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Sample records for vessel segmentation approach

  1. Robust vessel detection and segmentation in ultrasound images by a data-driven approach

    Science.gov (United States)

    Guo, Ping; Wang, Qiang; Wang, Xiaotao; Hao, Zhihui; Xu, Kuanhong; Ren, Haibing; Kim, Jung Bae; Hwang, Youngkyoo

    2014-03-01

    This paper presents a learning based vessel detection and segmentation method in real-patient ultrasound (US) liver images. We aim at detecting multiple shaped vessels robustly and automatically, including vessels with weak and ambiguous boundaries. Firstly, vessel candidate regions are detected by a data-driven approach. Multi-channel vessel enhancement maps with complement performances are generated and aggregated under a Conditional Random Field (CRF) framework. Vessel candidates are obtained by thresholding the saliency map. Secondly, regional features are extracted and the probability of each region being a vessel is modeled by random forest regression. Finally, a fast levelset method is developed to refine vessel boundaries. Experiments have been carried out on an US liver dataset with 98 patients. The dataset contains both normal and abnormal liver images. The proposed method in this paper is compared with a traditional Hessian based method, and the average precision is promoted by 56 percents and 7.8 percents for vessel detection and classification, respectively. This improvement shows that our method is more robust to noise, therefore has a better performance than the Hessian based method for the detection of vessels with weak and ambiguous boundaries.

  2. Vessel segmentation in screening mammograms

    Science.gov (United States)

    Mordang, J. J.; Karssemeijer, N.

    2015-03-01

    Blood vessels are a major cause of false positives in computer aided detection systems for the detection of breast cancer. Therefore, the purpose of this study is to construct a framework for the segmentation of blood vessels in screening mammograms. The proposed framework is based on supervised learning using a cascade classifier. This cascade classifier consists of several stages where in each stage a GentleBoost classifier is trained on Haar-like features. A total of 30 cases were included in this study. In each image, vessel pixels were annotated by selecting pixels on the centerline of the vessel, control samples were taken by annotating a region without any visible vascular structures. This resulted in a total of 31,000 pixels marked as vascular and over 4 million control pixels. After training, the classifier assigns a vesselness likelihood to the pixels. The proposed framework was compared to three other vessel enhancing methods, i) a vesselness filter, ii) a gaussian derivative filter, and iii) a tubeness filter. The methods were compared in terms of area under the receiver operating characteristics curves, the Az values. The Az value of the cascade approach is 0:85. This is superior to the vesselness, Gaussian, and tubeness methods, with Az values of 0:77, 0:81, and 0:78, respectively. From these results, it can be concluded that our proposed framework is a promising method for the detection of vessels in screening mammograms.

  3. Segmentation of vessels: the corkscrew algorithm

    Science.gov (United States)

    Wesarg, Stefan; Firle, Evelyn A.

    2004-05-01

    Medical imaging is nowadays much more than only providing data for diagnosis. It also links 'classical' diagnosis to modern forms of treatment such as image guided surgery. Those systems require the identification of organs, anatomical regions of the human body etc., i. e. the segmentation of structures from medical data sets. The algorithms used for these segmentation tasks strongly depend on the object to be segmented. One structure which plays an important role in surgery planning are vessels that are found everywhere in the human body. Several approaches for their extraction already exist. However, there is no general one which is suitable for all types of data or all sorts of vascular structures. This work presents a new algorithm for the segmentation of vessels. It can be classified as a skeleton-based approach working on 3D data sets, and has been designed for a reliable segmentation of coronary arteries. The algorithm is a semi-automatic extraction technique requiring the definition of the start and end the point of the (centerline) path to be found. A first estimation of the vessel's centerline is calculated and then corrected iteratively by detecting the vessel's border perpendicular to the centerline. We used contrast enhanced CT data sets of the thorax for testing our approach. Coronary arteries have been extracted from the data sets using the 'corkscrew algorithm' presented in this work. The segmentation turned out to be robust even if moderate breathing artifacts were present in the data sets.

  4. Vessel-guided airway tree segmentation

    DEFF Research Database (Denmark)

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

    2010-01-01

    method is evaluated on 250 low dose computed tomography images from a lung cancer screening trial. Our experiments showed that applying the region growing algorithm on the airway appearance model produces more complete airway segmentations, leading to on average 20% longer trees, and 50% less leakage......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 differentiate between airway and non-airway voxels. This is in contrast to previous works that use either intensity alone or hand crafted models of airway appearance. We show that the appearance model can be trained with a set of easily acquired, incomplete, airway tree segmentations. A vessel orientation...

  5. An automated method for accurate vessel segmentation

    Science.gov (United States)

    Yang, Xin; Liu, Chaoyue; Le Minh, Hung; Wang, Zhiwei; Chien, Aichi; (Tim Cheng, Kwang-Ting

    2017-05-01

    Vessel segmentation is a critical task for various medical applications, such as diagnosis assistance of diabetic retinopathy, quantification of cerebral aneurysm’s growth, and guiding surgery in neurosurgical procedures. Despite technology advances in image segmentation, existing methods still suffer from low accuracy for vessel segmentation in the two challenging while common scenarios in clinical usage: (1) regions with a low signal-to-noise-ratio (SNR), and (2) at vessel boundaries disturbed by adjacent non-vessel pixels. In this paper, we present an automated system which can achieve highly accurate vessel segmentation for both 2D and 3D images even under these challenging scenarios. Three key contributions achieved by our system are: (1) a progressive contrast enhancement method to adaptively enhance contrast of challenging pixels that were otherwise indistinguishable, (2) a boundary refinement method to effectively improve segmentation accuracy at vessel borders based on Canny edge detection, and (3) a content-aware region-of-interests (ROI) adjustment method to automatically determine the locations and sizes of ROIs which contain ambiguous pixels and demand further verification. Extensive evaluation of our method is conducted on both 2D and 3D datasets. On a public 2D retinal dataset (named DRIVE (Staal 2004 IEEE Trans. Med. Imaging 23 501-9)) and our 2D clinical cerebral dataset, our approach achieves superior performance to the state-of-the-art methods including a vesselness based method (Frangi 1998 Int. Conf. on Medical Image Computing and Computer-Assisted Intervention) and an optimally oriented flux (OOF) based method (Law and Chung 2008 European Conf. on Computer Vision). An evaluation on 11 clinical 3D CTA cerebral datasets shows that our method can achieve 94% average accuracy with respect to the manual segmentation reference, which is 23% to 33% better than the five baseline methods (Yushkevich 2006 Neuroimage 31 1116-28; Law and Chung 2008

  6. Recent Advancements in Retinal Vessel Segmentation.

    Science.gov (United States)

    L Srinidhi, Chetan; Aparna, P; Rajan, Jeny

    2017-04-01

    Retinal vessel segmentation is a key step towards the accurate visualization, diagnosis, early treatment and surgery planning of ocular diseases. For the last two decades, a tremendous amount of research has been dedicated in developing automated methods for segmentation of blood vessels from retinal fundus images. Despite the fact, segmentation of retinal vessels still remains a challenging task due to the presence of abnormalities, varying size and shape of the vessels, non-uniform illumination and anatomical variability between subjects. In this paper, we carry out a systematic review of the most recent advancements in retinal vessel segmentation methods published in last five years. The objectives of this study are as follows: first, we discuss the most crucial preprocessing steps that are involved in accurate segmentation of vessels. Second, we review most recent state-of-the-art retinal vessel segmentation techniques which are classified into different categories based on their main principle. Third, we quantitatively analyse these methods in terms of its sensitivity, specificity, accuracy, area under the curve and discuss newly introduced performance metrics in current literature. Fourth, we discuss the advantages and limitations of the existing segmentation techniques. Finally, we provide an insight into active problems and possible future directions towards building successful computer-aided diagnostic system.

  7. Blood vessel segmentation in magnetic resonance angiography imagery

    Science.gov (United States)

    Kozaitis, S. P.; Chandramohan, R.

    2011-06-01

    Small blood vessels may be difficult to detect in magnetic resonance angiography due to the lack of blood flow caused by disease or injury. Our method, which uses a block-matching denoising approach to segment blood vessels, works well in the presence of noise. We examined extended regions of an image to determine whether they contained blood vessels by fitting a Gaussian mixture model to a region's histogram. Then, dissimilar regions were denoised separately. This approach was beneficial in low-contrast settings. It can be used to detect higher-order blood vessels that may be difficult to detect under normal conditions.

  8. 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...... is evaluated within EXACT’09 on a diverse set of CT scans. Results show a favorable combination of a relatively large portion of the tree detected correctly with very few false positives....

  9. Multi-level deep supervised networks for retinal vessel segmentation.

    Science.gov (United States)

    Mo, Juan; Zhang, Lei

    2017-12-01

    Changes in the appearance of retinal blood vessels are an important indicator for various ophthalmologic and cardiovascular diseases, including diabetes, hypertension, arteriosclerosis, and choroidal neovascularization. Vessel segmentation from retinal images is very challenging because of low blood vessel contrast, intricate vessel topology, and the presence of pathologies such as microaneurysms and hemorrhages. To overcome these challenges, we propose a neural network-based method for vessel segmentation. A deep supervised fully convolutional network is developed by leveraging multi-level hierarchical features of the deep networks. To improve the discriminative capability of features in lower layers of the deep network and guide the gradient back propagation to overcome gradient vanishing, deep supervision with auxiliary classifiers is incorporated in some intermediate layers of the network. Moreover, the transferred knowledge learned from other domains is used to alleviate the issue of insufficient medical training data. The proposed approach does not rely on hand-crafted features and needs no problem-specific preprocessing or postprocessing, which reduces the impact of subjective factors. We evaluate the proposed method on three publicly available databases, the DRIVE, STARE, and CHASE_DB1 databases. Extensive experiments demonstrate that our approach achieves better or comparable performance to state-of-the-art methods with a much faster processing speed, making it suitable for real-world clinical applications. The results of cross-training experiments demonstrate its robustness with respect to the training set. The proposed approach segments retinal vessels accurately with a much faster processing speed and can be easily applied to other biomedical segmentation tasks.

  10. Liver vessel segmentation based on extreme learning machine.

    Science.gov (United States)

    Zeng, Ye Zhan; Zhao, Yu Qian; Liao, Miao; Zou, Bei Ji; Wang, Xiao Fang; Wang, Wei

    2016-05-01

    Liver-vessel segmentation plays an important role in vessel structure analysis for liver surgical planning. This paper presents a liver-vessel segmentation method based on extreme learning machine (ELM). Firstly, an anisotropic filter is used to remove noise while preserving vessel boundaries from the original computer tomography (CT) images. Then, based on the knowledge of prior shapes and geometrical structures, three classical vessel filters including Sato, Frangi and offset medialness filters together with the strain energy filter are used to extract vessel structure features. Finally, the ELM is applied to segment liver vessels from background voxels. Experimental results show that the proposed method can effectively segment liver vessels from abdominal CT images, and achieves good accuracy, sensitivity and specificity. Copyright © 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  11. Cerebral vessels segmentation for light-sheet microscopy image using convolutional neural networks

    Science.gov (United States)

    Hu, Chaoen; Hui, Hui; Wang, Shuo; Dong, Di; Liu, Xia; Yang, Xin; Tian, Jie

    2017-03-01

    Cerebral vessel segmentation is an important step in image analysis for brain function and brain disease studies. To extract all the cerebrovascular patterns, including arteries and capillaries, some filter-based methods are used to segment vessels. However, the design of accurate and robust vessel segmentation algorithms is still challenging, due to the variety and complexity of images, especially in cerebral blood vessel segmentation. In this work, we addressed a problem of automatic and robust segmentation of cerebral micro-vessels structures in cerebrovascular images acquired by light-sheet microscope for mouse. To segment micro-vessels in large-scale image data, we proposed a convolutional neural networks (CNNs) architecture trained by 1.58 million pixels with manual label. Three convolutional layers and one fully connected layer were used in the CNNs model. We extracted a patch of size 32x32 pixels in each acquired brain vessel image as training data set to feed into CNNs for classification. This network was trained to output the probability that the center pixel of input patch belongs to vessel structures. To build the CNNs architecture, a series of mouse brain vascular images acquired from a commercial light sheet fluorescence microscopy (LSFM) system were used for training the model. The experimental results demonstrated that our approach is a promising method for effectively segmenting micro-vessels structures in cerebrovascular images with vessel-dense, nonuniform gray-level and long-scale contrast regions.

  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...... with multivariate linear regression using image intensities sampled in a region of interest around an initialization curve. Subsequently, the position of the vessel boundary is refined with a robust nonlinear regression technique using intensity profiles sampled across the boundary of the rough segmentation...... and using information about plausible cross-sectional vessel shapes. The method was evaluated by quantitatively comparing segmentation results to manual annotations of 229 coronary arteries. On average the difference between the automatically obtained segmentations and manual contours was smaller than...

  13. Automatic segmentation of abdominal vessels for improved pancreas localization

    Science.gov (United States)

    Farag, Amal; Liu, Jiamin; Summers, Ronald M.

    2014-03-01

    Accurate automatic detection and segmentation of abdominal organs from CT images is important for quantitative and qualitative organ tissue analysis as well as computer-aided diagnosis. The large variability of organ locations, the spatial interaction between organs that appear similar in medical scans and orientation and size variations are among the major challenges making the task very difficult. The pancreas poses these challenges in addition to its flexibility which allows for the shape of the tissue to vastly change. Due to the close proximity of the pancreas to numerous surrounding organs within the abdominal cavity the organ shifts according to the conditions of the organs within the abdomen, as such the pancreas is constantly changing. Combining these challenges with typically found patient-to-patient variations and scanning conditions the pancreas becomes harder to localize. In this paper we focus on three abdominal vessels that almost always abut the pancreas tissue and as such useful landmarks to identify the relative location of the pancreas. The splenic and portal veins extend from the hila of the spleen and liver, respectively, travel through the abdominal cavity and join at a position close to the head of the pancreas known as the portal confluence. A third vein, the superior mesenteric vein, anastomoses with the other two veins at the portal confluence. An automatic segmentation framework for obtaining the splenic vein, portal confluence and superior mesenteric vein is proposed using 17 contrast enhanced computed-tomography datasets. The proposed method uses outputs from the multi-organ multi-atlas label fusion and Frangi vesselness filter to obtain automatic seed points for vessel tracking and generation of statistical models of the desired vessels. The approach shows ability to identify the vessels and improve localization of the pancreas within the abdomen.

  14. Lung vessel segmentation in CT images using graph-cuts

    Science.gov (United States)

    Zhai, Zhiwei; Staring, Marius; Stoel, Berend C.

    2016-03-01

    Accurate lung vessel segmentation is an important operation for lung CT analysis. Filters that are based on analyzing the eigenvalues of the Hessian matrix are popular for pulmonary vessel enhancement. However, due to their low response at vessel bifurcations and vessel boundaries, extracting lung vessels by thresholding the vesselness is not sufficiently accurate. Some methods turn to graph-cuts for more accurate segmentation, as it incorporates neighbourhood information. In this work, we propose a new graph-cuts cost function combining appearance and shape, where CT intensity represents appearance and vesselness from a Hessian-based filter represents shape. Due to the amount of voxels in high resolution CT scans, the memory requirement and time consumption for building a graph structure is very high. In order to make the graph representation computationally tractable, those voxels that are considered clearly background are removed from the graph nodes, using a threshold on the vesselness map. The graph structure is then established based on the remaining voxel nodes, source/sink nodes and the neighbourhood relationship of the remaining voxels. Vessels are segmented by minimizing the energy cost function with the graph-cuts optimization framework. We optimized the parameters used in the graph-cuts cost function and evaluated the proposed method with two manually labeled sub-volumes. For independent evaluation, we used 20 CT scans of the VESSEL12 challenge. The evaluation results of the sub-volume data show that the proposed method produced a more accurate vessel segmentation compared to the previous methods, with F1 score 0.76 and 0.69. In the VESSEL12 data-set, our method obtained a competitive performance with an area under the ROC curve of 0.975, especially among the binary submissions.

  15. Brain blood vessel segmentation using line-shaped profiles

    Science.gov (United States)

    Babin, Danilo; Pižurica, Aleksandra; De Vylder, Jonas; Vansteenkiste, Ewout; Philips, Wilfried

    2013-11-01

    Segmentation of cerebral blood vessels is of great importance in diagnostic and clinical applications, especially for embolization of cerebral aneurysms and arteriovenous malformations (AVMs). In order to perform embolization of the AVM, the structural and geometric information of blood vessels from 3D images is of utmost importance. For this reason, the in-depth segmentation of cerebral blood vessels is usually done as a fusion of different segmentation techniques, often requiring extensive user interaction. In this paper we introduce the idea of line-shaped profiling with an application to brain blood vessel and AVM segmentation, efficient both in terms of resolving details and in terms of computation time. Our method takes into account both local proximate and wider neighbourhood of the processed pixel, which makes it efficient for segmenting large blood vessel tree structures, as well as fine structures of the AVMs. Another advantage of our method is that it requires selection of only one parameter to perform segmentation, yielding very little user interaction.

  16. Automatic Segmentation of Vessels in In-Vivo Ultrasound Scans

    DEFF Research Database (Denmark)

    Tamimi-Sarnikowski, Philip; Brink-Kjær, Andreas; Moshavegh, Ramin

    2017-01-01

    presents a fully automatic segmentation algorithm, for robustly segmenting the vessel lumen in longitudinal B-mode ultrasound images. The automatic segmentation is performed using a combination of B-mode and power Doppler images. The proposed algorithm includes a series of preprocessing steps, and performs...... a vessel segmentation by use of the marker-controlled watershed transform. The ultrasound images used in the study were acquired using the bk3000 ultrasound scanner (BK Ultrasound, Herlev, Denmark) with two transducers ”8L2 Linear” and ”10L2w Wide Linear” (BK Ultrasound, Herlev, Denmark). The algorithm...... was evaluated empirically and applied to a dataset of in-vivo 1770 images recorded from 8 healthy subjects. The segmentation results were compared to manual delineation performed by two experienced users. The results showed a sensitivity and specificity of 90.41 ± 11.2 % and 97.93 ± 5.7 % (mean ± standard...

  17. Robust hepatic vessel segmentation using multi deep convolution network

    Science.gov (United States)

    Kitrungrotsakul, Titinunt; Han, Xian-Hua; Iwamoto, Yutaro; Foruzan, Amir Hossein; Lin, Lanfen; Chen, Yen-Wei

    2017-03-01

    Extraction of blood vessels of the organ is a challenging task in the area of medical image processing. It is really difficult to get accurate vessel segmentation results even with manually labeling by human being. The difficulty of vessels segmentation is the complicated structure of blood vessels and its large variations that make them hard to recognize. In this paper, we present deep artificial neural network architecture to automatically segment the hepatic vessels from computed tomography (CT) image. We proposed novel deep neural network (DNN) architecture for vessel segmentation from a medical CT volume, which consists of three deep convolution neural networks to extract features from difference planes of CT data. The three networks have share features at the first convolution layer but will separately learn their own features in the second layer. All three networks will join again at the top layer. To validate effectiveness and efficiency of our proposed method, we conduct experiments on 12 CT volumes which training data are randomly generate from 5 CT volumes and 7 using for test. Our network can yield an average dice coefficient 0.830, while 3D deep convolution neural network can yield around 0.7 and multi-scale can yield only 0.6.

  18. Learning-based automated segmentation of the carotid artery vessel wall in dual-sequence MRI using subdivision surface fitting

    NARCIS (Netherlands)

    Gao, Shan; van't Klooster, Ronald; Kitslaar, Pieter H.; Coolen, Bram F.; van den Berg, Alexandra M.; Smits, Loek P.; Shahzad, Rahil; Shamonin, Denis P.; de Koning, Patrick J. H.; Nederveen, Aart J.; van der Geest, Rob J.

    2017-01-01

    Purpose: The quantification of vessel wall morphology and plaque burden requires vessel segmentation, which is generally performed by manual delineations. The purpose of our work is to develop and evaluate a new 3D model-based approach for carotid artery wall segmentation from dual-sequence MRI.

  19. 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...... 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...

