. DNA has been generally used as the host to grow AgNCs due to the sequence-dependent fluorescence behavior. Actually, in such DNA, various ss-DNA segments that are structurally confined by the rigid ds-DNA counterparts have been used as the AgNCsГ—Ві growth sites. However, whether the ds-DNA structure plays somewhat role in AgNCsГ—Ві creation has not been well elucidated. Herein, we found that ds-DNA can also accommodate the growth of fluorescent AgNCs. The fluorescent AgNCs grown on ds-DNA should be separated each other and the G/C base pairs with right context sequences are the growth sites of fluorescent AgNCs. The intermediate A/T base pair among the continuous G/C ones seems to quench the growth of fluorescent AgNCs. For the repeat sequences, the fluorescence band position of AgNCs is not changed but the intensity is enhanced upon increasing the ds-DNA length, which is different from the results obtained with the previously reported ss-DNAs. AgNCs should be grown on the ds-DNA major groove, as convinced by the cytosine methylation experiment. Our work demonstrates that besides the ss-DNA role in defining AgNCs, one should also take into account the critical role of the ds-DNA segment in tuning the AgNCsГ—Ві fluorescence property.

  15. Cultural systems for growing potatoes in space

    Science.gov (United States)

    Tibbitts, T.; Bula, R.; Corey, R.; Morrow, R.

    1988-01-01

    Higher plants are being evaluated for life support to provide needed food, oxygen and water as well as removal of carbon dioxide from the atmosphere. The successful utilization of plants in space will require the development of not only highly productive growing systems but also highly efficient bioregenerative systems. It will be necessary to recycle all inedible plant parts and all human wastes so that the entire complement of elemental compounds can be reused. Potatoes have been proposed as one of the desirable crops because they are 1) extremely productive, yielding more than 100 metric tons per hectare from field plantings, 2) the edible tubers are high in digestible starch (70%) and protein (10%) on a dry weight basis, 3) up to 80% of the total plant production is in tubers and thus edible, 4) the plants are easily propagated either from tubers or from tissue culture plantlets, 5) the tubers can be utilized with a minimum of processing, and 6) potatoes can be prepared in a variety of different forms for the human diet (Tibbitts et al., 1982). However potatoes have a growth pattern that complicates the development of growing the plants in controlled systems. Tubers are borne on underground stems that are botanically termed 'rhizomes', but in common usage termed 'stolons'. The stolons must be maintained in a dark, moist area with sufficient provision for enlargement of tubers. Stems rapidly terminate in flowers forcing extensive branching and spreading of plants so that individual plants will cover 0.2 m2 or more area. Thus the growing system must be developed to provide an area that is darkened for tuber and root growth and of sufficient size for plant spread. A system developed for growing potatoes, or any plants, in space will have certain requirements that must be met to make them a useful part of a life support system. The system must 1) be constructed of materials, and involve media, that can be reused for many successive cycles of plant growth, 2

  16. Boundary segmentation for fluorescence microscopy using steerable filters

    Science.gov (United States)

    Ho, David Joon; Salama, Paul; Dunn, Kenneth W.; Delp, Edward J.

    2017-02-01

    Fluorescence microscopy is used to image multiple subcellular structures in living cells which are not readily observed using conventional optical microscopy. Moreover, two-photon microscopy is widely used to image structures deeper in tissue. Recent advancement in fluorescence microscopy has enabled the generation of large data sets of images at different depths, times, and spectral channels. Thus, automatic object segmentation is necessary since manual segmentation would be inefficient and biased. However, automatic segmentation is still a challenging problem as regions of interest may not have well defined boundaries as well as non-uniform pixel intensities. This paper describes a method for segmenting tubular structures in fluorescence microscopy images of rat kidney and liver samples using adaptive histogram equalization, foreground/background segmentation, steerable filters to capture directional tendencies, and connected-component analysis. The results from several data sets demonstrate that our method can segment tubular boundaries successfully. Moreover, our method has better performance when compared to other popular image segmentation methods when using ground truth data obtained via manual segmentation.