  20. Vessel segmentation and microaneurysm detection using discriminative dictionary learning and sparse representation.

    Science.gov (United States)

    Javidi, Malihe; Pourreza, Hamid-Reza; Harati, Ahad

    2017-02-01

    Diabetic retinopathy (DR) is a major cause of visual impairment, and the analysis of retinal image can assist patients to take action earlier when it is more likely to be effective. The accurate segmentation of blood vessels in the retinal image can diagnose DR directly. In this paper, a novel scheme for blood vessel segmentation based on discriminative dictionary learning (DDL) and sparse representation has been proposed. The proposed system yields a strong representation which contains the semantic concept of the image. To extract blood vessel, two separate dictionaries, for vessel and non-vessel, capable of providing reconstructive and discriminative information of the retinal image are learned. In the test step, an unseen retinal image is divided into overlapping patches and classified to vessel and non-vessel patches. Then, a voting scheme is applied to generate the binary vessel map. The proposed vessel segmentation method can achieve the accuracy of 95% and a sensitivity of 75% in the same range of specificity 97% on two public datasets. The results show that the proposed method can achieve comparable results to existing methods and decrease false positive vessels in abnormal retinal images with pathological regions. Microaneurysm (MA) is the earliest sign of DR that appears as a small red dot on the surface of the retina. Despite several attempts to develop automated MA detection systems, it is still a challenging problem. In this paper, a method for MA detection, which is similar to our vessel segmentation approach, is proposed. In our method, a candidate detection algorithm based on the Morlet wavelet is applied to identify all possible MA candidates. In the next step, two discriminative dictionaries with the ability to distinguish MA from non-MA object are learned. These dictionaries are then used to classify the detected candidate objects. The evaluations indicate that the proposed MA detection method achieves higher average sensitivity about 2

  1. Comparison of vessel enhancement algorithms applied to time-of-flight MRA images for cerebrovascular segmentation.

    Science.gov (United States)

    Phellan, Renzo; Forkert, Nils D

    2017-11-01

    Vessel enhancement algorithms are often used as a preprocessing step for vessel segmentation in medical images to improve the overall segmentation accuracy. Each algorithm uses different characteristics to enhance vessels, such that the most suitable algorithm may vary for different applications. This paper presents a comparative analysis of the accuracy gains in vessel segmentation generated by the use of nine vessel enhancement algorithms: Multiscale vesselness using the formulas described by Erdt (MSE), Frangi (MSF), and Sato (MSS), optimally oriented flux (OOF), ranking orientations responses path operator (RORPO), the regularized Perona-Malik approach (RPM), vessel enhanced diffusion (VED), hybrid diffusion with continuous switch (HDCS), and the white top hat algorithm (WTH). The filters were evaluated and compared based on time-of-flight MRA datasets and corresponding manual segmentations from 5 healthy subjects and 10 patients with an arteriovenous malformation. Additionally, five synthetic angiographic datasets with corresponding ground truth segmentation were generated with three different noise levels (low, medium, and high) and also used for comparison. The parameters for each algorithm and subsequent segmentation were optimized using leave-one-out cross evaluation. The Dice coefficient, Matthews correlation coefficient, area under the ROC curve, number of connected components, and true positives were used for comparison. The results of this study suggest that vessel enhancement algorithms do not always lead to more accurate segmentation results compared to segmenting nonenhanced images directly. Multiscale vesselness algorithms, such as MSE, MSF, and MSS proved to be robust to noise, while diffusion-based filters, such as RPM, VED, and HDCS ranked in the top of the list in scenarios with medium or no noise. Filters that assume tubular-shapes, such as MSE, MSF, MSS, OOF, RORPO, and VED show a decrease in accuracy when considering patients with an AVM

  2. Multi-atlas pancreas segmentation: Atlas selection based on vessel structure.

    Science.gov (United States)

    Karasawa, Ken'ichi; Oda, Masahiro; Kitasaka, Takayuki; Misawa, Kazunari; Fujiwara, Michitaka; Chu, Chengwen; Zheng, Guoyan; Rueckert, Daniel; Mori, Kensaku

    2017-07-01

    Automated organ segmentation from medical images is an indispensable component for clinical applications such as computer-aided diagnosis (CAD) and computer-assisted surgery (CAS). We utilize a multi-atlas segmentation scheme, which has recently been used in different approaches in the literature to achieve more accurate and robust segmentation of anatomical structures in computed tomography (CT) volume data. Among abdominal organs, the pancreas has large inter-patient variability in its position, size and shape. Moreover, the CT intensity of the pancreas closely resembles adjacent tissues, rendering its segmentation a challenging task. Due to this, conventional intensity-based atlas selection for pancreas segmentation often fails to select atlases that are similar in pancreas position and shape to those of the unlabeled target volume. In this paper, we propose a new atlas selection strategy based on vessel structure around the pancreatic tissue and demonstrate its application to a multi-atlas pancreas segmentation. Our method utilizes vessel structure around the pancreas to select atlases with high pancreatic resemblance to the unlabeled volume. Also, we investigate two types of applications of the vessel structure information to the atlas selection. Our segmentations were evaluated on 150 abdominal contrast-enhanced CT volumes. The experimental results showed that our approach can segment the pancreas with an average Jaccard index of 66.3% and an average Dice overlap coefficient of 78.5%. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Leveraging Multiscale Hessian-Based Enhancement With a Novel Exudate Inpainting Technique for Retinal Vessel Segmentation.

    Science.gov (United States)

    Annunziata, Roberto; Garzelli, Andrea; Ballerini, Lucia; Mecocci, Alessandro; Trucco, Emanuele

    2016-07-01

    Accurate vessel detection in retinal images is an important and difficult task. Detection is made more challenging in pathological images with the presence of exudates and other abnormalities. In this paper, we present a new unsupervised vessel segmentation approach to address this problem. A novel inpainting filter, called neighborhood estimator before filling, is proposed to inpaint exudates in a way that nearby false positives are significantly reduced during vessel enhancement. Retinal vascular enhancement is achieved with a multiple-scale Hessian approach. Experimental results show that the proposed vessel segmentation method outperforms state-of-the-art algorithms reported in the recent literature, both visually and in terms of quantitative measurements, with overall mean accuracy of 95.62% on the STARE dataset and 95.81% on the HRF dataset.

  4. Automatic blood vessels segmentation based on different retinal maps from OCTA scans.

    Science.gov (United States)

    Eladawi, Nabila; Elmogy, Mohammed; Helmy, Omar; Aboelfetouh, Ahmed; Riad, Alaa; Sandhu, Harpal; Schaal, Shlomit; El-Baz, Ayman

    2017-10-01

    The retinal vascular network reflects the health of the retina, which is a useful diagnostic indicator of systemic vascular. Therefore, the segmentation of retinal blood vessels is a powerful method for diagnosing vascular diseases. This paper presents an automatic segmentation system for retinal blood vessels from Optical Coherence Tomography Angiography (OCTA) images. The system segments blood vessels from the superficial and deep retinal maps for normal and diabetic cases. Initially, we reduced the noise and improved the contrast of the OCTA images by using the Generalized Gauss-Markov random field (GGMRF) model. Secondly, we proposed a joint Markov-Gibbs random field (MGRF) model to segment the retinal blood vessels from other background tissues. It integrates both appearance and spatial models in addition to the prior probability model of OCTA images. The higher order MGRF (HO-MGRF) model in addition to the 1 st -order intensity model are used to consider the spatial information in order to overcome the low contrast between vessels and other tissues. Finally, we refined the segmentation by extracting connected regions using a 2D connectivity filter. The proposed segmentation system was trained and tested on 47 data sets, which are 23 normal data sets and 24 data sets for diabetic patients. To evaluate the accuracy and robustness of the proposed segmentation framework, we used three different metrics, which are Dice similarity coefficient (DSC), absolute vessels volume difference (VVD), and area under the curve (AUC). The results on OCTA data sets (DSC=95.04±3.75%, VVD=8.51±1.49%, and AUC=95.20±1.52%) show the promise of the proposed segmentation approach. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Optimization of reactor pressure vessel internals segmentation in Korea

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Byung-Sik [Dankook Univ., Chungnam (Korea, Republic of). Dept. of Nuclear Engineering

    2017-11-15

    One of the most challenging tasks during plant decommissioning is the removal of highly radioactive internal components from the reactor pressure vessel (RPV). For RPV internals dismantling, it is essential that all activities are thoroughly planned and discussed in the early stage of the decommissioning project. One of the key activities in the detailed planning is to prepare the segmentation and packaging plan that describes the sequential steps required to segment, separate, and package each individual component of RPV, based on an activation analysis and component characterization study.

  6. A hybrid lung and vessel segmentation algorithm for computer aided detection of pulmonary embolism

    Science.gov (United States)

    Raghupathi, Laks; Lakare, Sarang

    2009-02-01

    Advances in multi-detector technology have made CT pulmonary angiography (CTPA) a popular radiological tool for pulmonary emboli (PE) detection. CTPA provide rich detail of lung anatomy and is a useful diagnostic aid in highlighting even very small PE. However analyzing hundreds of slices is laborious and time-consuming for the practicing radiologist which may also cause misdiagnosis due to the presence of various PE look-alike. Computer-aided diagnosis (CAD) can be a potential second reader in providing key diagnostic information. Since PE occurs only in vessel arteries, it is important to mark this region of interest (ROI) during CAD preprocessing. In this paper, we present a new lung and vessel segmentation algorithm for extracting contrast-enhanced vessel ROI in CTPA. Existing approaches to segmentation either provide only the larger lung area without highlighting the vessels or is computationally prohibitive. In this paper, we propose a hybrid lung and vessel segmentation which uses an initial lung ROI and determines the vessels through a series of refinement steps. We first identify a coarse vessel ROI by finding the "holes" from the lung ROI. We then use the initial ROI as seed-points for a region-growing process while carefully excluding regions which are not relevant. The vessel segmentation mask covers 99% of the 259 PE from a real-world set of 107 CTPA. Further, our algorithm increases the net sensitivity of a prototype CAD system by 5-9% across all PE categories in the training and validation data sets. The average run-time of algorithm was only 100 seconds on a standard workstation.

  7. Joint 3-D vessel segmentation and centerline extraction using oblique Hough forests with steerable filters.

    Science.gov (United States)

    Schneider, Matthias; Hirsch, Sven; Weber, Bruno; Székely, Gábor; Menze, Bjoern H

    2015-01-01

    We propose a novel framework for joint 3-D vessel segmentation and centerline extraction. The approach is based on multivariate Hough voting and oblique random forests (RFs) that we learn from noisy annotations. It relies on steerable filters for the efficient computation of local image features at different scales and orientations. We validate both the segmentation performance and the centerline accuracy of our approach both on synthetic vascular data and four 3-D imaging datasets of the rat visual cortex at 700 nm resolution. First, we evaluate the most important structural components of our approach: (1) Orthogonal subspace filtering in comparison to steerable filters that show, qualitatively, similarities to the eigenspace filters learned from local image patches. (2) Standard RF against oblique RF. Second, we compare the overall approach to different state-of-the-art methods for (1) vessel segmentation based on optimally oriented flux (OOF) and the eigenstructure of the Hessian, and (2) centerline extraction based on homotopic skeletonization and geodesic path tracing. Our experiments reveal the benefit of steerable over eigenspace filters as well as the advantage of oblique split directions over univariate orthogonal splits. We further show that the learning-based approach outperforms different state-of-the-art methods and proves highly accurate and robust with regard to both vessel segmentation and centerline extraction in spite of the high level of label noise in the training data. Copyright © 2014 Elsevier B.V. All rights reserved.

  8. Segmenting Retinal Blood Vessels With Deep Neural Networks.

    Science.gov (United States)

    Liskowski, Pawel; Krawiec, Krzysztof

    2016-11-01

    The condition of the vascular network of human eye is an important diagnostic factor in ophthalmology. Its segmentation in fundus imaging is a nontrivial task due to variable size of vessels, relatively low contrast, and potential presence of pathologies like microaneurysms and hemorrhages. Many algorithms, both unsupervised and supervised, have been proposed for this purpose in the past. We propose a supervised segmentation technique that uses a deep neural network trained on a large (up to 400[Formula: see text]000) sample of examples preprocessed with global contrast normalization, zero-phase whitening, and augmented using geometric transformations and gamma corrections. Several variants of the method are considered, including structured prediction, where a network classifies multiple pixels simultaneously. When applied to standard benchmarks of fundus imaging, the DRIVE, STARE, and CHASE databases, the networks significantly outperform the previous algorithms on the area under ROC curve measure (up to > 0.99) and accuracy of classification (up to > 0.97 ). The method is also resistant to the phenomenon of central vessel reflex, sensitive in detection of fine vessels ( sensitivity > 0.87 ), and fares well on pathological cases.

  9. Multimodal MEMPRAGE, FLAIR, and R2* Segmentation to Resolve Dura and Vessels from Cortical Gray Matter

    Directory of Open Access Journals (Sweden)

    Roberto Viviani

    2017-05-01

    Full Text Available While widely in use in automated segmentation approaches for the detection of group differences or of changes associated with continuous predictors in gray matter volume, T1-weighted images are known to represent dura and cortical vessels with signal intensities similar to those of gray matter. By considering multiple signal sources at once, multimodal segmentation approaches may be able to resolve these different tissue classes and address this potential confound. We explored here the simultaneous use of FLAIR and apparent transverse relaxation rates (a signal related to T2* relaxation maps and having similar contrast with T1-weighted images. Relative to T1-weighted images alone, multimodal segmentation had marked positive effects on 1. the separation of gray matter from dura, 2. the exclusion of vessels from the gray matter compartment, and 3. the contrast with extracerebral connective tissue. While obtainable together with the T1-weighted images without increasing scanning times, apparent transverse relaxation rates were less effective than added FLAIR images in providing the above mentioned advantages. FLAIR images also improved the detection of cortical matter in areas prone to susceptibility artifacts in standard MPRAGE T1-weighted images, while the addition of transverse relaxation maps exacerbated the effect of these artifacts on segmentation. Our results confirm that standard MPRAGE segmentation may overestimate gray matter volume by wrongly assigning vessels and dura to this compartment and show that multimodal approaches may greatly improve the specificity of cortical segmentation. Since multimodal segmentation is easily implemented, these benefits are immediately available to studies focusing on translational applications of structural imaging.

  10. Segmentation of retinal blood vessels using normalized Gabor filters and automatic thresholding

    Directory of Open Access Journals (Sweden)

    Mandlenkosi Victor Gwetu

    2014-12-01

    Full Text Available Although computerized retinal image blood vessel segmentation has been extensively researched, there is still room for improvement in the quality of the segmented images. Since retinal image analysis is still widely used in the diagnosis of diabetic retinopathy, efficient and accurate image characterization techniques are required. Previous work has mainly focused on improving segmentation accuracy rates with little regard to the false positives that are produced by illumination variation. This research work presents a hybrid approach towards the segmentation of retinal blood vessels. New approaches towards the reduction of background illumination variation are proposed using normalized Gabor filtering. These are the base-offset encoding and a modified version of an existing zero-integral kernel technique. The valley emphasis automatic thresholding scheme is used to segment the Gabor response images. Experiments are conducted on the DRIVE and STARE retinal image data sets. Accuracy rates of up to 94% are achieved through the zero-integral and base offset methods. This is comparable with results from literature, where the same data sets are segmented using other classification techniques. The median-offset method is found to most effectively reduce background illumination variation.

  11. Optic disc segmentation: level set methods and blood vessels inpainting

    Science.gov (United States)

    Almazroa, A.; Sun, Weiwei; Alodhayb, Sami; Raahemifar, Kaamran; Lakshminarayanan, Vasudevan

    2017-03-01

    Segmenting the optic disc (OD) is an important and essential step in creating a frame of reference for diagnosing optic nerve head (ONH) pathology such as glaucoma. Therefore, a reliable OD segmentation technique is necessary for automatic screening of ONH abnormalities. The main contribution of this paper is in presenting a novel OD segmentation algorithm based on applying a level set method on a localized OD image. To prevent the blood vessels from interfering with the level set process, an inpainting technique is applied. The algorithm is evaluated using a new retinal fundus image dataset called RIGA (Retinal Images for Glaucoma Analysis). In the case of low quality images, a double level set is applied in which the first level set is considered to be a localization for the OD. Five hundred and fifty images are used to test the algorithm accuracy as well as its agreement with manual markings by six ophthalmologists. The accuracy of the algorithm in marking the optic disc area and centroid is 83.9%, and the best agreement is observed between the results of the algorithm and manual markings in 379 images.

  12. Liver vessel segmentation and identification based on oriented flux symmetry and graph cuts.

    Science.gov (United States)

    Zeng, Ye-Zhan; Zhao, Yu-Qian; Tang, Ping; Liao, Miao; Liang, Yi-Xiong; Liao, Sheng-Hui; Zou, Bei-Ji

    2017-10-01

    Accurate segmentation of liver vessels from abdominal computer tomography angiography (CTA) volume is very important for liver-vessel analysis and living-related liver transplants. This paper presents a novel liver-vessel segmentation and identification method. Firstly, an anisotropic diffusion filter is used to smooth noise while preserving vessel boundaries. Then, based on the gradient symmetry and antisymmetry pattern of vessel structures, optimal oriented flux (OOF) and oriented flux antisymmetry (OFA) measures are respectively applied to detect liver vessels and their boundaries, and further to slenderize vessels. Next, according to vessel geometrical structure, a centerline extraction measure based on height ridge traversal and leaf node line-growing (LNLG) is proposed for the extraction of liver-vessel centerlines, and an intensity model based on fast marching is integrated into graph cuts (GCs) for effective segmentation of liver vessels. Finally, a distance voting mechanism is applied to separate the hepatic vein and portal vein. The experiment results on abdominal CTA images show that the proposed method can effectively segment liver vessels, achieving an average accuracy, sensitivity, and specificity of 97.7%, 79.8%, and 98.6%, respectively, and has a good performance on thin-vessel extraction. The proposed method does not require manual selection of the centerlines and vessel seeds, and can effectively segment liver vessels and identify hepatic vein and portal vein. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. VESSEL CENTERLINE TRACKING AND BOUNDARY SEGMENTATION IN CORONARY MRA WITH MINIMAL MANUAL INTERACTION.

    Science.gov (United States)

    Soleimanifard, Sahar; Schär, Michael; Hays, Allison G; Weiss, Robert G; Stuber, Matthias; Prince, Jerry L

    2012-01-01

    Magnetic resonance angiography (MRA) provides a noninvasive means to detect the presence, location and severity of atherosclerosis throughout the vascular system. In such studies, and especially those in the coronary arteries, the vessel luminal area is typically measured at multiple cross-sectional locations along the course of the artery. The advent of fast volumetric imaging techniques covering proximal to mid segments of coronary arteries necessitates automatic analysis tools requiring minimal manual interactions to robustly measure cross-sectional area along the three-dimensional track of the arteries in under-sampled and non-isotropic datasets. In this work, we present a modular approach based on level set methods to track the vessel centerline, segment the vessel boundaries, and measure transversal area using two user-selected endpoints in each coronary of interest. Arterial area and vessel length are measured using our method and compared to the standard Soap-Bubble reformatting and analysis tool in in-vivo non-contrast enhanced coronary MRA images.

  14. Computerized detection of pulmonary embolism in computed tomographic pulmonary angiography (CTPA): improvement of vessel segmentation

    Science.gov (United States)

    Zhou, Chuan; Chan, Heang-Ping; Kuriakose, Jean W.; Chughtai, Aamer; Hadjiiski, Lubomir M.; Wei, Jun; Patel, Smita; Kazerooni, Ella A.

    2011-03-01

    Vessel segmentation is a fundamental step in an automated pulmonary embolism (PE) detection system. The purpose of this study is to improve the segmentation scheme for pulmonary vessels affected by PE and other lung diseases. We have developed a multiscale hierarchical vessel enhancement and segmentation (MHES) method for pulmonary vessel tree extraction based on the analysis of eigenvalues of Hessian matrices. However, it is difficult to segment the pulmonary vessels accurately when the vessel is occluded by PEs and/or surrounded by lymphoid tissues or lung diseases. In this study, we developed a method that combines MHES with level set refinement (MHES-LSR) to improve vessel segmentation accuracy. The level set was designed to propagate the initial object contours to the regions with relatively high gray-level, high gradient, and high compactness as measured by the smoothness of the curvature along vessel boundaries. Two and eight CTPA scans were randomly selected as training and test data sets, respectively. Forty volumes of interest (VOI) containing "representative" vessels were manually segmented by a radiologist experienced in CTPA interpretation and used as reference standard. The results show that, for the 32 test VOIs, the average percentage volume error relative to the reference standard was improved from 31.7+/-10.9% using the MHES method to 7.7+/-4.7% using the MHES-LSR method. The correlation between the computer-segmented vessel volume and the reference standard was improved from 0.954 to 0.986. The accuracy of vessel segmentation was improved significantly (p<0.05). The MHES-LSR method may have the potential to improve PE detection.

  15. Comparison of approaches for microscopic imaging of skin lymphatic vessels.

    Science.gov (United States)

    Wu, Xiufeng; Yu, Zheyuan; Liu, Ningfei

    2012-01-01

    Assessment of skin lymphatic vessels is of great significance in understanding their roles in many pathological conditions. Our aim was to identify the optimal approach for investigation of cutaneous lymphatic system. We performed comparative studies on skin lymphatic vessels using immunohistochemistry of tissue sections, computer graphic reconstruction method together with immunohistochemically stained serial sections and whole mount fluorescence in human lower limb. Lymphatic vessels were identified with podoplanin antibody. The relative merits and drawbacks of each method in evaluation of structure, spatial organization, and distribution of cutaneous lymphatic vessels were described. Immunohistology of tissue sections enabled the investigation of the structure and distribution of the whole cutaneous lymphatic system in two-dimensional slices, whereas three-dimensional morphology of only the most superficial lymph capillary network immediately under the epidermis could be evaluated with the whole mount technique. Meanwhile, only little segmentation of skin lymphatic vessel from five immunohistochemically stained serial sections was reconstructed and evaluated due to expense and special skills required using computer graphic three-dimensional reconstruction. Furthermore, a great number of artifacts and special skills required in its processes leaded to less accurate structure of skin lymphatic vessels. Our findings demonstrated that the use of either of the proposed techniques alone could not allow a comprehensive analysis of the skin lymphatic system due to their relative drawbacks. Combination of immunohistology of tissue sections and three-dimensional whole-mount preparations appears to be the best candidate for comprehensive evaluation of skin lymphatic system. © Wiley Periodicals, Inc.

  16. Retinal blood vessels segmentation by using Gumbel probability distribution function based matched filter.

    Science.gov (United States)

    Singh, Nagendra Pratap; Srivastava, Rajeev

    2016-06-01

    Retinal blood vessel segmentation is a prominent task for the diagnosis of various retinal pathology such as hypertension, diabetes, glaucoma, etc. In this paper, a novel matched filter approach with the Gumbel probability distribution function as its kernel is introduced to improve the performance of retinal blood vessel segmentation. Before applying the proposed matched filter, the input retinal images are pre-processed. During pre-processing stage principal component analysis (PCA) based gray scale conversion followed by contrast limited adaptive histogram equalization (CLAHE) are applied for better enhancement of retinal image. After that an exhaustive experiments have been conducted for selecting the appropriate value of parameters to design a new matched filter. The post-processing steps after applying the proposed matched filter include the entropy based optimal thresholding and length filtering to obtain the segmented image. For evaluating the performance of proposed approach, the quantitative performance measures, an average accuracy, average true positive rate (ATPR), and average false positive rate (AFPR) are calculated. The respective values of the quantitative performance measures are 0.9522, 0.7594, 0.0292 for DRIVE data set and 0.9270, 0.7939, 0.0624 for STARE data set. To justify the effectiveness of proposed approach, receiver operating characteristic (ROC) curve is plotted and the average area under the curve (AUC) is calculated. The average AUC for DRIVE and STARE data sets are 0.9287 and 0.9140 respectively. The obtained experimental results confirm that the proposed approach performance better with respect to other prominent Gaussian distribution function and Cauchy PDF based matched filter approaches. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  17. An Automatic Cognitive Graph-Based Segmentation for Detection of Blood Vessels in Retinal Images

    Directory of Open Access Journals (Sweden)

    Rasha Al Shehhi

    2016-01-01

    Full Text Available This paper presents a hierarchical graph-based segmentation for blood vessel detection in digital retinal images. This segmentation employs some of perceptual Gestalt principles: similarity, closure, continuity, and proximity to merge segments into coherent connected vessel-like patterns. The integration of Gestalt principles is based on object-based features (e.g., color and black top-hat (BTH morphology and context and graph-analysis algorithms (e.g., Dijkstra path. The segmentation framework consists of two main steps: preprocessing and multiscale graph-based segmentation. Preprocessing is to enhance lighting condition, due to low illumination contrast, and to construct necessary features to enhance vessel structure due to sensitivity of vessel patterns to multiscale/multiorientation structure. Graph-based segmentation is to decrease computational processing required for region of interest into most semantic objects. The segmentation was evaluated on three publicly available datasets. Experimental results show that preprocessing stage achieves better results compared to state-of-the-art enhancement methods. The performance of the proposed graph-based segmentation is found to be consistent and comparable to other existing methods, with improved capability of detecting small/thin vessels.

  18. Roi Detection and Vessel Segmentation in Retinal Image

    Science.gov (United States)

    Sabaz, F.; Atila, U.

    2017-11-01

    Diabetes disrupts work by affecting the structure of the eye and afterwards leads to loss of vision. Depending on the stage of disease that called diabetic retinopathy, there are sudden loss of vision and blurred vision problems. Automated detection of vessels in retinal images is a useful study to diagnose eye diseases, disease classification and other clinical trials. The shape and structure of the vessels give information about the severity of the disease and the stage of the disease. Automatic and fast detection of vessels allows for a quick diagnosis of the disease and the treatment process to start shortly. ROI detection and vessel extraction methods for retinal image are mentioned in this study. It is shown that the Frangi filter used in image processing can be successfully used in detection and extraction of vessels.

  19. Threshold segmentation algorithm for automatic extraction of cerebral vessels from brain magnetic resonance angiography images.

    Science.gov (United States)

    Wang, Rui; Li, Chao; Wang, Jie; Wei, Xiaoer; Li, Yuehua; Zhu, Yuemin; Zhang, Su

    2015-02-15

    Cerebrovascular segmentation plays an important role in medical diagnosis. This study was conducted to develop a threshold segmentation algorithm for automatic extraction and volumetric quantification of cerebral vessels on brain magnetic resonance angiography (MRA) images. The MRA images of 10 individuals were acquired using a 3 Tesla MR scanner (Intera-achieva SMI-2.1, Philips Medical Systems). Otsu's method was used to divide the brain MRA images into two parts, namely, foreground and background regions. To extract the cerebral vessels, we performed the threshold segmentation algorithm on the foreground region by comparing two different statistical distributions. Automatically segmented vessels were compared with manually segmented vessels. Different similarity metrics were used to assess the changes in segmentation performance as a function of a weighted parameter w used in segmentation algorithm. Varying w from 2 to 100 resulted in a false positive rate ranging from 117% to 3.21%, and a false negative rate ranging from 8.23% to 28.97%. The Dice similarity coefficient (DSC), which reflected the segmentation accuracy, initially increased and then decreased as w increased. The suggested range of values for w is [10, 20] given that the maximum DSC (e.g., DSC=0.84) was obtained within this range. The performance of our method was validated by comparing with manual segmentation. The proposed threshold segmentation method can be used to accurately and efficiently extract cerebral vessels from brain MRA images. Threshold segmentation may be used for studies focusing on three-dimensional visualization and volumetric quantification of cerebral vessels. Copyright © 2014 Elsevier B.V. All rights reserved.

  20. A Vessel Active Contour Model for Vascular Segmentation

    Directory of Open Access Journals (Sweden)

    Yun Tian

    2014-01-01

    Full Text Available This paper proposes a vessel active contour model based on local intensity weighting and a vessel vector field. Firstly, the energy function we define is evaluated along the evolving curve instead of all image points, and the function value at each point on the curve is based on the interior and exterior weighted means in a local neighborhood of the point, which is good for dealing with the intensity inhomogeneity. Secondly, a vascular vector field derived from a vesselness measure is employed to guide the contour to evolve along the vessel central skeleton into thin and weak vessels. Thirdly, an automatic initialization method that makes the model converge rapidly is developed, and it avoids repeated trails in conventional local region active contour models. Finally, a speed-up strategy is implemented by labeling the steadily evolved points, and it avoids the repeated computation of these points in the subsequent iterations. Experiments using synthetic and real vessel images validate the proposed model. Comparisons with the localized active contour model, local binary fitting model, and vascular active contour model show that the proposed model is more accurate, efficient, and suitable for extraction of the vessel tree from different medical images.

  1. Magnetic resonance imaging of water ascent in embolized xylem vessels of grapevine stem segments

    Science.gov (United States)

    Mingtao Wang; Melvin T. Tyree; Roderick E. Wasylishen

    2013-01-01

    Temporal and spatial information about water refilling of embolized xylem vessels and the rate of water ascent in these vessels is critical for understanding embolism repair in intact living vascular plants. High-resolution 1H magnetic resonance imaging (MRI) experiments have been performed on embolized grapevine stem segments while they were...

  2. A fully-automatic locally adaptive thresholding algorithm for blood vessel segmentation in 3D digital subtraction angiography.

    Science.gov (United States)

    Boegel, Marco; Hoelter, Philip; Redel, Thomas; Maier, Andreas; Hornegger, Joachim; Doerfler, Arnd

    2015-01-01

    Subarachnoid hemorrhage due to a ruptured cerebral aneurysm is still a devastating disease. Planning of endovascular aneurysm therapy is increasingly based on hemodynamic simulations necessitating reliable vessel segmentation and accurate assessment of vessel diameters. In this work, we propose a fully-automatic, locally adaptive, gradient-based thresholding algorithm. Our approach consists of two steps. First, we estimate the parameters of a global thresholding algorithm using an iterative process. Then, a locally adaptive version of the approach is applied using the estimated parameters. We evaluated both methods on 8 clinical 3D DSA cases. Additionally, we propose a way to select a reference segmentation based on 2D DSA measurements. For large vessels such as the internal carotid artery, our results show very high sensitivity (97.4%), precision (98.7%) and Dice-coefficient (98.0%) with our reference segmentation. Similar results (sensitivity: 95.7%, precision: 88.9% and Dice-coefficient: 90.7%) are achieved for smaller vessels of approximately 1mm diameter.

  3. Software implementation and hardware acceleration of retinal vessel segmentation for diabetic retinopathy screening tests.

    Science.gov (United States)

    Cavinato, L; Fidone, I; Bacis, M; Del Sozzo, E; Durelli, G C; Santambrogio, M D

    2017-07-01

    Screening tests are an effective tool for the diagnosis and prevention of several diseases. Unfortunately, in order to produce an early diagnosis, the huge number of collected samples has to be processed faster than before. In particular this issue concerns image processing procedures, as they require a high computational complexity, which is not satisfied by modern software architectures. To this end, Field Programmable Gate Arrays (FPGAs) can be used to accelerate partially or entirely the computation. In this work, we demonstrate that the use of FPGAs is suitable for biomedical application, by proposing a case of study concerning the implementation of a vessels segmentation algorithm. The experimental results, computed on DRIVE and STARE databases, show remarkable improvements in terms of both execution time and power efficiency (6X and 5.7X respectively) compared to the software implementation. On the other hand, the proposed hardware approach outperforms literature works (3X speedup) without affecting the overall accuracy and sensitivity measures.

  4. Active Contours Driven by Multi-Feature Gaussian Distribution Fitting Energy with Application to Vessel Segmentation.

    Science.gov (United States)

    Wang, Lei; Zhang, Huimao; He, Kan; Chang, Yan; Yang, Xiaodong

    2015-01-01

    Active contour models are of great importance for image segmentation and can extract smooth and closed boundary contours of the desired objects with promising results. However, they cannot work well in the presence of intensity inhomogeneity. Hence, a novel region-based active contour model is proposed by taking image intensities and 'vesselness values' from local phase-based vesselness enhancement into account simultaneously to define a novel multi-feature Gaussian distribution fitting energy in this paper. This energy is then incorporated into a level set formulation with a regularization term for accurate segmentations. Experimental results based on publicly available STructured Analysis of the Retina (STARE) demonstrate our model is more accurate than some existing typical methods and can successfully segment most small vessels with varying width.

  5. Segmentation of hepatic vessels from MRI images for planning of electroporation-based treatments in the liver.

    Science.gov (United States)

    Marcan, Marija; Pavliha, Denis; Music, Maja Marolt; Fuckan, Igor; Magjarevic, Ratko; Miklavcic, Damijan

    2014-09-01

    Electroporation-based treatments rely on increasing the permeability of the cell membrane by high voltage electric pulses delivered to tissue via electrodes. To ensure that the whole tumor is covered by the sufficiently high electric field, accurate numerical models are built based on individual patient geometry. For the purpose of reconstruction of hepatic vessels from MRI images we searched for an optimal segmentation method that would meet the following initial criteria: identify major hepatic vessels, be robust and work with minimal user input. We tested the approaches based on vessel enhancement filtering, thresholding, and their combination in local thresholding. The methods were evaluated on a phantom and clinical data. Results show that thresholding based on variance minimization provides less error than the one based on entropy maximization. Best results were achieved by performing local thresholding of the original de-biased image in the regions of interest which were determined through previous vessel-enhancement filtering. In evaluation on clinical cases the proposed method scored in average sensitivity of 93.68%, average symmetric surface distance of 0.89 mm and Hausdorff distance of 4.04 mm. The proposed method to segment hepatic vessels from MRI images based on local thresholding meets all the initial criteria set at the beginning of the study and necessary to be used in treatment planning of electroporation-based treatments: it identifies the major vessels, provides results with consistent accuracy and works completely automatically. Whether the achieved accuracy is acceptable or not for treatment planning models remains to be verified through numerical modeling of effects of the segmentation error on the distribution of the electric field.

  6. Segmentation of retinal blood vessels using artificial neural networks for early detection of diabetic retinopathy

    Science.gov (United States)

    Mann, Kulwinder S.; Kaur, Sukhpreet

    2017-06-01

    There are various eye diseases in the patients suffering from the diabetes which includes Diabetic Retinopathy, Glaucoma, Hypertension etc. These all are the most common sight threatening eye diseases due to the changes in the blood vessel structure. The proposed method using supervised methods concluded that the segmentation of the retinal blood vessels can be performed accurately using neural networks training. It uses features which include Gray level features; Moment Invariant based features, Gabor filtering, Intensity feature, Vesselness feature for feature vector computation. Then the feature vector is calculated using only the prominent features.

  7. AN EFFICIENT TECHNIQUE FOR RETINAL VESSEL SEGMENTATION AND DENOISING USING MODIFIED ISODATA AND CLAHE

    Directory of Open Access Journals (Sweden)

    Khan Bahadar Khan

    2016-11-01

    Full Text Available Retinal damage caused due to complications of diabetes is known as Diabetic Retinopathy (DR. In this case, the vision is obscured due to the damage of retinal tinny blood vessels of the retina. These tinny blood vessels may cause leakage which affect the vision and can lead to complete blindness. Identification of these new retinal vessels and their structure is essential for analysis of DR. Automatic blood vessels segmentation plays a significant role to assist subsequent automatic methodologies that aid to such analysis. In literature most of the people have used computationally hungry a strong preprocessing steps followed by a simple thresholding and post processing, But in our proposed technique we utilize an arrangement of  light pre-processing which consists of Contrast Limited Adaptive Histogram Equalization (CLAHE for contrast enhancement, a difference image of green channel from its Gaussian blur filtered image to remove local noise or geometrical object, Modified Iterative Self Organizing Data Analysis Technique (MISODATA for segmentation of vessel and non-vessel pixels based on global and local thresholding, and a strong  post processing using region properties (area, eccentricity to eliminate the unwanted region/segment, non-vessel pixels and noise that never been used to reject misclassified foreground pixels. The strategy is tested on the publically accessible DRIVE (Digital Retinal Images for Vessel Extraction and STARE (STructured Analysis of the REtina databases. The performance of proposed technique is assessed comprehensively and the acquired accuracy, robustness, low complexity and high efficiency and very less computational time that make the method an efficient tool for automatic retinal image analysis. Proposed technique perform well as compared to the existing strategies on the online available databases in term of accuracy, sensitivity, specificity, false positive rate, true positive rate and area under receiver

  8. Automatic segmentation of blood vessels from retinal fundus images ...

    Indian Academy of Sciences (India)

    Abstract. Machine Learning techniques have been useful in almost every field of concern. Data Mining, a branch of Machine Learning is one of the most extensively used techniques. The ever-increasing demands in the field of medicine are being addressed by computational approaches in which Big Data analysis, image ...

  9. Fuzzy segmentation approach for quantitative SPECT

    Science.gov (United States)

    Schmitt, Thomas; Freyer, Richard; Oehme, Liane; Andreeff, Michael; Franke, Wolf-Gunter

    1998-06-01

    The determination of objective numerical criteria from nuclear medicine image data renders it possible to plan and control therapies, to compare inter- and intra-individual studies as well as time course studies and to facilitate the dominating visual interpretation of scintigrams. SPECT performs real 3D functional imaging of radionuclide distributions. The basic numerical value is the functional volume of a certain region. The volume is one prerequisite for activity measurement, but the value itself is of diagnostic importance, too. For determining the region boundaries several segmentation approaches are commonly used which are generally based on interactive ROI drawing, thresholding or edge detection methods. The image quality properties of SPECT render the segmentation process more difficult in any case. We propose an alternative segmentation approach where the crisp decision `object: yes or not' is substituted by a fuzzy boundary model `object: more or less'.

  10. Retinal vessel segmentation in colour fundus images using Extreme Learning Machine.

    Science.gov (United States)

    Zhu, Chengzhang; Zou, Beiji; Zhao, Rongchang; Cui, Jinkai; Duan, Xuanchu; Chen, Zailiang; Liang, Yixiong

    2017-01-01

    Attributes of the retinal vessel play important role in systemic conditions and ophthalmic diagnosis. In this paper, a supervised method based on Extreme Learning Machine (ELM) is proposed to segment retinal vessel. Firstly, a set of 39-D discriminative feature vectors, consisting of local features, morphological features, phase congruency, Hessian and divergence of vector fields, is extracted for each pixel of the fundus image. Then a matrix is constructed for pixel of the training set based on the feature vector and the manual labels, and acts as the input of the ELM classifier. The output of classifier is the binary retinal vascular segmentation. Finally, an optimization processing is implemented to remove the region less than 30 pixels which is isolated from the retinal vascilar. The experimental results testing on the public Digital Retinal Images for Vessel Extraction (DRIVE) database demonstrate that the proposed method is much faster than the other methods in segmenting the retinal vessels. Meanwhile the average accuracy, sensitivity, and specificity are 0.9607, 0.7140 and 0.9868, respectively. Moreover the proposed method exhibits high speed and robustness on a new Retinal Images for Screening (RIS) database. Therefore it has potential applications for real-time computer-aided diagnosis and disease screening. Copyright © 2016 Elsevier Ltd. All rights reserved.

  11. Device for Investigation of Mechanical Tension of Isolated Smooth Muscle Vessels and Airway Segments of Animals

    Science.gov (United States)

    Aleinik, A.; Karpovich, N.; Turgunova, N.; Nosarev, A.

    2016-11-01

    For the purpose of testing and the search for new drug compounds, designed to heal many human diseases, it is necessary to investigate the deformation of experimental tissue samples under influence of these drugs. For this task a precision force sensor for measuring the mechanical tension, produced by isolated ring segments of blood vessels and airways was created. The hardware and software systems for the study of changes in contractile responses of the airway smooth muscles and blood vessels of experimental animals was developed.

  12. Automated image segmentation and registration of vessel wall MRI for quantitative assessment of carotid artery vessel wall dimensions and plaque composition

    NARCIS (Netherlands)

    Klooster, Ronald van 't

    2014-01-01

    The main goal of this thesis was to develop methods for automated segmentation, registration and classification of the carotid artery vessel wall and plaque components using multi-sequence MR vessel wall images to assess atherosclerosis. First, a general introduction into atherosclerosis and

  13. Vessel segmentation in 4D arterial spin labeling magnetic resonance angiography images of the brain

    Science.gov (United States)

    Phellan, Renzo; Lindner, Thomas; Falcão, Alexandre X.; Forkert, Nils D.