  17. The Miracle Baby Grows Up: Hypoplastic Left Heart Syndrome in the Adult.

    Science.gov (United States)

    Lewis, Matthew; Rosenbaum, Marlon

    2017-08-01

    Hypoplastic left heart syndrome (HLHS) is characterized by underdevelopment of the mitral valve, left ventricle, and aorta and is ultimately palliated with a single-ventricle repair. Universally fatal in infancy prior to the advent of modern surgical techniques, the majority of HLHS patients will now reach adulthood. However, despite improvements in early survival, the HLHS population continues to face significant morbidity and early mortality. This review delineates common sources of patient morbidity and highlights areas in need of additional research for this growing segment of the adult congenital heart disease population. It has become increasingly clear that palliated adult single ventricle patients, like those with HLHS, face significant life-long morbidity from elevated systemic venous pressures as a consequence of the Fontan procedure. Downstream organ dysfunction secondary to elevated Fontan pressures has the potential to significantly impact long-term management decisions, including strategies of organ allocation. Because of the presence of a morphologic systemic right ventricle, HLHS patients may be at even higher risk than other adult patients with a Fontan. Because the adult HLHS population continues to grow, recognition of common sources of patient morbidity and mortality is becoming increasingly important. A coordinated effort between patients and providers is necessary to address the many remaining areas of clinical uncertainty to help ensure continued improvement in patient prognosis and quality of life.

  18. Challenges of the growing African cement market – environmental issues, regulative framework, and quality infrastructure requirements

    Directory of Open Access Journals (Sweden)

    Schmidt Wolfram

    2018-01-01

    Full Text Available The African cement, concrete and construction business is growing at rapid pace. The cement sales are expected to grow rapidly until 2050. The number of newly built cement plants increases dramatically and in addition more cements are being imported from outside the continent, e.g. from Turkey, Pakistan, Indonesia, and China, driven by overcapacities in the countries of origin. This causes a high number of potentials and challenges at the same time. Newly built cement plants can operate directly at best technological state of the art and thus incorporate more sustainable technologies as well as produce new and more sustainable products such as cements blended with sustainable supplementary cementitious materials such as calcined clays, and industrial or agricultural by products. At the same time the new variety of binding agent as well as the international imports, which are driven by price considerations, make the cement market prone to quality scatter. This puts pressure on the quality control regulations and institutions to ensure safety of construction, healthy application, and environmental safety for the population. The paper presents possible solutions to build up the rapidly increasing African cement production more sustainably than in the rest of the world as well as the related challenges and obstacles that need to be overcome. Based on experiences with a series of pan-African cement testing laboratory proficiency schemes conclusions are made on technical, regulative and political level.

  19. Connecting textual segments

    DEFF Research Database (Denmark)

    Brügger, Niels

    2017-01-01

    history than just the years of the emergence of the web, the chapter traces the history of how segments of text have deliberately been connected to each other by the use of specific textual and media features, from clay tablets, manuscripts on parchment, and print, among others, to hyperlinks on stand......In “Connecting textual segments: A brief history of the web hyperlink” Niels Brügger investigates the history of one of the most fundamental features of the web: the hyperlink. Based on the argument that the web hyperlink is best understood if it is seen as another step in a much longer and broader...

  20. A comparative study on medical image segmentation methods

    Directory of Open Access Journals (Sweden)

    Praylin Selva Blessy SELVARAJ ASSLEY

    2014-03-01

    Full Text Available Image segmentation plays an important role in medical images. It has been a relevant research area in computer vision and image analysis. Many segmentation algorithms have been proposed for medical images. This paper makes a review on segmentation methods for medical images. In this survey, segmentation methods are divided into five categories: region based, boundary based, model based, hybrid based and atlas based. The five different categories with their principle ideas, advantages and disadvantages in segmenting different medical images are discussed.

  1. Biotic response to late Quaternary rapid climate switches in Santa Barbara Basin: Ecological and evolutionary implications

    International Nuclear Information System (INIS)

    Cannariato, K.G.; Kennett, J.P.; Behl, R.J.

    1999-01-01

    Benthic foraminiferal assemblages from Santa Barbara Basin exhibit major faunal and ecological switches associated with late Quaternary millennial- to decadal-scale global climate oscillations. Repeated turnovers of entire faunas occurred rapidly (<40--400 yr) without extinction or speciation in conjunction with Dansgaard-Oeschger shifts in thermohaline circulation, ventilation, and climate, confirming evolutionary model predictions of Roy et al. Consistent faunal successions of dysoxic taxa during successive interstadials reflect the extreme sensitivity and adaptation of the benthic ecosystem to the rapid environmental changes that marked the late Quaternary and possibly other transitional intervals in the history of the Earth's ocean-atmosphere-cryosphere system. These data support the hypothesis that broad segments of the biosphere are well adapted to rapid climate change

  2. Distance measures for image segmentation evaluation

    OpenAIRE

    Monteiro, Fernando C.; Campilho, Aurélio

    2012-01-01

    In this paper we present a study of evaluation measures that enable the quantification of the quality of an image segmentation result. Despite significant advances in image segmentation techniques, evaluation of these techniques thus far has been largely subjective. Typically, the effectiveness of a new algorithm is demonstrated only by the presentation of a few segmented images and is otherwise left to subjective evaluation by the reader. Such an evaluation criterion can be useful for differ...

  3. Segmentation of complex document

    Directory of Open Access Journals (Sweden)

    Souad Oudjemia

    2014-06-01

    Full Text Available In this paper we present a method for segmentation of documents image with complex structure. This technique based on GLCM (Grey Level Co-occurrence Matrix used to segment this type of document in three regions namely, 'graphics', 'background' and 'text'. Very briefly, this method is to divide the document image, in block size chosen after a series of tests and then applying the co-occurrence matrix to each block in order to extract five textural parameters which are energy, entropy, the sum entropy, difference entropy and standard deviation. These parameters are then used to classify the image into three regions using the k-means algorithm; the last step of segmentation is obtained by grouping connected pixels. Two performance measurements are performed for both graphics and text zones; we have obtained a classification rate of 98.3% and a Misclassification rate of 1.79%.

  4. Hemorrhage Detection and Segmentation in Traumatic Pelvic Injuries

    Science.gov (United States)

    Davuluri, Pavani; Wu, Jie; Tang, Yang; Cockrell, Charles H.; Ward, Kevin R.; Najarian, Kayvan; Hargraves, Rosalyn H.

    2012-01-01

    Automated hemorrhage detection and segmentation in traumatic pelvic injuries is vital for fast and accurate treatment decision making. Hemorrhage is the main cause of deaths in patients within first 24 hours after the injury. It is very time consuming for physicians to analyze all Computed Tomography (CT) images manually. As time is crucial in emergence medicine, analyzing medical images manually delays the decision-making process. Automated hemorrhage detection and segmentation can significantly help physicians to analyze these images and make fast and accurate decisions. Hemorrhage segmentation is a crucial step in the accurate diagnosis and treatment decision-making process. This paper presents a novel rule-based hemorrhage segmentation technique that utilizes pelvic anatomical information to segment hemorrhage accurately. An evaluation measure is used to quantify the accuracy of hemorrhage segmentation. The results show that the proposed method is able to segment hemorrhage very well, and the results are promising. PMID:22919433

  5. SALIENCY BASED SEGMENTATION OF SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    A. Sharma

    2015-03-01

    Full Text Available Saliency gives the way as humans see any image and saliency based segmentation can be eventually helpful in Psychovisual image interpretation. Keeping this in view few saliency models are used along with segmentation algorithm and only the salient segments from image have been extracted. The work is carried out for terrestrial images as well as for satellite images. The methodology used in this work extracts those segments from segmented image which are having higher or equal saliency value than a threshold value. Salient and non salient regions of image become foreground and background respectively and thus image gets separated. For carrying out this work a dataset of terrestrial images and Worldview 2 satellite images (sample data are used. Results show that those saliency models which works better for terrestrial images are not good enough for satellite image in terms of foreground and background separation. Foreground and background separation in terrestrial images is based on salient objects visible on the images whereas in satellite images this separation is based on salient area rather than salient objects.

  6. Segmentation of internal brain structures in three-dimensional nuclear magnetic resonance imaging

    International Nuclear Information System (INIS)

    Geraud, Th.