    2017-03-01

    4D arterial spin labeling magnetic resonance angiography (4D ASL MRA) is a non-invasive and safe modality for cerebrovascular imaging procedures. It uses the patient's magnetically labeled blood as intrinsic contrast agent, so that no external contrast media is required. It provides important 3D structure and blood flow information but a sufficient cerebrovascular segmentation is important since it can help clinicians to analyze and diagnose vascular diseases faster, and with higher confidence as compared to simple visual rating of raw ASL MRA images. This work presents a new method for automatic cerebrovascular segmentation in 4D ASL MRA images of the brain. In this process images are denoised, corresponding image label/control image pairs of the 4D ASL MRA sequences are subtracted, and temporal intensity averaging is used to generate a static representation of the vascular system. After that, sets of vessel and background seeds are extracted and provided as input for the image foresting transform algorithm to segment the vascular system. Four 4D ASL MRA datasets of the brain arteries of healthy subjects and corresponding time-of-flight (TOF) MRA images were available for this preliminary study. For evaluation of the segmentation results of the proposed method, the cerebrovascular system was automatically segmented in the high-resolution TOF MRA images using a validated algorithm and the segmentation results were registered to the 4D ASL datasets. Corresponding segmentation pairs were compared using the Dice similarity coefficient (DSC). On average, a DSC of 0.9025 was achieved, indicating that vessels can be extracted successfully from 4D ASL MRA datasets by the proposed segmentation method.

  14. A SURVEY OF RETINA BASED DISEASE IDENTIFICATION USING BLOOD VESSEL SEGMENTATION

    Directory of Open Access Journals (Sweden)

    P Kuppusamy

    2016-11-01

    Full Text Available The colour retinal photography is one of the most essential features to identify the confirmation of various eye diseases. The iris is primary attribute to authenticate the human. This research work presents the survey and comparison of various blood vessel related feature identification, segmentation, extraction and enhancement methods. Additionally, this study is observed the various databases performance for storing the images and testing in minimal time. This paper is also provides the better performance techniques based on the survey.

  15. Retina Image Vessel Segmentation Using a Hybrid CGLI Level Set Method

    Directory of Open Access Journals (Sweden)

    Guannan Chen

    2017-01-01

    Full Text Available As a nonintrusive method, the retina imaging provides us with a better way for the diagnosis of ophthalmologic diseases. Extracting the vessel profile automatically from the retina image is an important step in analyzing retina images. A novel hybrid active contour model is proposed to segment the fundus image automatically in this paper. It combines the signed pressure force function introduced by the Selective Binary and Gaussian Filtering Regularized Level Set (SBGFRLS model with the local intensity property introduced by the Local Binary fitting (LBF model to overcome the difficulty of the low contrast in segmentation process. It is more robust to the initial condition than the traditional methods and is easily implemented compared to the supervised vessel extraction methods. Proposed segmentation method was evaluated on two public datasets, DRIVE (Digital Retinal Images for Vessel Extraction and STARE (Structured Analysis of the Retina (the average accuracy of 0.9390 with 0.7358 sensitivity and 0.9680 specificity on DRIVE datasets and average accuracy of 0.9409 with 0.7449 sensitivity and 0.9690 specificity on STARE datasets. The experimental results show that our method is effective and our method is also robust to some kinds of pathology images compared with the traditional level set methods.

  16. Automatic segmentation of the pulmonary lobes from chest CT scans based on fissures, vessels, and bronchi

    NARCIS (Netherlands)

    Lassen, B.C.; Rikxoort, E.M. van; Schmidt, M.; Kerkstra, S.; Ginneken, B. van; Kuhnigk, J.

    2013-01-01

    Segmentation of the pulmonary lobes is relevant in clinical practice and particularly challenging for cases with severe diseases or incomplete fissures. In this work an automated segmentation approach is presented that performs a markerbased watershed transformation on {CT} scans to subdivide the

  17. Use of Gabor filters and deep networks in the segmentation of retinal vessel morphology

    Science.gov (United States)

    Leopold, Henry A.; Orchard, Jeff; Zelek, John; Lakshminarayanan, Vasudevan

    2017-02-01

    The segmentation of retinal morphology has numerous applications in assessing ophthalmologic and cardiovascular disease pathologies. The early detection of many such conditions is often the most effective method for reducing patient risk. Computer aided segmentation of the vasculature has proven to be a challenge, mainly due to inconsistencies such as noise, variations in hue and brightness that can greatly reduce the quality of fundus images. Accurate fundus and/or retinal vessel maps give rise to longitudinal studies able to utilize multimodal image registration and disease/condition status measurements, as well as applications in surgery preparation and biometrics. This paper further investigates the use of a Convolutional Neural Network as a multi-channel classifier of retinal vessels using the Digital Retinal Images for Vessel Extraction database, a standardized set of fundus images used to gauge the effectiveness of classification algorithms. The CNN has a feed-forward architecture and varies from other published architectures in its combination of: max-pooling, zero-padding, ReLU layers, batch normalization, two dense layers and finally a Softmax activation function. Notably, the use of Adam to optimize training the CNN on retinal fundus images has not been found in prior review. This work builds on prior work of the authors, exploring the use of Gabor filters to boost the accuracy of the system to 0.9478 during post processing. The mean of a series of Gabor filters with varying frequencies and sigma values are applied to the output of the network and used to determine whether a pixel represents a vessel or non-vessel.

  18. Automated method for identification and artery-venous classification of vessel trees in retinal vessel networks.

    Directory of Open Access Journals (Sweden)

    Vinayak S Joshi

    Full Text Available The separation of the retinal vessel network into distinct arterial and venous vessel trees is of high interest. We propose an automated method for identification and separation of retinal vessel trees in a retinal color image by converting a vessel segmentation image into a vessel segment map and identifying the individual vessel trees by graph search. Orientation, width, and intensity of each vessel segment are utilized to find the optimal graph of vessel segments. The separated vessel trees are labeled as primary vessel or branches. We utilize the separated vessel trees for arterial-venous (AV classification, based on the color properties of the vessels in each tree graph. We applied our approach to a dataset of 50 fundus images from 50 subjects. The proposed method resulted in an accuracy of 91.44% correctly classified vessel pixels as either artery or vein. The accuracy of correctly classified major vessel segments was 96.42%.

  19. Safe electrode trajectory planning in SEEG via MIP-based vessel segmentation

    Science.gov (United States)

    Scorza, Davide; Moccia, Sara; De Luca, Giuseppe; Plaino, Lisa; Cardinale, Francesco; Mattos, Leonardo S.; Kabongo, Luis; De Momi, Elena

    2017-03-01

    Stereo-ElectroEncephaloGraphy (SEEG) is a surgical procedure that allows brain exploration of patients affected by focal epilepsy by placing intra-cerebral multi-lead electrodes. The electrode trajectory planning is challenging and time consuming. Various constraints have to be taken into account simultaneously, such as absence of vessels at the electrode Entry Point (EP), where bleeding is more likely to occur. In this paper, we propose a novel framework to help clinicians in defining a safe trajectory and focus our attention on EP. For each electrode, a Maximum Intensity Projection (MIP) image was obtained from Computer Tomography Angiography (CTA) slices of the brain first centimeter measured along the electrode trajectory. A Gaussian Mixture Model (GMM), modified to include neighborhood prior through Markov Random Fields (GMM-MRF), is used to robustly segment vessels and deal with the noisy nature of MIP images. Results are compared with simple GMM and manual global Thresholding (Th) by computing sensitivity, specificity, accuracy and Dice similarity index against manual segmentation performed under the supervision of an expert surgeon. In this work we present a novel framework which can be easily integrated into manual and automatic planner to help surgeon during the planning phase. GMM-MRF qualitatively showed better performance over GMM in reproducing the connected nature of brain vessels also in presence of noise and image intensity drops typical of MIP images. With respect Th, it is a completely automatic method and it is not influenced by inter-subject variability.

  20. Optimal Viewing Angle Determination for Multiple Vessel Segments in Coronary Angiographic Image

    Science.gov (United States)

    Wang, Xuehu; Yang, Jian; Chen, Yang; Ai, Danni; Hu, Yining; Wang, Yongtian

    2014-06-01

    Angiographic image is the perspective projection of the whole body from a 3D space to a 2D imaging plane, in which X-ray is used. As such, topological vasculature information has been lost. In 2D angiograms, foreshortening and overlapping are commonly observed in tubular-like structures. Hence, an optimum viewing angle should be determined to observe an interesting vessel segment (IVS) or an interesting vessel bifurcation (IVB) with minimized foreshortening and overlapping from a limited number of angiographic images. In this study, a novel integrated optimization method is proposed to calculate the optimum viewing angle. In the proposed method, the irregular shape and inter-branch distance of vasculatures are considered. Furthermore, three optimized conditions, including projection foreshortening rate, projection stenosis rate, and projection overlapping rate, are designed and integrated to determine the optimum viewing angle in a single vessel segment. The three conditions, including projection foreshortening, projection stenosis, and projection adjacent spacing rates, are also designed to optimize the viewing angle of bifurcations. To evaluate the performance of the proposed method, we simulated an angiographic image based on X-ray propagating principle by integrating 3D coronary artery tree models and the respective CT volume data. Experimental results demonstrate that the proposed method is very effective and robust; hence, this method can be used to determine the optimum viewing angle of IVS or IVB with irregular stenosis. The proposed method can also help physicians observe the branching structure or stenosis clearly in clinical practice.

  1. Automated Vessel Segmentation Using Infinite Perimeter Active Contour Model with Hybrid Region Information with Application to Retinal Images.

    Science.gov (United States)

    Zhao, Yitian; Rada, Lavdie; Chen, Ke; Harding, Simon P; Zheng, Yalin

    2015-09-01

    Automated detection of blood vessel structures is becoming of crucial interest for better management of vascular disease. In this paper, we propose a new infinite active contour model that uses hybrid region information of the image to approach this problem. More specifically, an infinite perimeter regularizer, provided by using L(2) Lebesgue measure of the γ -neighborhood of boundaries, allows for better detection of small oscillatory (branching) structures than the traditional models based on the length of a feature's boundaries (i.e., H(1) Hausdorff measure). Moreover, for better general segmentation performance, the proposed model takes the advantage of using different types of region information, such as the combination of intensity information and local phase based enhancement map. The local phase based enhancement map is used for its superiority in preserving vessel edges while the given image intensity information will guarantee a correct feature's segmentation. We evaluate the performance of the proposed model by applying it to three public retinal image datasets (two datasets of color fundus photography and one fluorescein angiography dataset). The proposed model outperforms its competitors when compared with other widely used unsupervised and supervised methods. For example, the sensitivity (0.742), specificity (0.982) and accuracy (0.954) achieved on the DRIVE dataset are very close to those of the second observer's annotations.

  2. Segmentation of elastic fibres in images of vessel wall sections stained with Weigert's resorcin-fuchsin.

    Science.gov (United States)

    Hernández-Morera, Pablo; Travieso-González, Carlos M; Castaño-González, Irene; Mompeó-Corredera, Blanca; Ortega-Santana, Francisco

    2017-04-01

    The elastic fibres are an essential component of the extracellular matrix in blood vessel walls that allows a long-range of deformability and passive recoil without energy input. The quantitative determination of elastic fibres will provide information on the state of the vascular wall and to determine the role and behaviour of this key structural element in different physiological and pathological vascular processes. We present a segmentation method to identify and quantify elastic fibres based on a local threshold technique and some morphological characteristics measured on the segmented objects that facilitate the discrimination between elastic fibres and other image components. The morphological characteristics analysed are the thickness and the length of an object. The segmentation method was evaluated using an image database of vein sections stained with Weigert's resorcin-fuchsin. The performance results are based on a ground truth generated manually resulting in values of sensitivity greater than 80% with the exception in two samples, and specificity values above 90% for all samples. Medical specialists carried out a visual evaluation where the observations indicate a general agreement on the segmentation results' visual quality, and the consistency between the methodology proposed and the subjective observation of the doctors for the evaluation of pathological changes in vessel wall. The proposed methodology provides more objective measurements than the qualitative methods traditionally used in the histological analysis, with a significant potential for this method to be used as a diagnostic aid for many other vascular pathological conditions and in similar tissues such as skin and mucous membranes. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. A multiview boosting approach to tissue segmentation

    Science.gov (United States)

    Kwak, Jin Tae; Xu, Sheng; Pinto, Peter A.; Turkbey, Baris; Bernardo, Marcelino; Choyke, Peter L.; Wood, Bradford J.

    2014-04-01

    Digitized histopathology images have a great potential for improving or facilitating current assessment tools in cancer pathology. In order to develop accurate and robust automated methods, the precise segmentation of histologic objects such epithelium, stroma, and nucleus is necessary, in the hopes of information extraction not otherwise obvious to the subjective eye. Here, we propose a multivew boosting approach to segment histology objects of prostate tissue. Tissue specimen images are first represented at different scales using a Gaussian kernel and converted into several forms such HSV and La*b*. Intensity- and texture-based features are extracted from the converted images. Adopting multiview boosting approach, we effectively learn a classifier to predict the histologic class of a pixel in a prostate tissue specimen. The method attempts to integrate the information from multiple scales (or views). 18 prostate tissue specimens from 4 patients were employed to evaluate the new method. The method was trained on 11 tissue specimens including 75,832 epithelial and 103,453 stroma pixels and tested on 55,319 epithelial and 74,945 stroma pixels from 7 tissue specimens. The technique showed 96.7% accuracy, and as summarized into a receiver operating characteristic (ROC) plot, the area under the ROC curve (AUC) of 0.983 (95% CI: 0.983-0.984) was achieved.

  4. PCA-based localization approach for segmentation of optic disc.

    Science.gov (United States)

    Gopi, Varun P; Anjali, M S; Niwas, S Issac

    2017-12-01

    The optic disc is the origin of the optic nerve, where the axons of retinal ganglion cells join together. The size, shape and contour of optic disc are used for classification and identification of retinal diseases. Automatic detection of eye disease requires development of an efficient algorithm. This paper proposes an efficient method for optic disc segmentation and detection for the diagnosis of retinal diseases. The methodology involves optic disc localization, blood vessel inpainting and optic disc segmentation. Localization is based on principal component analysis, and segmentation is based on Markov random field segmentation. In order to get reasonable background images, blood vessel inpainting is done before segmentation. The proposed method tested with two standard databases MESSIDOR and DRIVE, and achieved an average overlapping score of 92.41, 92.17%, respectively; also validation experiments were done with one local database from Venu Eye Hospital, New Delhi, and obtained an average overlapping score of 91%. An efficient algorithm is developed for detecting optic disc using principal component analysis-based localization and Markov random field segmentation. The comparison with alternative method yielded results that demonstrate the superiority of the proposed algorithm for optic disc detection.

  5. Infranuchal infrafloccular approach to the more vulnerable segments of the facial nerve in microvascular decompressions for the hemifacial spasm.

    Science.gov (United States)

    Park, Heung-Sik; Chang, Dong Kyu; Han, Young-Min

    2009-10-01

    We investigated the locations of compressing vessels in hemifacial spasm. To approach compression sites, we described and evaluated the efficacy of the infranuchal infrafloccular (INIF) approach. A retrospective review of 31 consecutive patients who underwent microvascular decompression (MVD) through INIF with a minimum follow-up of 1 year was performed. Along the intracranial facial nerve, we classified the compression sites into the transitional zone (TRZ), the central nervous system (CNS) segment and the peripheral nervous system (PNS) segment. The INIF approach was used to inspect the CNS segment and the TRZ. Subdural patch graft technique was used in order to achieve watertight dural closure. The cranioplasty was performed using polymethylmethacrylate. The outcome and procedure-related morbidities were evaluated. Twenty-nine patients (93%) showed complete disappearance of spasm. In two patients, the spasm was resolved gradually in 2 and 4 weeks, respectively. Late recurrence was noted in one patient (3%). The TRZ has been identified as the only compression site in 19 cases (61.3%), both the TRZ and CNS segment in 11 (35.5%) and the CNS segment only in 1 (3.2%). There was no patient having a compressing vessel in the PNS segment. Infection as a result of cerebrospinal fluid leak occurred in one patient (3%). Delayed transient facial weakness occurred in one patient. The TRZ and the CNS segment were more vulnerable area to the compression of vessels. We suggest that surgical avenue with the INIF approach provides early identification of this area.c.

  6. Body Segment Contributions to Sport Skill Performance: Two Contrasting Approaches.

    Science.gov (United States)

    Miller, Doris I.

    1980-01-01

    Two methods for approaching the problems of body segment contributions to motor performance are joint immobilization with restraint and resultant muscle torque pattern. Although the second approach is preferred, researchers face major challenges when using it. (CJ)

  7. Social discourses of healthy eating. A market segmentation approach.

    Science.gov (United States)

    Chrysochou, Polymeros; Askegaard, Søren; Grunert, Klaus G; Kristensen, Dorthe Brogård

    2010-10-01

    This paper proposes a framework of discourses regarding consumers' healthy eating as a useful conceptual scheme for market segmentation purposes. The objectives are: (a) to identify the appropriate number of health-related segments based on the underlying discursive subject positions of the framework, (b) to validate and further describe the segments based on their socio-demographic characteristics and attitudes towards healthy eating, and (c) to explore differences across segments in types of associations with food and health, as well as perceptions of food healthfulness.316 Danish consumers participated in a survey that included measures of the underlying subject positions of the proposed framework, followed by a word association task that aimed to explore types of associations with food and health, and perceptions of food healthfulness. A latent class clustering approach revealed three consumer segments: the Common, the Idealists and the Pragmatists. Based on the addressed objectives, differences across the segments are described and implications of findings are discussed.

  8. Multispectral satellite imagery segmentation using a simplified JSEG approach

    Science.gov (United States)

    Chen, QiuXiao; Luo, JianCheng; Zhou, ChengHu

    2004-11-01

    It is a big challenge to segment remote sensing images especially multispectral satellite imagery due to their unique features. In consideration of the fact that satellite imagery are playing an increasing important role, we conducted the research on segmentation of such imagery. Since multispectral satellite imagery are more similar to natural color images than to other type of images, it is more likely that studies on natural color images segmentation can be extended to multispectral satellite imagery. The obstacle of applying these studies into multispectral satellite imagery lies into their inefficiency when dealing with the large size of images. Therefore, based on a natural color image segmentation approach - JSEG, we proposed a more efficient one. First, a grid-based cluster initialization approach is proposed to obtain the initial cluster centers, based on which, a fast image quantization approach is implemented. Second, a feature image named J-image to describe local homogeneity is obtained. Then a watershed approach is applied to the J-image, and initial segmentation results are obtained. At last, based on the histogram similarity of each region, a simplified growth merging approach is proposed and the final segmentation results are obtained. By comparing the result of the JSEG approach and the proposed one, we found that the latter is rather efficient and accuracy. Advice on further studies is also presented.

  9. THE ROLE OF ECG IN LOCALIZING THE CULPRIT VESSEL OCCLUSION IN ACUTE ST SEGMENT ELEVATION MYOCARDICAL INFARCTION WITH ANGIOGRAPHIC CORRELATION

    OpenAIRE

    Markandeya Rao; Ravindra Kumar; Nanditha

    2015-01-01

    BACKGROUND & OBJECTIVES The Electrocardiogram remains a crucial tool in the identification and management of acute myocardial infarction. A detailed analysis of patterns of ST-segment elevation may influence decisions regarding the perfusion therapy. This study was undertaken to identify the culprit vessel from ECG in patients with acute ST elevation myocardial infarction and correlate with coronary angiogram. MATERIALS & METHODS This is a prospective study, condu...

  10. Clustering approach for unsupervised segmentation of malarial Plasmodium vivax parasite

    Science.gov (United States)

    Abdul-Nasir, Aimi Salihah; Mashor, Mohd Yusoff; Mohamed, Zeehaida

    2017-10-01

    Malaria is a global health problem, particularly in Africa and south Asia where it causes countless deaths and morbidity cases. Efficient control and prompt of this disease require early detection and accurate diagnosis due to the large number of cases reported yearly. To achieve this aim, this paper proposes an image segmentation approach via unsupervised pixel segmentation of malaria parasite to automate the diagnosis of malaria. In this study, a modified clustering algorithm namely enhanced k-means (EKM) clustering, is proposed for malaria image segmentation. In the proposed EKM clustering, the concept of variance and a new version of transferring process for clustered members are used to assist the assignation of data to the proper centre during the process of clustering, so that good segmented malaria image can be generated. The effectiveness of the proposed EKM clustering has been analyzed qualitatively and quantitatively by comparing this algorithm with two popular image segmentation techniques namely Otsu's thresholding and k-means clustering. The experimental results show that the proposed EKM clustering has successfully segmented 100 malaria images of P. vivax species with segmentation accuracy, sensitivity and specificity of 99.20%, 87.53% and 99.58%, respectively. Hence, the proposed EKM clustering can be considered as an image segmentation tool for segmenting the malaria images.

  11. Evaluation of an improved technique for lumen path definition and lumen segmentation of atherosclerotic vessels in CT angiography

    Energy Technology Data Exchange (ETDEWEB)

    Velsen, Evert F.S. van; Niessen, Wiro J.; Meijering, Erik; Stokking, Rik [University Medical Center Rotterdam, Departments of Radiology and Medical Informatics, Biomedical Imaging Group Rotterdam, Erasmus MC, Rotterdam (Netherlands); Weert, Thomas T. de; Monye, Cecile de; Lugt, Aad van der [University Medical Center Rotterdam, Department of Radiology, Erasmus MC, Rotterdam (Netherlands)

    2007-07-15

    Vessel image analysis is crucial when considering therapeutical options for (cardio-) vascular diseases. Our method, VAMPIRE (Vascular Analysis using Multiscale Paths Inferred from Ridges and Edges), involves two parts: a user defines a start- and endpoint upon which a lumen path is automatically defined, and which is used for initialization; the automatic segmentation of the vessel lumen on computed tomographic angiography (CTA) images. Both parts are based on the detection of vessel-like structures by analyzing intensity, edge, and ridge information. A multi-observer evaluation study was performed to compare VAMPIRE with a conventional method on the CTA data of 15 patients with carotid artery stenosis. In addition to the start- and endpoint, the two radiologists required on average 2.5 (SD: 1.9) additional points to define a lumen path when using the conventional method, and 0.1 (SD: 0.3) when using VAMPIRE. The segmentation results were quantitatively evaluated using Similarity Indices, which were slightly lower between VAMPIRE and the two radiologists (respectively 0.90 and 0.88) compared with the Similarity Index between the radiologists (0.92). The evaluation shows that the improved definition of a lumen path requires minimal user interaction, and that using this path as initialization leads to good automatic lumen segmentation results. (orig.)

  12. AUTOMOTIVE MARKET- FROM A GENERAL TO A MARKET SEGMENTATION APPROACH

    Directory of Open Access Journals (Sweden)

    Liviana Andreea Niminet

    2014-01-01

    Full Text Available Automotive market and its corresponding industry are undoubtedly of outmost importance and therefore proper market segmentation is crucial for market players, potential competitors and customers as well. Time has proved that market economic analysis often shown flaws in determining the relevant market, by using solely or mainly the geographic aspect and disregarding the importance of segments on the automotive market. For these reasons we propose a new approach of the automotive market proving the importance of proper market segmentation and defining the strategic groups within the automotive market.

  13. A Cooperative Learning-Based Clustering Approach to Lip Segmentation Without Knowing Segment Number.

    Science.gov (United States)

    Cheung, Yiu-Ming; Li, Meng; Peng, Qinmu; Chen, C L Philip

    2017-01-01

    It is usually hard to predetermine the true number of segments in lip segmentation. This paper, therefore, presents a clustering-based approach to lip segmentation without knowing the true segment number. The objective function in the proposed approach is a variant of the partition entropy (PE) and features that the coincident cluster centroids in pattern space can be equivalently substituted by one centroid with the function value unchanged. It is shown that the minimum of the proposed objective function can be reached provided that: 1) the number of positions occupied by cluster centroids in pattern space is equal to the true number of clusters and 2) these positions are coincident with the optimal cluster centroids obtained under PE criterion. In implementation, we first randomly initialize the clusters provided that the number of clusters is greater than or equal to the ground truth. Then, an iterative algorithm is utilized to minimize the proposed objective function. For each iterative step, not only is the winner, i.e., the centroid with the maximum membership degree, updated to adapt to the corresponding input data, but also the other centroids are adjusted with a specific cooperation strength, so that they are each close to the winner. Subsequently, the initial overpartition will be gradually faded out with the redundant centroids superposed over the convergence of the algorithm. Based upon the proposed algorithm, we present a lip segmentation scheme. Empirical studies have shown its efficacy in comparison with the existing methods.

  14. Vessel involvement in giant cell arteritis : an imaging approach

    NARCIS (Netherlands)

    Holm, Pieter W.; Sandovici, Maria; Slart, Riemer H. J. A.; Glaudemans, Andor W. J. M.; Rutgers, Abraham; Brouwer, Elisabeth

    Vasculitis is classified based on the size of the involved vessels. The two major forms are small vessel vasculitis and large vessel vasculitis (LVV). Main forms of LVV are Takayasu arteritis, giant cell arteritis (GCA), isolated aortitis and chronic periaortitis. This manuscript will focus on GCA,

  15. BOOST: a supervised approach for multiple sclerosis lesion segmentation.

    Science.gov (United States)

    Cabezas, Mariano; Oliver, Arnau; Valverde, Sergi; Beltran, Brigitte; Freixenet, Jordi; Vilanova, Joan C; Ramió-Torrentà, Lluís; Rovira, Alex; Lladó, Xavier

    2014-11-30

    Automatic multiple sclerosis lesion segmentation is a challenging task. An extensive analysis of the most recent techniques indicates an improvement of the results obtained when using prior knowledge and contextual information. We present BOOST, a knowledge-based approach to automatically segment multiple sclerosis lesions through a voxel by voxel classification. We used the Gentleboost classifier and a set of features, including contextual features, registered atlas probability maps and an outlier map. Results are computed on a set of 45 cases from three different hospitals (15 of each), obtaining a moderate agreement between the manual annotations and the automatically segmented results. We quantitatively compared our results with three public state-of-the-art approaches obtaining competitive results and a better overlap with manual annotations. Our approach tends to better segment those cases with high lesion load, while cases with small lesion load are more difficult to accurately segment. We believe BOOST has potential applicability in the clinical practice, although it should be improved in those cases with small lesion load. Copyright © 2014 Elsevier B.V. All rights reserved.

  16. Electrocardiography as a predictor of left main or three-vessel disease in patients with non-ST segment elevation acute coronary syndrome

    Directory of Open Access Journals (Sweden)

    Ashraf Hussien

    2011-06-01

    Conclusion: ST-segment elevation in lead aVR ⩾0.5 mm and QRS duration ⩾90 ms are good electrocardiographic predictors of left main or three vessel disease in patients with non-ST segment elevation acute coronary syndrome.

  17. A neural network approach to lung nodule segmentation

    Science.gov (United States)

    Hu, Yaoxiu; Menon, Prahlad G.

    2016-03-01

    Computed tomography (CT) imaging is a sensitive and specific lung cancer screening tool for the high-risk population and shown to be promising for detection of lung cancer. This study proposes an automatic methodology for detecting and segmenting lung nodules from CT images. The proposed methods begin with thorax segmentation, lung extraction and reconstruction of the original shape of the parenchyma using morphology operations. Next, a multi-scale hessian-based vesselness filter is applied to extract lung vasculature in lung. The lung vasculature mask is subtracted from the lung region segmentation mask to extract 3D regions representing candidate pulmonary nodules. Finally, the remaining structures are classified as nodules through shape and intensity features which are together used to train an artificial neural network. Up to 75% sensitivity and 98% specificity was achieved for detection of lung nodules in our testing dataset, with an overall accuracy of 97.62%+/-0.72% using 11 selected features as input to the neural network classifier, based on 4-fold cross-validation studies. Receiver operator characteristics for identifying nodules revealed an area under curve of 0.9476.

  18. Hybrid Segmentation of Vessels and Automated Flow Measures in In-Vivo Ultrasound Imaging

    DEFF Research Database (Denmark)

    Moshavegh, Ramin; Martins, Bo; Hansen, Kristoffer Lindskov

    2016-01-01

    method implements automated VFI flow measures such as peak systolic velocity (PSV) and volume flow. An evaluation of the performance of the segmentation algorithm relative to expert manual segmentation of 60 frames randomly chosen from 6 ultrasound sequences (10 frame randomly chosen from each sequence...... expert segmentations. The flowrig results also demonstrated that the PSVs measured from VFI had a mean relative error of 14.5% in comparison with the actual PSVs. The error for the PSVs measured from spectral Doppler was 29.5%, indicating that VFI is 15% more precise than spectral Doppler in PSV...

  19. An Approach for Identifying Benefit Segments among Prospective College Students.

    Science.gov (United States)

    Miller, Patrick; And Others

    1990-01-01

    A study investigated the importance to 578 applicants of various benefits offered by a moderately selective private university. Applicants rated the institution on 43 academic, social, financial, religious, and curricular attributes. The objective was to test the efficacy of one approach to college market segmentation. Results support the utility…

  20. A novel reporting approach to coronary angiography: "segmental coding system".

    Science.gov (United States)

    Konuralp, Cüneyt; Idiz, Mustafa; Ateş, Mehmet

    2005-01-01

    A new systematic reporting system for coronary angiography has been developed, which is capable of describing any visible intraluminal or extraluminal conditions with the exact coordinates. In this method, called "segmental coding system"(SCS), the part of the artery that is located between its two subsequent branches is considered to be an "angiographic segment". Conditions are localized according to their relationship with these angiographic segments and the anatomic border of the segments (coronary ostiums, primary, secondary and tertiary branches, grafts and proximal and distal anastomosis sites). They are also described by using a special coding system that consists of letters, numbers and signs. SCS can supply the name (stenosis, occlusion, contour deformity, aneurysm, rupture, anatomical variation, existence of stent, etc.) and the exact localization (coordinates) of the condition with its properties; filling direction, and the collateral system that fills the vessel. We applied SCS to more than 500 cineangiograpies. According to our experience, SCS provides more objective, detailed, and even correct information than the current narrative reporting system. SCS also offers many extra advantages. (a) It can describe all imaginable types of lesion combinations. (b) All of the existing conditions can be listed without missing. (c) The definitions are very precise and clear. They can easily be understood by everyone in the same way. (d) It is more advantageous on archiving, searching the database, and comparing the subsequent reports for the same patient. (e) In the future, by using specially tailored software, personal and detailed angiographic images will be reproduced from the SCS data. By being introduced into clinical practice, we believe, SCS will prove a very useful tool for both surgeons and cardiologists.

  1. THE ROLE OF ECG IN LOCALIZING THE CULPRIT VESSEL OCCLUSION IN ACUTE ST SEGMENT ELEVATION MYOCARDICAL INFARCTION WITH ANGIOGRAPHIC CORRELATION

    Directory of Open Access Journals (Sweden)

    Markandeya Rao

    2015-12-01

    Full Text Available BACKGROUND & OBJECTIVES The Electrocardiogram remains a crucial tool in the identification and management of acute myocardial infarction. A detailed analysis of patterns of ST-segment elevation may influence decisions regarding the perfusion therapy. This study was undertaken to identify the culprit vessel from ECG in patients with acute ST elevation myocardial infarction and correlate with coronary angiogram. MATERIALS & METHODS This is a prospective study, conducted on 126 patients in Osmania General Hospital, Hyderabad. Patients with ST segment elevation from ECG was evaluated to identify culprit vessel and later correlated with coronary angiogram. RESULTS Amongst 126 patients in this study, 70 patients had anterior wall and 56 patients had inferior wall myocardial infarction. ST> 1mm in V4R, ST  V3/ST  LIII Lead II was the most sensitive and ratio of STV3/STLIII >1.2 was the most specific criteria. ST in inferior leads > 1mm had maximum sensitivity in localizing occlusion in proximal D1 occlusion proximal to S1 as well. Absence of ST i in inferior leads is the most sensitive criteria in occlusion distal to S1 as well as in distal D1 in AWMI. CONCLUSION The admission ECG in patients with ST elevation AMI is valuable not only for determining early reperfusion treatment, but also provides important information to guide clinical decision-making.

  2. Word recognition in a segmentation-free approach to OCR

    Science.gov (United States)

    Mulgaonkar, Prasanna G.; Chen, Chien-Huei; DeCurtins, Jeff L.

    1994-02-01

    Segmentation is a key step in current OCR systems. It has been estimated that half the errors in character recognition are due to segmentation. We have developed a novel approach that performs OCR without the segmentation step. The approach starts by extracting significant geometric features from the input document image of the page. Each feature then `votes' for the character that could have generated that feature. Thus, even if some of the features are occluded or lost due to degradation, the remaining features can successfully identify the character. In extreme case, the degradation may be severe enough to prevent recognition of some of the characters in a word. In such cases, we use a lexicon-based word recognition technique to resolve ambiguity. Inexact matching and probabilistic evaluation used in the technique allow us to identify the correct word, by detecting a partial set of characters. This paper first presents an overview of our segmentation-free OCR system and then focuses on the word-recognition technique. Preliminary experimental results show that this is a very promising approach.

  3. Evolutionary Approach Based on Active Edges Detection for Images Segmentation

    Directory of Open Access Journals (Sweden)

    Slatnia Sihem

    2015-03-01

    Full Text Available There are many methods for segmentation which vary strongly in their approach to the problem of image segmentation. In this paper, We specified the study in a particular segmentation method of radiological images based on the active edges detection. The optimize solutions was chosen as the genetic algorithm optimization method, and to compare this formalism with other existing methods, we chose a greedy algorithm is criterion for its timeliness. we propose a method of genetic active edge detection in images gray level. In fact, for the convergence of the edge to the object edges, we use the classic and the greedy method. Indeed, the proposed method is based on the active edges optimization using the genetic algorithms process to minimize a sum various energies, in order to evolve a population of snakes to an individual who has the minimum energy.

  4. TOURISM SEGMENTATION BASED ON TOURISTS PREFERENCES: A MULTIVARIATE APPROACH

    Directory of Open Access Journals (Sweden)

    Sérgio Dominique Ferreira

    2010-11-01

    Full Text Available Over the last decades, tourism became one of the most important sectors of the international economy. Specifically in Portugal and Brazil, its contribution to Gross Domestic Product (GDP and job creation is quite relevant. In this sense, to follow a strong marketing approach on the management of tourism resources of a country comes to be paramount. Such an approach should be based on innovations which help unveil the preferences of tourists with accuracy, turning it into a competitive advantage. In this context, the main objective of the present study is to illustrate the importance and benefits associated with the use of multivariate methodologies for market segmentation. Another objective of this work is to illustrate on the importance of a post hoc segmentation. In this work, the authors applied a Cluster Analysis, with a hierarchical method followed by an  optimization method. The main results of this study allow the identification of five clusters that are distinguished by assigning special importance to certain tourism attributes at the moment of choosing a specific destination. Thus, the authors present the advantages of post hoc segmentation based on tourists’ preferences, in opposition to an a priori segmentation based on socio-demographic characteristics.

  5. An approach toward fast gradient-based image segmentation.

    Science.gov (United States)

    Hell, Benjamin; Kassubeck, Marc; Bauszat, Pablo; Eisemann, Martin; Magnor, Marcus

    2015-09-01

    In this paper, we present and investigate an approach to fast multilabel color image segmentation using convex optimization techniques. The presented model is in some ways related to the well-known Mumford-Shah model, but deviates in certain important aspects. The optimization problem has been designed with two goals in mind. The objective function should represent fundamental concepts of image segmentation, such as incorporation of weighted curve length and variation of intensity in the segmented regions, while allowing transformation into a convex concave saddle point problem that is computationally inexpensive to solve. This paper introduces such a model, the nontrivial transformation of this model into a convex-concave saddle point problem, and the numerical treatment of the problem. We evaluate our approach by applying our algorithm to various images and show that our results are competitive in terms of quality at unprecedentedly low computation times. Our algorithm allows high-quality segmentation of megapixel images in a few seconds and achieves interactive performance for low resolution images.

  6. Low QRS Voltage on Presenting Electrocardiogram Predicts Multi-vessel Disease in Anterior ST-segment Elevation Myocardial Infarction.

    Science.gov (United States)

    Kobayashi, Akihiro; Misumida, Naoki; Aoi, Shunsuke; Kanei, Yumiko

    Low QRS voltage was reported to predict adverse outcomes in acute myocardial infarction in the pre-thrombolytic era. However, the association between low voltage and angiographic findings has not been fully addressed. We performed a retrospective analysis of patients with anterior ST-segment elevation myocardial infarction (STEMI). Low QRS voltage was defined as either peak to peak QRS complex voltage voltage. Patients with low voltage had a higher rate of multi-vessel disease (MVD) (76% vs. 52%, p=0.01). Patients with low voltage were more likely to undergo coronary artery bypass grafting (CABG) during admission (11% vs. 2%, p=0.028). Low voltage was an independent predictor for MVD (OR 2.50; 95% CI 1.12 to 6.03; p=0.032). Low QRS voltage was associated with MVD and in-hospital CABG in anterior STEMI. Copyright © 2017 Elsevier Inc. All rights reserved.

  7. Replica inference approach to unsupervised multiscale image segmentation

    Science.gov (United States)

    Hu, Dandan; Ronhovde, Peter; Nussinov, Zohar

    2012-01-01

    We apply a replica-inference-based Potts model method to unsupervised image segmentation on multiple scales. This approach was inspired by the statistical mechanics problem of “community detection” and its phase diagram. Specifically, the problem is cast as identifying tightly bound clusters (“communities” or “solutes”) against a background or “solvent.” Within our multiresolution approach, we compute information-theory-based correlations among multiple solutions (“replicas”) of the same graph over a range of resolutions. Significant multiresolution structures are identified by replica correlations manifest by information theory overlaps. We further employ such information theory measures (such as normalized mutual information and variation of information), thermodynamic quantities such as the system entropy and energy, and dynamic measures monitoring the convergence time to viable solutions as metrics for transitions between various solvable and unsolvable phases. Within the solvable phase, transitions between contending solutions (such as those corresponding to segmentations on different scales) may also appear. With the aid of these correlations as well as thermodynamic measures, the phase diagram of the corresponding Potts model is analyzed at both zero and finite temperatures. Optimal parameters corresponding to a sensible unsupervised segmentations appear within the “easy phase” of the Potts model. Our algorithm is fast and shown to be at least as accurate as the best algorithms to date and to be especially suited to the detection of camouflaged images.

  8. Retinal vessel width measurement at branchings using an improved electric field theory-based graph approach.

    Directory of Open Access Journals (Sweden)

    Xiayu Xu

    Full Text Available The retinal vessel width relationship at vessel branch points in fundus images is an important biomarker of retinal and systemic disease. We propose a fully automatic method to measure the vessel widths at branch points in fundus images. The method is a graph-based method, in which a graph construction method based on electric field theory is applied which specifically deals with complex branching patterns. The vessel centerline image is used as the initial segmentation of the graph. Branching points are detected on the vessel centerline image using a set of detection kernels. Crossing points are distinguished from branch points and excluded. The electric field based graph method is applied to construct the graph. This method is inspired by the non-intersecting force lines in an electric field. At last, the method is further improved to give a consistent vessel width measurement for the whole vessel tree. The algorithm was validated on 100 artery branchings and 100 vein branchings selected from 50 fundus images by comparing with vessel width measurements from two human experts.

  9. Retinal vessel width measurement at branchings using an improved electric field theory-based graph approach.

    Science.gov (United States)

    Xu, Xiayu; Reinhardt, Joseph M; Hu, Qiao; Bakall, Benjamin; Tlucek, Paul S; Bertelsen, Geir; Abràmoff, Michael D

    2012-01-01

    The retinal vessel width relationship at vessel branch points in fundus images is an important biomarker of retinal and systemic disease. We propose a fully automatic method to measure the vessel widths at branch points in fundus images. The method is a graph-based method, in which a graph construction method based on electric field theory is applied which specifically deals with complex branching patterns. The vessel centerline image is used as the initial segmentation of the graph. Branching points are detected on the vessel centerline image using a set of detection kernels. Crossing points are distinguished from branch points and excluded. The electric field based graph method is applied to construct the graph. This method is inspired by the non-intersecting force lines in an electric field. At last, the method is further improved to give a consistent vessel width measurement for the whole vessel tree. The algorithm was validated on 100 artery branchings and 100 vein branchings selected from 50 fundus images by comparing with vessel width measurements from two human experts.