    1998-01-01

    For neurological studies, the in vivo aspect of imaging systems is very attractive. Brain images are currently a classical tool used in clinical routine and research. The most appropriate system to observe brain anatomy is tridimensional magnetic resonance imaging, and a major issue of image processing is to segment automatically cerebral structures. This is the scope of our thesis. The number of applications is steadily growing: morphometric measurements, pathology detection, surgery planning, getting a reference for functional studies,a and so forth. The use of pattern recognition to classify the different cerebral tissues from the only radiometric levels of the images is limited. Even supervised, these methods can not lead to distinguish easily several classes of grey matter. When these methods are automatic, their use has to be empirical in order to ensure robust results, and has to be restricted to regions of interest in order to get reliable results. As these methods do not fully respect the spatial consistency of classes in the images, we have introduced contextual information with the help of different formalisms. With Markovian regularization, we have shown that energetic terms of localization permit the separation of two grey classes: cortex and central nuclei. With mathematical morphology, we have proposed processing chains dedicated to several cerebral objects; in particular, brain segmentation is robust and reproducible, and we have successfully obtained individual markers for lateral ventricles, caudate nuclei, putamen and thalami. We have also proposed a contextual method to estimate pure tissue characteristics from a rough segmentation. Our main contribution has been to present a recognition method which is progressive and atlas guided. The originality of this method is manifold. At first, it takes into account structural information processed as flexible spatial constraints the formalism of which relies on fuzzy set theory and information fusion

  7. Multimodal navigated skull base tumor resection using image-based vascular and cranial nerve segmentation: A prospective pilot study.

    Science.gov (United States)

    Dolati, Parviz; Gokoglu, Abdulkerim; Eichberg, Daniel; Zamani, Amir; Golby, Alexandra; Al-Mefty, Ossama

    2015-01-01

    Skull base tumors frequently encase or invade adjacent normal neurovascular structures. For this reason, optimal tumor resection with incomplete knowledge of patient anatomy remains a challenge. To determine the accuracy and utility of image-based preoperative segmentation in skull base tumor resections, we performed a prospective study. Ten patients with skull base tumors underwent preoperative 3T magnetic resonance imaging, which included thin section three-dimensional (3D) space T2, 3D time of flight, and magnetization-prepared rapid acquisition gradient echo sequences. Imaging sequences were loaded in the neuronavigation system for segmentation and preoperative planning. Five different neurovascular landmarks were identified in each case and measured for accuracy using the neuronavigation system. Each segmented neurovascular element was validated by manual placement of the navigation probe, and errors of localization were measured. Strong correspondence between image-based segmentation and microscopic view was found at the surface of the tumor and tumor-normal brain interfaces in all cases. The accuracy of the measurements was 0.45 ± 0.21 mm (mean ± standard deviation). This information reassured the surgeon and prevented vascular injury intraoperatively. Preoperative segmentation of the related cranial nerves was possible in 80% of cases and helped the surgeon localize involved cranial nerves in all cases. Image-based preoperative vascular and neural element segmentation with 3D reconstruction is highly informative preoperatively and could increase the vigilance of neurosurgeons for preventing neurovascular injury during skull base surgeries. Additionally, the accuracy found in this study is superior to previously reported measurements. This novel preliminary study is encouraging for future validation with larger numbers of patients.

  8. Segmentation precedes face categorization under suboptimal conditions

    Directory of Open Access Journals (Sweden)

    Carlijn eVan Den Boomen

    2015-05-01

    Full Text Available Both categorization and segmentation processes play a crucial role in face perception. However, the functional relation between these subprocesses is currently unclear. The present study investigates the temporal relation between segmentation-related and category-selective responses in the brain, using electroencephalography (EEG. Surface segmentation and category content were both manipulated using texture-defined objects, including faces. This allowed us to study brain activity related to segmentation and to categorization. In the main experiment, participants viewed texture-defined objects for a duration of 800 ms. EEG results revealed that segmentation-related responses precede category-selective responses. Three additional experiments revealed that the presence and timing of categorization depends on stimulus properties and presentation duration. Photographic objects were presented for a long and short (92 ms duration and evoked fast category-selective responses in both cases. On the other hand, presentation of texture-defined objects for a short duration only evoked segmentation-related but no category-selective responses. Category-selective responses were much slower when evoked by texture-defined than by photographic objects. We suggest that in case of categorization of objects under suboptimal conditions, such as when low-level stimulus properties are not sufficient for fast object categorization, segmentation facilitates the slower categorization process.