  10. Computer-aided detection of pulmonary embolism: Influence on radiologists' detection performance with respect to vessel segments

    Energy Technology Data Exchange (ETDEWEB)

    Das, Marco; Muehlenbruch, Georg; Helm, Anita; Guenther, Rolf W.; Wildberger, Joachim E. [RWTH Aachen University, Department of Diagnostic Radiology, Aachen (Germany); Bakai, Annemarie [Siemens Medical Solutions, CAD Applications, Malvern, PA (United States); Salganicoff, Marcos; Liang, Jianming; Wolf, Matthias [Siemens Medical Solutions, CT Division, Forchheim (Germany); Stanzel, Sven [RWTH Aachen University, Institute of Medical Statistics, Aachen (Germany)

    2008-07-15

    The purpose was to assess the sensitivity of a CAD software prototype for the detection of pulmonary embolism in MDCT chest examinations with regard to vessel level and to assess the influence on radiologists' detection performance. Forty-three patients with suspected PE were included in this retrospective study. MDCT chest examinations with a standard PE protocol were acquired at a 16-slice MDCT. All patient data were read by three radiologists (R1, R2, R3), and all thrombi were marked. A CAD prototype software was applied to all datasets, and each finding of the software was analyzed with regard to vessel level. The standard of reference was assessed in a consensus read. Sensitivity for the radiologists and CAD software was assessed. Thirty-three patients were positive for PE, with a total of 215 thrombi. The mean overall sensitivity for the CAD software alone was 83% (specificity, 80%). Radiologist sensitivity was 77% = R3, 82% = R2, and R1 = 87%. With the aid of the CAD software, sensitivities increased to 98% (R1), 93% (R2), and 92% (R3) (p<0.0001). CAD performance at the lobar level was 87%, at the segmental 90% and at the subsegmental 77%. With the use of CAD for PE, the detection performance of radiologists can be improved. (orig.)

  11. Unified approach for multiple sclerosis lesion segmentation on brain MRI.

    Science.gov (United States)

    Sajja, Balasrinivasa Rao; Datta, Sushmita; He, Renjie; Mehta, Meghana; Gupta, Rakesh K; Wolinsky, Jerry S; Narayana, Ponnada A

    2006-01-01

    The presence of large number of false lesion classification on segmented brain MR images is a major problem in the accurate determination of lesion volumes in multiple sclerosis (MS) brains. In order to minimize the false lesion classifications, a strategy that combines parametric and nonparametric techniques is developed and implemented. This approach uses the information from the proton density (PD)- and T2-weighted and fluid attenuation inversion recovery (FLAIR) images. This strategy involves CSF and lesion classification using the Parzen window classifier. Image processing, morphological operations, and ratio maps of PD- and T2-weighted images are used for minimizing false positives. Contextual information is exploited for minimizing the false negative lesion classifications using hidden Markov random field-expectation maximization (HMRF-EM) algorithm. Lesions are delineated using fuzzy connectivity. The performance of this algorithm is quantitatively evaluated on 23 MS patients. Similarity index, percentages of over, under, and correct estimations of lesions are computed by spatially comparing the results of present procedure with expert manual segmentation. The automated processing scheme detected 80% of the manually segmented lesions in the case of low lesion load and 93% of the lesions in those cases with high lesion load.

  12. Automatic detection and segmentation of vascular structures in dermoscopy images using a novel vesselness measure based on pixel redness and tubularness

    Science.gov (United States)

    Kharazmi, Pegah; Lui, Harvey; Stoecker, William V.; Lee, Tim

    2015-03-01

    Vascular structures are one of the most important features in the diagnosis and assessment of skin disorders. The presence and clinical appearance of vascular structures in skin lesions is a discriminating factor among different skin diseases. In this paper, we address the problem of segmentation of vascular patterns in dermoscopy images. Our proposed method is composed of three parts. First, based on biological properties of human skin, we decompose the skin to melanin and hemoglobin component using independent component analysis of skin color images. The relative quantities and pure color densities of each component were then estimated. Subsequently, we obtain three reference vectors of the mean RGB values for normal skin, pigmented skin and blood vessels from the hemoglobin component by averaging over 100000 pixels of each group outlined by an expert. Based on the Euclidean distance thresholding, we generate a mask image that extracts the red regions of the skin. Finally, Frangi measure was applied to the extracted red areas to segment the tubular structures. Finally, Otsu's thresholding was applied to segment the vascular structures and get a binary vessel mask image. The algorithm was implemented on a set of 50 dermoscopy images. In order to evaluate the performance of our method, we have artificially extended some of the existing vessels in our dermoscopy data set and evaluated the performance of the algorithm to segment the newly added vessel pixels. A sensitivity of 95% and specificity of 87% were achieved.

  13. Software-assisted live visualization system for subjacent blood vessels in endonasal endoscopic approaches

    Science.gov (United States)

    Lempe, B.; Taudt, Ch.; Maschke, R.; Gruening, J.; Ernstberger, M.; Basan, F.; Baselt, T.; Grunert, R.; Hartmann, P.

    2013-02-01

    Minimal invasive surgery methods have received growing attention in recent years. In vital important areas, it is crucial for the surgeon to have a precise knowledge of the tissue structure. Especially the visualization of arteries is desirable, as the destruction of the same can be lethal to the patient. In order to meet this requirement, the study presents a novel assistance system for endoscopic surgery. While state-of-the art systems rely on pre-operational data like computer-tomographic maps and require the use of radiation, the goal of the presented approach is to provide the clarification of subjacent blood vessels on live images of the endoscope camera system. Based on the transmission and reflection spectra of various human tissues, a prototype system with a NIR illumination unit working at 808 nm was established. Several image filtering, processing and enhancement techniques have been investigated and evaluated on the raw pictures in order to obtain high quality results. The most important were increasing contrast and thresholding by difference of Gaussian method. Based on that, it is possible to rectify a fragmented artery pattern and extract geometrical information about the structure in terms of position and orientation. By superposing the original image and the extracted segment, the surgeon is assisted with valuable live pictures of the region of interest. The whole system has been tested on a laboratory scale. An outlook on the integration of such a system in a clinical environment and obvious benefits are discussed.

  14. Gas detection by using transmittance estimation and segmentation approaches

    Science.gov (United States)

    Özısık Baskurt, Didem; Gür, Yusuf; Ömrüuzun, Fatih; ćetin, Yasemin Yardımcı

    2016-10-01

    Hyperspectral imaging for gas detection applications is an under-researched topic. The same gas model is used in most of the gas detection studies in the literature. This model aims to formulate the scene covering the gas emission as well as the background and the atmosphere. Therefore, the model requires prior knowledge on transmittance, emissivity, and temperature values of the components in the scene. The commonly used approaches to estimate these parameters include atmospheric modeling and statistical inference. However, accessing such information is costly in remote detection applications. Some studies avoid background characterization by decomposing the scene using spectral-spatial information. There are several studies in the literature using this model. They aim to detect various types of gases on different parts of electromagnetic spectrum. Most of these studies use hyperspectral radiance information regarding the scene. However, using brightness temperature map of the data instead of radiance data is more suitable for direct analysis. For this reason, we used brightness temperature spectrum in this study. On the other hand, the detection algorithms are generally based on pixel based investigation. Since the emission of the gas is sourced by a pipe or a chimney, investigating the emission region at the segment level increases detection accuracy. In this study, we used an iterative spectral feature based pixel clustering algorithm followed by spatial segmentation.

  15. Marketing ambulatory care to women: a segmentation approach.

    Science.gov (United States)

    Harrell, G D; Fors, M F

    1985-01-01

    Although significant changes are occurring in health care delivery, in many instances the new offerings are not based on a clear understanding of market segments being served. This exploratory study suggests that important differences may exist among women with regard to health care selection. Five major women's segments are identified for consideration by health care executives in developing marketing strategies. Additional research is suggested to confirm this segmentation hypothesis, validate segmental differences and quantify the findings.

  16. Technical aspects of the process of segmentation and packaging of the reactor vessel of Jose Cabrera NPP; Aspectos tecnicos del proceso de segmentacion y embalaje de la vasija del reactor de la central nuclear Jose Cabrera

    Energy Technology Data Exchange (ETDEWEB)

    Valdivieso, J. M.; Garcia Castro, R.

    2015-07-01

    Westinghouse is carrying out the segmentation of the reactor pressure vessel (RPV) within the framework of the Dismantling and Decommissioning Project of the Jose Cabrera NPP. The final concept is based on the comprehensive Westinghouse experience in the field of LWR pressure vessel and internals segmentation, and particularly in previous reactor internals segmentation project for Jose Cabrera NPP. This article shows the development of all the activities included: cutting method selection, preparatory works, cutting activities, waste characterization and packaging activities. (Author)

  17. A benefit segmentation approach for innovation-oriented university-business collaboration

    DEFF Research Database (Denmark)

    Kesting, Tobias; Gerstlberger, Wolfgang; Baaken, Thomas

    2017-01-01

    current challenges. Transferring the segmentation approach and the customer benefit perspective to university-business collaboration (UBC), this paper develops a multi-step segmentation framework aimed at identifying research customer segments in technical textile industries in Western Europe. This novel...... view helps to promote UBC and benefits both actors and society....

  18. AUTOMOTIVE MARKET- FROM A GENERAL TO A MARKET SEGMENTATION APPROACH

    National Research Council Canada - National Science Library

    Liviana Andreea Niminet

    2014-01-01

    Automotive market and its corresponding industry are undoubtedly of outmost importance and therefore proper market segmentation is crucial for market players, potential competitors and customers as well...

  19. New approach for validating the segmentation of 3D data applied to individual fibre extraction

    DEFF Research Database (Denmark)

    Emerson, Monica Jane; Dahl, Anders Bjorholm; Dahl, Vedrana Andersen

    2017-01-01

    We present two approaches for validating the segmentation of 3D data. The first approach consists on comparing the amount of estimated material to a value provided by the manufacturer. The second approach consists on comparing the segmented results to those obtained from imaging modalities...

  20. A topology-preserving approach to the segmentation of brain images with multiple sclerosis lesions

    OpenAIRE

    Shiee, Navid; Bazin, Pierre-Louis; Ozturk, Arzu; Reich, Daniel S.; Calabresi, Peter A.; Pham, Dzung L.

    2009-01-01

    We describe a new fully automatic method for the segmentation of brain images that contain multiple sclerosis white matter lesions. Multichannel magnetic resonance images are used to delineate multiple sclerosis lesions while segmenting the brain into its major structures. The method is an atlas-based segmentation technique employing a topological atlas as well as a statistical atlas. An advantage of this approach is that all segmented structures are topologically constrained, thereby allowin...

  1. Effect of a novel motion correction algorithm (SSF) on the image quality of coronary CTA with intermediate heart rates: Segment-based and vessel-based analyses

    Energy Technology Data Exchange (ETDEWEB)

    Li, Qianwen, E-mail: qianwen18@126.com; Li, Pengyu, E-mail: lipyu818@gmail.com; Su, Zhuangzhi, E-mail: suzhuangzhi@xwh.ccmu.edu.cn; Yao, Xinyu, E-mail: 314985151@qq.com; Wang, Yan, E-mail: wy19851121@126.com; Wang, Chen, E-mail: fskwangchen@gmail.com; Du, Xiangying, E-mail: duxying_xw@163.com; Li, Kuncheng, E-mail: kuncheng.li@gmail.com

    2014-11-15

    Highlights: • SSF provided better image quality than single-sector and bi-sector reconstruction among the intermediate heart rates (65–75 bpm). • Evidence for the application of prospective ECG-triggered coronary CTA with SSF onto an expanded heart rate range. • Information about the inconsistent effectiveness of SSF among the segments of coronary artery. - Abstract: Purpose: To evaluate the effect of SnapShot Freeze (SSF) reconstruction at an intermediate heart-rate (HR) range (65–75 bpm) and compare this method with single-sector reconstruction and bi-sector reconstruction on segmental and vessel bases in retrospective coronary computed tomography angiography (CCTA). Materials and methods: Retrospective electrocardiogram-gated CCTA was performed on 37 consecutive patients with HR between 65 and 75 bpm using a 64-row CT scanner. Retrospective single-sector reconstruction, bi-sector reconstruction, and SSF were performed for each patient. Multi-phase single-sector reconstruction was performed to select the optimal phase. SSF and bi-sector images were also reconstructed at the optimal phase. The images were interpreted in an intent-to-diagnose fashion by two experienced readers using a 5-point scale, with 3 points as diagnostically acceptable. Image quality among the three reconstruction groups were compared on per-patient, per-vessel, and per-segment bases. Results: The average HR of the enrolled patients was 69.4 ± 2.7 bpm. A total of 111 vessels and 481 coronary segments were assessed. SSF provided significantly higher interpretability of the coronary segments than bi-sector reconstructions. The qualified and excellent rates of SSF (97.9% and 82.3%) were significantly higher than those of single-sector (92.9% and 66.3%) and bi-sector (90.9% and 64.7%) reconstructions. The image quality score (IQS) using SSF was also significantly higher than those of single-sector and bi-sector reconstructions both on per-patient and per-vessel bases. On per-segment

  2. Tissue segmentation-assisted analysis of fMRI for human motor response: an approach combining artificial neural network and fuzzy C means.

    Science.gov (United States)

    Chiu, M J; Lin, C C; Chuang, K H; Chen, J H; Huang, K M

    2001-03-01

    The authors have developed an automated algorithm for segmentation of magnetic resonance images (MRI) of the human brain. They investigated the quantitative analysis of tissue-specific human motor response through an approach combining gradient echo functional MRI and automated segmentation analysis. Fifteen healthy volunteers, placed in a 1.5 T clinical MR imager, performed a self-paced finger opposition throughout the activation periods. T1-weighted images (WI), T2WI, and proton density WI were acquired for segmentation analysis. Single-slice axial T2* fast low-angle shot (FLASH) images were obtained during the functional study. Pixelwise cross-correlation analysis was performed to obtain an activation map. A cascaded algorithm, combining Kohonen feature maps and fuzzy C means, was applied for segmentation. After processing, masks for gray matter, white matter, small vessels, and large vessels were generated. Tissue-specific analysis showed a signal change rate of 4.53% in gray matter, 2.98% in white matter, 5.79% in small vessels, and 7.24% in large vessels. Different temporal patterns as well as different levels of activation were identified in the functional response from various types of tissue. High correlation exists between cortical gray matter and subcortical white matter (r = 0.957), while the vessel behaves somewhat different temporally. The cortical gray matter fits best to the assumed input function (r = 0.957) followed by subcortical white matter (r = 0.829) and vessels (r = 0.726). The automated algorithm of tissue-specific analysis thus can assist functional MRI studies with different modalities of response in different brain regions.

  3. A Hybrid 3D Learning-and-Interaction-based Segmentation Approach Applied on CT Liver Volumes

    Directory of Open Access Journals (Sweden)

    M. Danciu

    2013-04-01

    Full Text Available Medical volume segmentation in various imaging modalities using real 3D approaches (in contrast to slice-by-slice segmentation represents an actual trend. The increase in the acquisition resolution leads to large amount of data, requiring solutions to reduce the dimensionality of the segmentation problem. In this context, the real-time interaction with the large medical data volume represents another milestone. This paper addresses the twofold problem of the 3D segmentation applied to large data sets and also describes an intuitive neuro-fuzzy trained interaction method. We present a new hybrid semi-supervised 3D segmentation, for liver volumes obtained from computer tomography scans. This is a challenging medical volume segmentation task, due to the acquisition and inter-patient variability of the liver parenchyma. The proposed solution combines a learning-based segmentation stage (employing 3D discrete cosine transform and a probabilistic support vector machine classifier with a post-processing stage (automatic and manual segmentation refinement. Optionally, an optimization of the segmentation can be achieved by level sets, using as initialization the segmentation provided by the learning-based solution. The supervised segmentation is applied on elementary cubes in which the CT volume is decomposed by tilling, thus ensuring a significant reduction of the data to be classified by the support vector machine into liver/not liver. On real volumes, the proposed approach provides good segmentation accuracy, with a significant reduction in the computational complexity.

  4. Identifying target groups for environmentally sustainable transport: assessment of different segmentation approaches

    DEFF Research Database (Denmark)

    Haustein, Sonja; Hunecke, Marcel

    2013-01-01

    Recently, the use of attitude-based market segmentation to promote environmentally sustainable transport has significantly increased. The segmentation of the population into meaningful groups sharing similar attitudes and preferences provides valuable information about how green measures should...... and behavioural segmentations are compared regarding marketing criteria. Although none of the different approaches can claim absolute superiority, attitudinal approaches show advantages in providing startingpoints for interventions to reduce car use....

  5. A Nordic approach to impact assessment of accidents with nuclear-propelled vessels

    Energy Technology Data Exchange (ETDEWEB)

    Reistad, O. [Institute for Energy Technology, Kjeller (Norway); Hustveit, S. [Norwegian Radiation Protection Authority, Oesteraes (Norway); Palsson, S.E. [Icelandic Radiation Safety Authority, Reykjavik (Iceland); Hoe, S. [Danish Emergency Management Agency, Birkeroed (Denmark); Lahtinen, J. [STUK, Helsinki (Finland)

    2012-11-15

    The MareNuc project has identified the parameters in a graded approach to impact assessment for marine nuclear reactors. The graded approach is founded on the following elements: 1) More detailed understanding of previous accidents in nuclear-propelled vessels (initiating events, accident developments, release fractions), including release mechanisms (radionuclide retention in vessel construction); 2) Bench-marking of release scenarios using modelling tools applied in the Nordic countries, in addition to demonstration of generally accessible and free software developed by the IAEA; 3) Other systematic approaches to safety assessments of vessel port calls, and to the design and maintenance of emergency preparedness systems; More specifically, increased emphasis compared to earlier analysis after the Kursk accident is given to the engineered vessel barriers. Relevant standards from impact assessments for commercial nuclear power plants have been identified, such as from the NUREG series. The Nordic approaches to safety evaluation, impact assessments and emergency preparedness organisation was also reported as part of the project. The Canadian approach for international port calls was carefully reported and assessed as part of the project, and commended for its broad and comprehensive approach to reactor and vessel design for the nationalities involved, to the design and maintenance of emergency preparedness systems, and the well-structured and broad cooperation between civilian and military institutions. This approach goes beyond the current approach in the Nordic countries, also in the case of Norway, which experience regular port calls from allied nuclear navies. The overall result is a broader understanding in the Nordic countries for the importance of the various parameters for impact assessment of releases from marine reactors, and to the design and maintenance of an emergency preparedness organisation without detailed knowledge of the installation in question

  6. 3D Medical Volume Segmentation Using Hybrid Multiresolution Statistical Approaches

    Directory of Open Access Journals (Sweden)

    Shadi AlZu'bi

    2010-01-01

    that 3D methodologies can accurately detect the Region Of Interest (ROI. Automatic segmentation has been achieved using HMMs where the ROI is detected accurately but suffers a long computation time for its calculations.

  7. A new approach in the numerical simulation for the blood flow in large vessels

    Directory of Open Access Journals (Sweden)

    Balazs ALBERT

    2013-03-01

    Full Text Available In this paper we are proposing a new approach in the numerical simulation of the bloodflow in large vessels. The initial conditions are set to be compatible with the non-Newtonian modelused. Numerical experiments in stenosed artery and in artery with aneurysm (using COMSOL 3.3,are presented.

  8. A new approach in the numerical simulation for the blood flow in large vessels

    OpenAIRE

    Balazs ALBERT; Titus PETRILA

    2013-01-01

    In this paper we are proposing a new approach in the numerical simulation of the bloodflow in large vessels. The initial conditions are set to be compatible with the non-Newtonian modelused. Numerical experiments in stenosed artery and in artery with aneurysm (using COMSOL 3.3),are presented.

  9. Population segmentation: an approach to reducing childhood obesity inequalities.

    Science.gov (United States)

    Mahmood, Hashum; Lowe, Susan

    2017-05-01

    The aims of this study are threefold: (1) to investigate the relationship between socio-economic status (inequality) and childhood obesity prevalence within Birmingham local authority, (2) to identify any change in childhood obesity prevalence between deprivation quintiles and (3) to analyse individualised Birmingham National Child Measurement Programme (NCMP) data using a population segmentation tool to better inform obesity prevention strategies. Data from the NCMP for Birmingham (2010/2011 and 2014/2015) were analysed using the deprivation scores from the Income Domain Affecting Children Index (IDACI 2010). The percentage of children with excess weight was calculated for each local deprivation quintile. Population segmentation was carried out using the Experian's Mosaic Public Sector 6 (MPS6) segmentation tool. Childhood obesity levels have remained static at the national and Birmingham level. For Year 6 pupils, obesity levels have increased in the most deprived deprivation quintiles for boys and girls. The most affluent quintile shows a decreasing trend of obesity prevalence for boys and girls in both year groups. For the middle quintiles, the results show fluctuating trends. This research highlighted the link in Birmingham between obesity and socio-economic factors with the gap increasing between deprivation quintiles. Obesity is a complex problem that cannot simply be addressed through targeting most deprived populations, rather through a range of effective interventions tailored for the various population segments that reside within communities. Using population segmentation enables a more nuanced understanding of the potential barriers and levers within populations on their readiness for change. The segmentation of childhood obesity data will allow utilisation of social marketing methodology that will facilitate identification of suitable methods for interventions and motivate individuals to sustain behavioural change. Sequentially, it will also inform

  10. Wireless Positioning Based on a Segment-Wise Linear Approach for Modeling the Target Trajectory

    DEFF Research Database (Denmark)

    Figueiras, Joao; Pedersen, Troels; Schwefel, Hans-Peter

    2008-01-01

    measurements and the user mobility patterns. One class of typical human being movement patterns is the segment-wise linear approach, which is studied in this paper. Current tracking solutions, such as the Constant Velocity model, hardly handle such segment-wise linear patterns. In this paper we propose...... a segment-wise linear model, called the Drifting Points model. The model results in an increased performance when compared with traditional solutions....