  9. A Kalman Filtering Perspective for Multiatlas Segmentation*

    Science.gov (United States)

    Gao, Yi; Zhu, Liangjia; Cates, Joshua; MacLeod, Rob S.; Bouix, Sylvain; Tannenbaum, Allen

    2016-01-01

    In multiatlas segmentation, one typically registers several atlases to the novel image, and their respective segmented label images are transformed and fused to form the final segmentation. In this work, we provide a new dynamical system perspective for multiatlas segmentation, inspired by the following fact: The transformation that aligns the current atlas to the novel image can be not only computed by direct registration but also inferred from the transformation that aligns the previous atlas to the image together with the transformation between the two atlases. This process is similar to the global positioning system on a vehicle, which gets position by inquiring from the satellite and by employing the previous location and velocity—neither answer in isolation being perfect. To solve this problem, a dynamical system scheme is crucial to combine the two pieces of information; for example, a Kalman filtering scheme is used. Accordingly, in this work, a Kalman multiatlas segmentation is proposed to stabilize the global/affine registration step. The contributions of this work are twofold. First, it provides a new dynamical systematic perspective for standard independent multiatlas registrations, and it is solved by Kalman filtering. Second, with very little extra computation, it can be combined with most existing multiatlas segmentation schemes for better registration/segmentation accuracy. PMID:26807162

  10. Segmentation precedes face categorization under suboptimal conditions.

    Science.gov (United States)

    Van Den Boomen, Carlijn; Fahrenfort, Johannes J; Snijders, Tineke M; Kemner, Chantal

    2015-01-01

    Both categorization and segmentation processes play a crucial role in face perception. However, the functional relation between these subprocesses is currently unclear. The present study investigates the temporal relation between segmentation-related and category-selective responses in the brain, using electroencephalography (EEG). Surface segmentation and category content were both manipulated using texture-defined objects, including faces. This allowed us to study brain activity related to segmentation and to categorization. In the main experiment, participants viewed texture-defined objects for a duration of 800 ms. EEG results revealed that segmentation-related responses precede category-selective responses. Three additional experiments revealed that the presence and timing of categorization depends on stimulus properties and presentation duration. Photographic objects were presented for a long and short (92 ms) duration and evoked fast category-selective responses in both cases. On the other hand, presentation of texture-defined objects for a short duration only evoked segmentation-related but no category-selective responses. Category-selective responses were much slower when evoked by texture-defined than by photographic objects. We suggest that in case of categorization of objects under suboptimal conditions, such as when low-level stimulus properties are not sufficient for fast object categorization, segmentation facilitates the slower categorization process.

  11. Improved document image segmentation algorithm using multiresolution morphology

    Science.gov (United States)

    Bukhari, Syed Saqib; Shafait, Faisal; Breuel, Thomas M.

    2011-01-01

    Page segmentation into text and non-text elements is an essential preprocessing step before optical character recognition (OCR) operation. In case of poor segmentation, an OCR classification engine produces garbage characters due to the presence of non-text elements. This paper describes modifications to the text/non-text segmentation algorithm presented by Bloomberg,1 which is also available in his open-source Leptonica library.2The modifications result in significant improvements and achieved better segmentation accuracy than the original algorithm for UW-III, UNLV, ICDAR 2009 page segmentation competition test images and circuit diagram datasets.

  12. Apparatus For Laminating Segmented Core For Electric Machine

    Science.gov (United States)

    Lawrence, Robert Anthony; Stabel, Gerald R

    2003-06-17

    A segmented core for an electric machine includes segments stamped from coated electric steel. The segments each have a first end, a second end, and winding openings. A predetermined number of segments are placed end-to-end to form layers. The layers are stacked such that each of the layers is staggered from adjacent layers by a predetermined rotation angle. The winding openings of each of the layers are in vertical alignment with the winding openings of the adjacent layers. The stack of layers is secured to form the segmented core.

  13. SEGMENTATION OF SME PORTFOLIO IN BANKING SYSTEM

    Directory of Open Access Journals (Sweden)

    Namolosu Simona Mihaela

    2013-07-01

    Full Text Available The Small and Medium Enterprises (SMEs represent an important target market for commercial Banks. In this respect, finding the best methods for designing and implementing the optimal marketing strategies (for this target are a continuous concern for the marketing specialists and researchers from the banking system; the purpose is to find the most suitable service model for these companies. SME portfolio of a bank is not homogeneous, different characteristics and behaviours being identified. The current paper reveals empirical evidence about SME portfolio characteristics and segmentation methods used in banking system. Its purpose is to identify if segmentation has an impact in finding the optimal marketing strategies and service model and if this hypothesis might be applicable for any commercial bank, irrespective of country/ region. Some banks are segmenting the SME portfolio by a single criterion: the annual company (official turnover; others are considering also profitability and other financial indicators of the company. In some cases, even the banking behaviour becomes a criterion. For all cases, creating scenarios with different thresholds and estimating the impact in profitability and volumes are two mandatory steps in establishing the final segmentation (criteria matrix. Details about each of these segmentation methods may be found in the paper. Testing the final matrix of criteria is also detailed, with the purpose of making realistic estimations. Example for lending products is provided; the product offer is presented as responding to needs of targeted sub segment and therefore being correlated with the sub segment characteristics. Identifying key issues and trends leads to further action plan proposal. Depending on overall strategy and commercial target of the bank, the focus may shift, one or more sub segments becoming high priority (for acquisition/ activation/ retention/ cross sell/ up sell/ increase profitability etc., while

  14. Temperature Sensitivity of Soil Respiration to Nitrogen Fertilization: Varying Effects between Growing and Non-Growing Seasons

    Science.gov (United States)

    Liu, Qingfang; Wang, Rui; Li, Rujian; Hu, Yaxian; Guo, Shengli

    2016-01-01

    Nitrogen (N) fertilization has a considerable effect on food production and carbon cycling in agro-ecosystems. However, the impacts of N fertilization rates on the temperature sensitivity of soil respiration (Q10) were controversial. Five N rates (N0, N45, N90, N135, and N180) were applied to a continuous winter wheat (Triticum aestivum L.) crop on the semi-arid Loess Plateau, and the in situ soil respiration was monitored during five consecutive years from 2008 to 2013. During the growing season, the mean soil respiration rates increased with increasing N fertilization rates, peaking at 1.53 μmol m−2s−1 in the N135 treatment. A similar dynamic pattern was observed during the non-growing season, yet on average with 7.3% greater soil respiration rates than the growing season. In general for all the N fertilization treatments, the mean Q10 value during the non-growing season was significantly greater than that during the growing season. As N fertilization rates increased, the Q10 values did not change significantly in the growing season but significantly decreased in the non-growing season. Overall, N fertilization markedly influenced soil respirations and Q10 values, in particular posing distinct effects on the Q10 values between the growing and non-growing seasons. PMID:27992576

  15. Event segmentation ability uniquely predicts event memory.

    Science.gov (United States)

    Sargent, Jesse Q; Zacks, Jeffrey M; Hambrick, David Z; Zacks, Rose T; Kurby, Christopher A; Bailey, Heather R; Eisenberg, Michelle L; Beck, Taylor M

    2013-11-01

    Memory for everyday events plays a central role in tasks of daily living, autobiographical memory, and planning. Event memory depends in part on segmenting ongoing activity into meaningful units. This study examined the relationship between event segmentation and memory in a lifespan sample to answer the following question: Is the ability to segment activity into meaningful events a unique predictor of subsequent memory, or is the relationship between event perception and memory accounted for by general cognitive abilities? Two hundred and eight adults ranging from 20 to 79years old segmented movies of everyday events and attempted to remember the events afterwards. They also completed psychometric ability tests and tests measuring script knowledge for everyday events. Event segmentation and script knowledge both explained unique variance in event memory above and beyond the psychometric measures, and did so as strongly in older as in younger adults. These results suggest that event segmentation is a basic cognitive mechanism, important for memory across the lifespan. Copyright © 2013 Elsevier B.V. All rights reserved.