  11. AN ADAPTIVE APPROACH FOR SEGMENTATION OF 3D LASER POINT CLOUD

    OpenAIRE

    Z. Lari; Habib, A.; E. Kwak

    2012-01-01

    Automatic processing and object extraction from 3D laser point cloud is one of the major research topics in the field of photogrammetry. Segmentation is an essential step in the processing of laser point cloud, and the quality of extracted objects from laser data is highly dependent on the validity of the segmentation results. This paper presents a new approach for reliable and efficient segmentation of planar patches from a 3D laser point cloud. In this method, the neighbourhood of each poin...

  12. Segmentation of Lung Structures in CT

    DEFF Research Database (Denmark)

    Lo, Pechin Chien Pau

    This thesis proposes and evaluates new algorithms for segmenting various lung structures in computed tomography (CT) images, namely the lungs, airway trees and vessel trees. The main objective of these algorithms is to facilitate a better platform for studying Chronic Obstructive Pulmonary Disease....... Two approaches for extracting the airway tree using the voxel classification appearance model are proposed: a vessel guided approach and a locally optimal paths approach. The vessel guided approach exploits the fact that all airways are accompanied by arteries of similar orientation...... in combination with a multiscale vessel enhancement filter for the extraction of vessel trees in CT. It was shown that the locally optimal path approach is capable of extracting a better connected vessel tree and extract more of the small peripheral vessels in comparison to applying a threshold on the output...

  13. Sperm whales ability to avoid approaching vessels is affected by sound reception in stratified waters.

    Science.gov (United States)

    Gannier, A; Marty, G

    2015-06-15

    Collision with vessels is a major cause of whale mortality in the Mediterranean Sea. The effect of non-spherical sound propagation effects on received levels (RL) was investigated for the sperm whale (Physeter macrocephalus). Relevant dive patterns were considered in each case and the RL were compared for two periods using a ray tracing software, the winter conditions and the summer stratified situation. RL were plotted as a function of time in a simulated collision case for two vessel speeds representative of a conventional merchant ship (15knots) and a fast-ferry (37knots). In almost all simulated cases, RL featured a brutal 23-31dB re 1μPa rise from below 100dB while the vessel approached the whale at close range. Summer situations were worse because this transition occurred at closer ranges, resulting in acoustic warning times of less than 30s in the fast ferry case. These results suggested that sperm whales could not be able to achieve an escape manoeuvre in a critical situation such as a fast vessel approaching under stratified waters conditions. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. A local segmentation parameter optimization approach for mapping heterogeneous urban environments using VHR imagery

    Science.gov (United States)

    Grippa, Tais; Georganos, Stefanos; Lennert, Moritz; Vanhuysse, Sabine; Wolff, Eléonore

    2017-10-01

    Mapping large heterogeneous urban areas using object-based image analysis (OBIA) remains challenging, especially with respect to the segmentation process. This could be explained both by the complex arrangement of heterogeneous land-cover classes and by the high diversity of urban patterns which can be encountered throughout the scene. In this context, using a single segmentation parameter to obtain satisfying segmentation results for the whole scene can be impossible. Nonetheless, it is possible to subdivide the whole city into smaller local zones, rather homogeneous according to their urban pattern. These zones can then be used to optimize the segmentation parameter locally, instead of using the whole image or a single representative spatial subset. This paper assesses the contribution of a local approach for the optimization of segmentation parameter compared to a global approach. Ouagadougou, located in sub-Saharan Africa, is used as case studies. First, the whole scene is segmented using a single globally optimized segmentation parameter. Second, the city is subdivided into 283 local zones, homogeneous in terms of building size and building density. Each local zone is then segmented using a locally optimized segmentation parameter. Unsupervised segmentation parameter optimization (USPO), relying on an optimization function which tends to maximize both intra-object homogeneity and inter-object heterogeneity, is used to select the segmentation parameter automatically for both approaches. Finally, a land-use/land-cover classification is performed using the Random Forest (RF) classifier. The results reveal that the local approach outperforms the global one, especially by limiting confusions between buildings and their bare-soil neighbors.

  15. A topology-preserving approach to the segmentation of brain images with multiple sclerosis lesions.

    Science.gov (United States)

    Shiee, Navid; Bazin, Pierre-Louis; Ozturk, Arzu; Reich, Daniel S; Calabresi, Peter A; Pham, Dzung L

    2010-01-15

    We describe a new fully automatic method for the segmentation of brain images that contain multiple sclerosis white matter lesions. Multichannel magnetic resonance images are used to delineate multiple sclerosis lesions while segmenting the brain into its major structures. The method is an atlas-based segmentation technique employing a topological atlas as well as a statistical atlas. An advantage of this approach is that all segmented structures are topologically constrained, thereby allowing subsequent processing such as cortical unfolding or diffeomorphic shape analysis techniques. Evaluation with both simulated and real data sets demonstrates that the method has an accuracy competitive with state-of-the-art MS lesion segmentation methods, while simultaneously segmenting the whole brain.

  16. Segmenting articular cartilage automatically using a voxel classification approach

    DEFF Research Database (Denmark)

    Folkesson, Jenny; Dam, Erik B; Olsen, Ole F

    2007-01-01

    agreement with manual segmentations, an interscan reproducibility as good as that of a human expert, and enables the separation between healthy and osteoarthritic populations. While high-field scanners offer high-quality imaging from which the articular cartilage have been evaluated extensively using manual...... and automated image analysis techniques, low-field scanners on the other hand produce lower quality images but to a fraction of the cost of their high-field counterpart. For low-field MRI, there is no well-established accuracy validation for quantitative cartilage estimates, but we show that differences between...

  17. A Multiscale Modeling Approach to Analyze Filament-Wound Composite Pressure Vessels

    Energy Technology Data Exchange (ETDEWEB)

    Nguyen, Ba Nghiep; Simmons, Kevin L.

    2013-07-22

    A multiscale modeling approach to analyze filament-wound composite pressure vessels is developed in this article. The approach, which extends the Nguyen et al. model [J. Comp. Mater. 43 (2009) 217] developed for discontinuous fiber composites to continuous fiber ones, spans three modeling scales. The microscale considers the unidirectional elastic fibers embedded in an elastic-plastic matrix obeying the Ramberg-Osgood relation and J2 deformation theory of plasticity. The mesoscale behavior representing the composite lamina is obtained through an incremental Mori-Tanaka type model and the Eshelby equivalent inclusion method [Proc. Roy. Soc. Lond. A241 (1957) 376]. The implementation of the micro-meso constitutive relations in the ABAQUS® finite element package (via user subroutines) allows the analysis of a filament-wound composite pressure vessel (macroscale) to be performed. Failure of the composite lamina is predicted by a criterion that accounts for the strengths of the fibers and of the matrix as well as of their interface. The developed approach is demonstrated in the analysis of a filament-wound pressure vessel to study the effect of the lamina thickness on the burst pressure. The predictions are favorably compared to the numerical and experimental results by Lifshitz and Dayan [Comp. Struct. 32 (1995) 313].

  18. New Computational Approaches to Determining the Astronomical Vessel Position Based on the Sumner Line

    Directory of Open Access Journals (Sweden)

    Chen Chih-Li

    2015-01-01

    Full Text Available In this paper two new approaches are developed to calculate the astronomical vessel position (AVP. Basically, determining the AVP is originated from the spherical equal altitude circles (EACs concept; therefore, based on the Sumner line's idea, which implies the trial-and-error procedure in assumption, the AVP is determined by using the two proposed approaches. One consists in taking the great circle of spherical geometry to replace the EAC to fix the AVP and the other implements the straight line of the plane geometry to replace the EAC to yield the AVP. To ensure the real AVP, both approaches choose the iteration scheme running in the assumed latitude interval to determine the final AVP. Several benchmark examples are demonstrated to show that the proposed approaches are more accurate and universal as compared with those conventional approaches used in the maritime education or practical operations.

  19. An approach to segment lung pleura from CT data with high precision

    Science.gov (United States)

    Angelats, E.; Chaisaowong, K.; Knepper, A.; Kraus, T.; Aach, T.

    2008-03-01

    A new approach to segment pleurae from CT data with high precision is introduced. This approach is developed in the segmentation's framework of an image analysis system to automatically detect pleural thickenings. The new technique to carry out the 3D segmentation of lung pleura is based on supervised range-constrained thresholding and a Gibbs-Markov random field model. An initial segmentation is done using the 3D histogram by supervised range-constrained thresholding. 3D connected component labelling is then applied to find the thorax. In order to detect and remove trachea and bronchi therein, the 3D histogram of connected pulmonary organs is modelled as a finite mixture of Gaussian distributions. Parameters are estimated using the Expectation-Maximization algorithm, which leads to the classification of that pulmonary region. As consequence left and right lungs are separated. Finally we apply a Gibbs-Markov random field model to our initial segmentation in order to achieve a high accuracy segmentation of lung pleura. The Gibbs- Markov random field is combined with maximum a posteriori estimation to estimate optimal pleural contours. With these procedures, a new segmentation strategy is developed in order to improve the reliability and accuracy of the detection of pleural contours and to achieve a better assessment performance of pleural thickenings.

  20. A scalable approach for tree segmentation within small-footprint airborne LiDAR data

    Science.gov (United States)

    Hamraz, Hamid; Contreras, Marco A.; Zhang, Jun

    2017-05-01

    This paper presents a distributed approach that scales up to segment tree crowns within a LiDAR point cloud representing an arbitrarily large forested area. The approach uses a single-processor tree segmentation algorithm as a building block in order to process the data delivered in the shape of tiles in parallel. The distributed processing is performed in a master-slave manner, in which the master maintains the global map of the tiles and coordinates the slaves that segment tree crowns within and across the boundaries of the tiles. A minimal bias was introduced to the number of detected trees because of trees lying across the tile boundaries, which was quantified and adjusted for. Theoretical and experimental analyses of the runtime of the approach revealed a near linear speedup. The estimated number of trees categorized by crown class and the associated error margins as well as the height distribution of the detected trees aligned well with field estimations, verifying that the distributed approach works correctly. The approach enables providing information of individual tree locations and point cloud segments for a forest-level area in a timely manner, which can be used to create detailed remotely sensed forest inventories. Although the approach was presented for tree segmentation within LiDAR point clouds, the idea can also be generalized to scale up processing other big spatial datasets.

  1. A modified approach combining FNEA and watershed algorithms for segmenting remotely-sensed optical images

    Science.gov (United States)

    Liu, Likun

    2018-01-01

    In the field of remote sensing image processing, remote sensing image segmentation is a preliminary step for later analysis of remote sensing image processing and semi-auto human interpretation, fully-automatic machine recognition and learning. Since 2000, a technique of object-oriented remote sensing image processing method and its basic thought prevails. The core of the approach is Fractal Net Evolution Approach (FNEA) multi-scale segmentation algorithm. The paper is intent on the research and improvement of the algorithm, which analyzes present segmentation algorithms and selects optimum watershed algorithm as an initialization. Meanwhile, the algorithm is modified by modifying an area parameter, and then combining area parameter with a heterogeneous parameter further. After that, several experiments is carried on to prove the modified FNEA algorithm, compared with traditional pixel-based method (FCM algorithm based on neighborhood information) and combination of FNEA and watershed, has a better segmentation result.

  2. A benefit segmentation approach for innovation-oriented university-business collaboration

    DEFF Research Database (Denmark)

    Kesting, Tobias; Gerstlberger, Wolfgang; Baaken, Thomas

    2018-01-01

    Increasing competition in the light of globalisation imposes challenges on both academia and businesses. Universities have to compete for additional financial means, while companies, particular in high technology business environments, are facing a stronger pressure to innovate. Universities seek...... current challenges. Transferring the segmentation approach and the customer benefit perspective to university-business collaboration (UBC), this paper develops a multi-step segmentation framework aimed at identifying research customer segments in technical textile industries in Western Europe. This novel...... to deal with this situation by academic engagement, hereby providing external research support for businesses. Relying on the market segmentation approach, promoting beneficial exchange relations between academia and businesses enables the integration of both perspectives and may contribute to solving...

  3. An optical approach to validate ultrasound surface segmentation of the heart

    Science.gov (United States)

    Wang, Bo; Schlaefer, Alexander; Zhang, Zhenxi

    2014-09-01

    The patient specific geometry of the heart is of interest for a number of diagnostic methods, e.g., when modeling the inverse electrocardiography (ECG) problem. One approach to get images of the heart is three-dimensional ultrasound. However, segmentation of the surface is complicated and segmentation methods are typically validated against manually drawn contours. This requires considerable expert knowledge. Hence, we have developed a setup that allows studying the accuracy of image segmentation from cardiac ultrasound. Using an optical tracking system, we have measured the three-dimensional surface of an isolated porcine heart. We studied whether the actual geometry can be reconstructed from both optical and ultrasound images. We illustrate the use of our approach in quantifying the segmentation result for a three-dimensional region-based active contour algorithm.

  4. Multi-atlas and unsupervised learning approach to perirectal space segmentation in CT images.

    Science.gov (United States)

    Ghose, Soumya; Denham, James W; Ebert, Martin A; Kennedy, Angel; Mitra, Jhimli; Dowling, Jason A

    2016-12-01

    Perirectal space segmentation in computed tomography images aids in quantifying radiation dose received by healthy tissues and toxicity during the course of radiation therapy treatment of the prostate. Radiation dose normalised by tissue volume facilitates predicting outcomes or possible harmful side effects of radiation therapy treatment. Manual segmentation of the perirectal space is time consuming and challenging in the presence of inter-patient anatomical variability and may suffer from inter- and intra-observer variabilities. However automatic or semi-automatic segmentation of the perirectal space in CT images is a challenging task due to inter patient anatomical variability, contrast variability and imaging artifacts. In the model presented here, a volume of interest is obtained in a multi-atlas based segmentation approach. Un-supervised learning in the volume of interest with a Gaussian-mixture-modeling based clustering approach is adopted to achieve a soft segmentation of the perirectal space. Probabilities from soft clustering are further refined by rigid registration of the multi-atlas mask in a probabilistic domain. A maximum a posteriori approach is adopted to achieve a binary segmentation from the refined probabilities. A mean volume similarity value of 97% and a mean surface difference of 3.06 ± 0.51 mm is achieved in a leave-one-patient-out validation framework with a subset of a clinical trial dataset. Qualitative results show a good approximation of the perirectal space volume compared to the ground truth.

  5. Heparin pre-treatment in patients with ST-segment elevation myocardial infarction and the risk of intracoronary thrombus and total vessel occlusion. Insights from the TASTE trial.

    Science.gov (United States)

    Karlsson, Sofia; Andell, Pontus; Mohammad, Moman A; Koul, Sasha; Olivecrona, Göran K; James, Stefan K; Fröbert, Ole; Erlinge, David

    2017-08-01

    Pre-treatment with unfractionated heparin is common in ST-segment elevation myocardial infarction (STEMI) protocols, but the effect on intracoronary thrombus burden is unknown. We studied the effect of heparin pre-treatment on intracoronary thrombus burden and Thrombolysis in Myocardial Infarction (TIMI) flow prior to percutaneous coronary intervention in patients with STEMI. The Thrombus Aspiration in ST-Elevation Myocardial Infarction in Scandinavia (TASTE) trial angiographically assessed intracoronary thrombus burden and TIMI flow, prior to percutaneous coronary intervention, in patients with STEMI. In this observational sub-study, patients pre-treated with heparin were compared with patients not pre-treated with heparin. Primary end points were a visible intracoronary thrombus and total vessel occlusion prior to percutaneous coronary intervention. Secondary end points were in-hospital bleeding, in-hospital stroke and 30-day all-cause mortality. Heparin pre-treatment was administered in 2898 out of 7144 patients (41.0%). Patients pre-treated with heparin less often presented with an intracoronary thrombus (61.3% vs. 66.0%, ppre-treatment was independently associated with a reduced risk of intracoronary thrombus (odds ratio (OR) 0.73, 95% confidence interval (CI)=0.65-0.83) and total vessel occlusion (OR 0.64, 95% CI=0.56-0.73), prior to percutaneous coronary intervention. There were no significant differences in secondary end points of in-hospital bleeding (OR 0.84, 95% CI=0.55-1.27), in-hospital stroke (OR 1.17, 95% CI=0.48-2.82) or 30-day all-cause mortality (hazard ratio 0.88, 95% CI=0.60-1.30). Heparin pre-treatment was independently associated with a lower risk of intracoronary thrombus and total vessel occlusion before percutaneous coronary intervention in patients with STEMI, without evident safety concerns, in this large multi-centre observational study.

  6. A Novel Segmentation Approach Combining Region- and Edge-Based Information for Ultrasound Images

    Directory of Open Access Journals (Sweden)

    Yaozhong Luo

    2017-01-01

    Full Text Available Ultrasound imaging has become one of the most popular medical imaging modalities with numerous diagnostic applications. However, ultrasound (US image segmentation, which is the essential process for further analysis, is a challenging task due to the poor image quality. In this paper, we propose a new segmentation scheme to combine both region- and edge-based information into the robust graph-based (RGB segmentation method. The only interaction required is to select two diagonal points to determine a region of interest (ROI on the original image. The ROI image is smoothed by a bilateral filter and then contrast-enhanced by histogram equalization. Then, the enhanced image is filtered by pyramid mean shift to improve homogeneity. With the optimization of particle swarm optimization (PSO algorithm, the RGB segmentation method is performed to segment the filtered image. The segmentation results of our method have been compared with the corresponding results obtained by three existing approaches, and four metrics have been used to measure the segmentation performance. The experimental results show that the method achieves the best overall performance and gets the lowest ARE (10.77%, the second highest TPVF (85.34%, and the second lowest FPVF (4.48%.

  7. MS lesion segmentation using a multi-channel patch-based approach with spatial consistency

    Science.gov (United States)

    Mechrez, Roey; Goldberger, Jacob; Greenspan, Hayit

    2015-03-01

    This paper presents an automatic method for segmentation of Multiple Sclerosis (MS) in Magnetic Resonance Images (MRI) of the brain. The approach is based on similarities between multi-channel patches (T1, T2 and FLAIR). An MS lesion patch database is built using training images for which the label maps are known. For each patch in the testing image, k similar patches are retrieved from the database. The matching labels for these k patches are then combined to produce an initial segmentation map for the test case. Finally a novel iterative patch-based label refinement process based on the initial segmentation map is performed to ensure spatial consistency of the detected lesions. A leave-one-out evaluation is done for each testing image in the MS lesion segmentation challenge of MICCAI 2008. Results are shown to compete with the state-of-the-art methods on the MICCAI 2008 challenge.

  8. A Retinal Vessel Detection Approach Based on Shearlet Transform and Indeterminacy Filtering on Fundus Images

    Directory of Open Access Journals (Sweden)

    Yanhui Guo

    2017-10-01

    Full Text Available A fundus image is an effective tool for ophthalmologists studying eye diseases. Retinal vessel detection is a significant task in the identification of retinal disease regions. This study presents a retinal vessel detection approach using shearlet transform and indeterminacy filtering. The fundus image’s green channel is mapped in the neutrosophic domain via shearlet transform. The neutrosophic domain images are then filtered with an indeterminacy filter to reduce the indeterminacy information. A neural network classifier is employed to identify the pixels whose inputs are the features in neutrosophic images. The proposed approach is tested on two datasets, and a receiver operating characteristic curve and the area under the curve are employed to evaluate experimental results quantitatively. The area under the curve values are 0.9476 and 0.9469 for each dataset respectively, and 0.9439 for both datasets. The comparison with the other algorithms also illustrates that the proposed method yields the highest evaluation measurement value and demonstrates the efficiency and accuracy of the proposed method.