  16. Retina image–based optic disc segmentation

    Directory of Open Access Journals (Sweden)

    Ching-Lin Wang

    2016-05-01

    Full Text Available The change of optic disc can be used to diagnose many eye diseases, such as glaucoma, diabetic retinopathy and macular degeneration. Moreover, retinal blood vessel pattern is unique for human beings even for identical twins. It is a highly stable pattern in biometric identification. Since optic disc is the beginning of the optic nerve and main blood vessels in retina, it can be used as a reference point of identification. Therefore, optic disc segmentation is an important technique for developing a human identity recognition system and eye disease diagnostic system. This article hence presents an optic disc segmentation method to extract the optic disc from a retina image. The experimental results show that the optic disc segmentation method can give impressive results in segmenting the optic disc from a retina image.

  17. The Process of Marketing Segmentation Strategy Selection

    OpenAIRE

    Ionel Dumitru

    2007-01-01

    The process of marketing segmentation strategy selection represents the essence of strategical marketing. We present hereinafter the main forms of the marketing statategy segmentation: undifferentiated marketing, differentiated marketing, concentrated marketing and personalized marketing. In practice, the companies use a mix of these marketing segmentation methods in order to maximize the proffit and to satisfy the consumers’ needs.

  18. Possibilities of segmentation variables in relation with advertising

    OpenAIRE

    Erbanová, Nela

    2011-01-01

    The aim of this thesis is to capture significant segmentation variables that shape marketing communication with an emphasis on advertising. The theoretical part deals with the concepts of market segmentation, segmentation variables, marketing communication, advertising and research. The practical part is focused on the realization of the actual research using a questionnaire survey and the evaluation of questions from Market Media Lifestyle. Only traditional descriptive segmentation variables...

  19. Open-source software platform for medical image segmentation applications

    Science.gov (United States)

    Namías, R.; D'Amato, J. P.; del Fresno, M.

    2017-11-01

    Segmenting 2D and 3D images is a crucial and challenging problem in medical image analysis. Although several image segmentation algorithms have been proposed for different applications, no universal method currently exists. Moreover, their use is usually limited when detection of complex and multiple adjacent objects of interest is needed. In addition, the continually increasing volumes of medical imaging scans require more efficient segmentation software design and highly usable applications. In this context, we present an extension of our previous segmentation framework which allows the combination of existing explicit deformable models in an efficient and transparent way, handling simultaneously different segmentation strategies and interacting with a graphic user interface (GUI). We present the object-oriented design and the general architecture which consist of two layers: the GUI at the top layer, and the processing core filters at the bottom layer. We apply the framework for segmenting different real-case medical image scenarios on public available datasets including bladder and prostate segmentation from 2D MRI, and heart segmentation in 3D CT. Our experiments on these concrete problems show that this framework facilitates complex and multi-object segmentation goals while providing a fast prototyping open-source segmentation tool.

  20. Levels of specificity of Xylaria species associated with fungus-growing termites: a phylogenetic approach

    DEFF Research Database (Denmark)

    Visser, Andre; Ros, V I D; De Beer, Z. W.

    2009-01-01

    of the ascomycete genus Xylaria appear and rapidly cover the fungus garden. This raises the question whether certain Xylaria species are specialised in occupying termite nests or whether they are just occasional visitors. We tested Xylaria specificity at four levels: (1) fungus-growing termites, (2) termite genera...... of the ITS region revealed 16 operational taxonomic units of Xylaria, indicating high levels of Xylaria species richness. Not much of this variation was explained by termite genus, species, or colony; thus, at level 2-4 the specificity is low. Analysis of the large subunit rDNA region, showed that all...... termite-associated Xylaria belong to a single clade, together with only three of the 26 non-termite-associated strains. Termite-associated Xylaria thus show specificity for fungus-growing termites (level 1). We did not find evidence for geographic or temporal structuring in these Xylaria phylogenies...