  9. An Approach to Streaming Video Segmentation With Sub-Optimal Low-Rank Decomposition.

    Science.gov (United States)

    Li, Chenglong; Lin, Liang; Zuo, Wangmeng; Wang, Wenzhong; Tang, Jin

    2016-05-01

    This paper investigates how to perform robust and efficient video segmentation while suppressing the effects of data noises and/or corruptions, and an effective approach is introduced to this end. First, a general algorithm, called sub-optimal low-rank decomposition (SOLD), is proposed to pursue the low-rank representation for video segmentation. Given the data matrix formed by supervoxel features of an observed video sequence, SOLD seeks a sub-optimal solution by making the matrix rank explicitly determined. In particular, the representation coefficient matrix with the fixed rank can be decomposed into two sub-matrices of low rank, and then we iteratively optimize them with closed-form solutions. Moreover, we incorporate a discriminative replication prior into SOLD based on the observation that small-size video patterns tend to recur frequently within the same object. Second, based on SOLD, we present an efficient inference algorithm to perform streaming video segmentation in both unsupervised and interactive scenarios. More specifically, the constrained normalized-cut algorithm is adopted by incorporating the low-rank representation with other low level cues and temporal consistent constraints for spatio-temporal segmentation. Extensive experiments on two public challenging data sets VSB100 and SegTrack suggest that our approach outperforms other video segmentation approaches in both accuracy and efficiency.

  10. A segmentation-free approach to Arabic and Urdu OCR

    Science.gov (United States)

    Sabbour, Nazly; Shafait, Faisal

    2013-01-01

    In this paper, we present a generic Optical Character Recognition system for Arabic script languages called Nabocr. Nabocr uses OCR approaches specific for Arabic script recognition. Performing recognition on Arabic script text is relatively more difficult than Latin text due to the nature of Arabic script, which is cursive and context sensitive. Moreover, Arabic script has different writing styles that vary in complexity. Nabocr is initially trained to recognize both Urdu Nastaleeq and Arabic Naskh fonts. However, it can be trained by users to be used for other Arabic script languages. We have evaluated our system's performance for both Urdu and Arabic. In order to evaluate Urdu recognition, we have generated a dataset of Urdu text called UPTI (Urdu Printed Text Image Database), which measures different aspects of a recognition system. The performance of our system for Urdu clean text is 91%. For Arabic clean text, the performance is 86%. Moreover, we have compared the performance of our system against Tesseract's newly released Arabic recognition, and the performance of both systems on clean images is almost the same.

  11. Segmentation of the pectoral muscle in breast MRI using atlas-based approaches.

    Science.gov (United States)

    Gubern-Mérida, Albert; Kallenberg, Michiel; Martí, Robert; Karssemeijer, Nico

    2012-01-01

    Pectoral muscle segmentation is an important step in automatic breast image analysis methods and crucial for multi-modal image registration. In breast MRI, accurate delineation of the pectoral is important for volumetric breast density estimation and for pharmacokinetic analysis of dynamic contrast enhancement. In this paper we propose and study the performance of atlas-based segmentation methods evaluating two fully automatic breast MRI dedicated strategies on a set of 27 manually segmented MR volumes. One uses a probabilistic model and the other is a multi-atlas registration based approach. The multi-atlas approach performed slightly better, with an average Dice coefficient (DSC) of 0.74, while with the much faster probabilistic method a DSC of 0.72 was obtained.

  12. An Approach to a Comprehensive Test Framework for Analysis and Evaluation of Text Line Segmentation Algorithms

    Directory of Open Access Journals (Sweden)

    Zoran N. Milivojevic

    2011-09-01

    Full Text Available The paper introduces a testing framework for the evaluation and validation of text line segmentation algorithms. Text line segmentation represents the key action for correct optical character recognition. Many of the tests for the evaluation of text line segmentation algorithms deal with text databases as reference templates. Because of the mismatch, the reliable testing framework is required. Hence, a new approach to a comprehensive experimental framework for the evaluation of text line segmentation algorithms is proposed. It consists of synthetic multi-like text samples and real handwritten text as well. Although the tests are mutually independent, the results are cross-linked. The proposed method can be used for different types of scripts and languages. Furthermore, two different procedures for the evaluation of algorithm efficiency based on the obtained error type classification are proposed. The first is based on the segmentation line error description, while the second one incorporates well-known signal detection theory. Each of them has different capabilities and convenience, but they can be used as supplements to make the evaluation process efficient. Overall the proposed procedure based on the segmentation line error description has some advantages, characterized by five measures that describe measurement procedures.

  13. Segmentation of light and dark hair in dermoscopic images: a hybrid approach using a universal kernel

    Science.gov (United States)

    Nguyen, Nhi H.; Lee, Tim K.; Atkins, M. Stella

    2010-03-01

    The main challenge in an automated diagnostic system for the early diagnosis of melanoma is the correct segmentation and classification of moles, often occluded by hair in images obtained with a dermoscope. Hair occlusion causes segmentation algorithms to fail to identify the correct nevus border, and can cause errors in estimating texture measures. We present a new method to identify hair in dermoscopic images using a universal approach, which can segment both dark and light hair without prior knowledge of the hair type. First, the hair is amplified using a universal matched filtering kernel, which generates strong responses for both dark and light hair without prejudice. Then we apply local entropy thresholding on the response to get a raw binary hair mask. This hair mask is then refined and verified by a model checker. The model checker includes a combination of image processing (morphological thinning and label propagation) and mathematical (Gaussian curve fitting) techniques. The result is a clean hair mask which can be used to segment and disocclude the hair in the image, preparing it for further segmentation and analysis. Application on real dermoscopic images yields good results for thick hair of varying colours, from light to dark. The algorithm also performs well on skin images with a mixture of both dark and light hair, which was not previously possible with previous hair segmentation algorithms.

  14. [One-segment interbody lumbar arthrodesis using impacted cages: posterior unilateral approach versus posterior bilateral approach].

    Science.gov (United States)

    Commarmond, J

    2001-04-01

    We assessed the relative advantages of unilateral versus bilateral posterior approaches for lumbar spine fusion. Eighty-three patients who underwent lumbar spine fusion via a bilateral posterior approach and who had reached more than two years follow-up were compared with 80 patients who had undergone the same procedure via a unilateral posterior approach, including 54 with a follow-up greater than one year and 24 greater than two years. Most cases were L4-L5 fusions for degenerative spondylolisthesis or recurrent discal herniation with instability. Two composite carbon cages were filled with autologous cancellous bone. The key to the unilateral approach was the comfortable exposure of the disc by lamino-arthectomy; the osteosynthesis could then be performed unilaterally if only one gutter was opened. We measured bleeding and operative time to quantify surgical difficulty. At one year we assessed disc height, lordosis, frontal balance, and fusion of the operated disk. At two years, we assessed lombalgia and sciatalgia [scored from 4 (none) to 0 (intolerable)], subjective outcome, and recovery of former activity level. Mean blood loss and operative time were 360 ml and 162 min for the 83 classical procedures and 216 ml and 118 min for the 80 unilateral procedures. There were ten dural wounds with the bilateral approach and one dural wound and one transient radicular deficit with the unilateral approach. At one year, 81 of the 83 unilateral cases had reached fusion (2 nonunions). There was a mean 2 degrees gain in discal lordosis despite three cases of impaction due to osteoporosis. For the unilateral procedures, all 54 reached fusion at one year with a mean 2.5 degrees gain in lordosis, also with 3 impactions. With intersomatic distraction, balanced disc height in the frontal plane was obtained in all cases where the initial narrowing was not excessive. There were no cases of posterior displacement. There was a degradation of the supra-adjacent segment in three of

  15. A variational approach to liver segmentation using statistics from multiple sources

    Science.gov (United States)

    Zheng, Shenhai; Fang, Bin; Li, Laquan; Gao, Mingqi; Wang, Yi

    2018-01-01

    Medical image segmentation plays an important role in digital medical research, and therapy planning and delivery. However, the presence of noise and low contrast renders automatic liver segmentation an extremely challenging task. In this study, we focus on a variational approach to liver segmentation in computed tomography scan volumes in a semiautomatic and slice-by-slice manner. In this method, one slice is selected and its connected component liver region is determined manually to initialize the subsequent automatic segmentation process. From this guiding slice, we execute the proposed method downward to the last one and upward to the first one, respectively. A segmentation energy function is proposed by combining the statistical shape prior, global Gaussian intensity analysis, and enforced local statistical feature under the level set framework. During segmentation, the shape of the liver shape is estimated by minimization of this function. The improved Chan–Vese model is used to refine the shape to capture the long and narrow regions of the liver. The proposed method was verified on two independent public databases, the 3D-IRCADb and the SLIVER07. Among all the tested methods, our method yielded the best volumetric overlap error (VOE) of 6.5 +/- 2.8 % , the best root mean square symmetric surface distance (RMSD) of 2.1 +/- 0.8 mm, the best maximum symmetric surface distance (MSD) of 18.9 +/- 8.3 mm in 3D-IRCADb dataset, and the best average symmetric surface distance (ASD) of 0.8 +/- 0.5 mm, the best RMSD of 1.5 +/- 1.1 mm in SLIVER07 dataset, respectively. The results of the quantitative comparison show that the proposed liver segmentation method achieves competitive segmentation performance with state-of-the-art techniques.

  16. A variational approach to liver segmentation using statistics from multiple sources.

    Science.gov (United States)

    Zheng, Shenhai; Fang, Bin; Li, Laquan; Gao, Mingqi; Wang, Yi

    2018-01-16

    Medical image segmentation plays an important role in digital medical research, and therapy planning and delivery. However, the presence of noise and low contrast renders automatic liver segmentation an extremely challenging task. In this study, we focus on a variational approach to liver segmentation in computed tomography scan volumes in a semiautomatic and slice-by-slice manner. In this method, one slice is selected and its connected component liver region is determined manually to initialize the subsequent automatic segmentation process. From this guiding slice, we execute the proposed method downward to the last one and upward to the first one, respectively. A segmentation energy function is proposed by combining the statistical shape prior, global Gaussian intensity analysis, and enforced local statistical feature under the level set framework. During segmentation, the shape of the liver shape is estimated by minimization of this function. The improved Chan-Vese model is used to refine the shape to capture the long and narrow regions of the liver. The proposed method was verified on two independent public databases, the 3D-IRCADb and the SLIVER07. Among all the tested methods, our method yielded the best volumetric overlap error (VOE) of [Formula: see text], the best root mean square symmetric surface distance (RMSD) of [Formula: see text] mm, the best maximum symmetric surface distance (MSD) of [Formula: see text] mm in 3D-IRCADb dataset, and the best average symmetric surface distance (ASD) of [Formula: see text] mm, the best RMSD of [Formula: see text] mm in SLIVER07 dataset, respectively. The results of the quantitative comparison show that the proposed liver segmentation method achieves competitive segmentation performance with state-of-the-art techniques.

  17. Segmentation and Image Analysis of Abnormal Lungs at CT: Current Approaches, Challenges, and Future Trends

    Science.gov (United States)

    Mansoor, Awais; Foster, Brent; Xu, Ziyue; Papadakis, Georgios Z.; Folio, Les R.; Udupa, Jayaram K.; Mollura, Daniel J.

    2015-01-01

    The computer-based process of identifying the boundaries of lung from surrounding thoracic tissue on computed tomographic (CT) images, which is called segmentation, is a vital first step in radiologic pulmonary image analysis. Many algorithms and software platforms provide image segmentation routines for quantification of lung abnormalities; however, nearly all of the current image segmentation approaches apply well only if the lungs exhibit minimal or no pathologic conditions. When moderate to high amounts of disease or abnormalities with a challenging shape or appearance exist in the lungs, computer-aided detection systems may be highly likely to fail to depict those abnormal regions because of inaccurate segmentation methods. In particular, abnormalities such as pleural effusions, consolidations, and masses often cause inaccurate lung segmentation, which greatly limits the use of image processing methods in clinical and research contexts. In this review, a critical summary of the current methods for lung segmentation on CT images is provided, with special emphasis on the accuracy and performance of the methods in cases with abnormalities and cases with exemplary pathologic findings. The currently available segmentation methods can be divided into five major classes: (a) thresholding-based, (b) region-based, (c) shape-based, (d) neighboring anatomy–guided, and (e) machine learning–based methods. The feasibility of each class and its shortcomings are explained and illustrated with the most common lung abnormalities observed on CT images. In an overview, practical applications and evolving technologies combining the presented approaches for the practicing radiologist are detailed. ©RSNA, 2015 PMID:26172351

  18. 2D Fast Vessel Visualization Using a Vessel Wall Mask Guiding Fine Vessel Detection

    Directory of Open Access Journals (Sweden)

    Sotirios Raptis

    2010-01-01

    and then try to approach the ridges and branches of the vasculature's using fine detection. Fine vessel screening looks into local structural inconsistencies in vessels properties, into noise, or into not expected intensity variations observed inside pre-known vessel-body areas. The vessels are first modelled sufficiently but not precisely by their walls with a tubular model-structure that is the result of an initial segmentation. This provides a chart of likely Vessel Wall Pixels (VWPs yielding a form of a likelihood vessel map mainly based on gradient filter's intensity and spatial arrangement parameters (e.g., linear consistency. Specific vessel parameters (centerline, width, location, fall-away rate, main orientation are post-computed by convolving the image with a set of pre-tuned spatial filters called Matched Filters (MFs. These are easily computed as Gaussian-like 2D forms that use a limited range sub-optimal parameters adjusted to the dominant vessel characteristics obtained by Spatial Grey Level Difference statistics limiting the range of search into vessel widths of 16, 32, and 64 pixels. Sparse pixels are effectively eliminated by applying a limited range Hough Transform (HT or region growing. Major benefits are limiting the range of parameters, reducing the search-space for post-convolution to only masked regions, representing almost 2% of the 2D volume, good speed versus accuracy/time trade-off. Results show the potentials of our approach in terms of time for detection ROC analysis and accuracy of vessel pixel (VP detection.

  19. A probability tracking approach to segmentation of ultrasound prostate images using weak shape priors

    Science.gov (United States)

    Xu, Robert S.; Michailovich, Oleg V.; Solovey, Igor; Salama, Magdy M. A.

    2010-03-01

    Prostate specific antigen density is an established parameter for indicating the likelihood of prostate cancer. To this end, the size and volume of the gland have become pivotal quantities used by clinicians during the standard cancer screening process. As an alternative to manual palpation, an increasing number of volume estimation methods are based on the imagery data of the prostate. The necessity to process large volumes of such data requires automatic segmentation algorithms, which can accurately and reliably identify the true prostate region. In particular, transrectal ultrasound (TRUS) imaging has become a standard means of assessing the prostate due to its safe nature and high benefit-to-cost ratio. Unfortunately, modern TRUS images are still plagued by many ultrasound imaging artifacts such as speckle noise and shadowing, which results in relatively low contrast and reduced SNR of the acquired images. Consequently, many modern segmentation methods incorporate prior knowledge about the prostate geometry to enhance traditional segmentation techniques. In this paper, a novel approach to the problem of TRUS segmentation, particularly the definition of the prostate shape prior, is presented. The proposed approach is based on the concept of distribution tracking, which provides a unified framework for tracking both photometric and morphological features of the prostate. In particular, the tracking of morphological features defines a novel type of "weak" shape priors. The latter acts as a regularization force, which minimally bias the segmentation procedure, while rendering the final estimate stable and robust. The value of the proposed methodology is demonstrated in a series of experiments.

  20. Segmented Assimilation Theory and the Life Model: An Integrated Approach to Understanding Immigrants and Their Children

    Science.gov (United States)

    Piedra, Lissette M.; Engstrom, David W.

    2009-01-01

    The life model offers social workers a promising framework to use in assisting immigrant families. However, the complexities of adaptation to a new country may make it difficult for social workers to operate from a purely ecological approach. The authors use segmented assimilation theory to better account for the specificities of the immigrant…

  1. Systematic review: comparative effectiveness of adjunctive devices in patients with ST-segment elevation myocardial infarction undergoing percutaneous coronary intervention of native vessels

    Directory of Open Access Journals (Sweden)

    Sobieraj Diana M

    2011-12-01

    Full Text Available Abstract Background During percutaneous coronary intervention (PCI, dislodgement of atherothrombotic material from coronary lesions can result in distal embolization, and may lead to increased major adverse cardiovascular events (MACE and mortality. We sought to systematically review the comparative effectiveness of adjunctive devices to remove thrombi or protect against distal embolization in patients with ST-segment elevation myocardial infarction (STEMI undergoing PCI of native vessels. Methods We conducted a systematic literature search of Medline, the Cochrane Database, and Web of Science (January 1996-March 2011, http://www.clinicaltrials.gov, abstracts from major cardiology meetings, TCTMD, and CardioSource Plus. Two investigators independently screened citations and extracted data from randomized controlled trials (RCTs that compared the use of adjunctive devices plus PCI to PCI alone, evaluated patients with STEMI, enrolled a population with 95% of target lesion(s in native vessels, and reported data on at least one pre-specified outcome. Quality was graded as good, fair or poor and the strength of evidence was rated as high, moderate, low or insufficient. Disagreement was resolved through consensus. Results 37 trials met inclusion criteria. At the maximal duration of follow-up, catheter aspiration devices plus PCI significantly decreased the risk of MACE by 27% compared to PCI alone. Catheter aspiration devices also significantly increased the achievement of ST-segment resolution by 49%, myocardial blush grade of 3 (MBG-3 by 39%, and thrombolysis in myocardial infarction (TIMI 3 flow by 8%, while reducing the risk of distal embolization by 44%, no reflow by 48% and coronary dissection by 70% versus standard PCI alone. In a majority of trials, the use of catheter aspiration devices increased procedural time upon qualitative assessment. Distal filter embolic protection devices significantly increased the risk of target revascularization

  2. A Replica Inference Approach to Unsupervised Multi-Scale Image Segmentation

    OpenAIRE

    Hu, Dandan; Ronhovde, Peter; Nussinov, Zohar

    2011-01-01

    We apply a replica inference based Potts model method to unsupervised image segmentation on multiple scales. This approach was inspired by the statistical mechanics problem of "community detection" and its phase diagram. Specifically, the problem is cast as identifying tightly bound clusters ("communities" or "solutes") against a background or "solvent". Within our multiresolution approach, we compute information theory based correlations among multiple solutions ("replicas") of the same grap...

  3. Competitive Environment of the National Market of Banking Services: Essence and Approaches to Segmentation

    OpenAIRE

    Urusova Svitlana S.

    2014-01-01

    The goal of the article lies in the study of essence of the "competitive environment of the market of banking services" notion and assessment of suitability of modern approaches to its segmentation for justifying the bank competitive strategy. On the basis of analysis and synthesis of theoretical approaches of scientists the article determines essence of competitive environment of the market of banking services and systemises methodical grounds of its structural analysis. The article establis...

  4. Segmentation and feature extraction of fluid-filled uterine fibroid–A knowledge-based approach

    Directory of Open Access Journals (Sweden)

    Ratha Jeyalakshmi

    2010-10-01

    Full Text Available Uterine fibroids are the most common pelvic tumours in females. Ultrasound images of fibroids require image segmentation and feature extraction for analysis. This paper proposes a new method for segmenting the fluid-filled fibroid found in the uterus. It presents a fully automatic approach in which there is no need for human intervention. The method used in this paper employs a number of knowledge-based rules to locate the object and also utilises the concepts in mathematical morphology. It also extracts the necessary features of the fibroid which can be used to prepare the radiological report. The performance of this method is evaluated using area-based metrics.

  5. A transfer-learning approach to image segmentation across scanners by maximizing distribution similarity

    DEFF Research Database (Denmark)

    van Opbroek, Annegreet; Ikram, M. Arfan; Vernooij, Meike W.

    2013-01-01

    Many successful methods for biomedical image segmentation are based on supervised learning, where a segmentation algorithm is trained based on manually labeled training data. For supervised-learning algorithms to perform well, this training data has to be representative for the target data...... different studies than the target data. The algorithm assigns an importance weight to all training images, in such a way that the Kullback-Leibler divergence between the resulting distribution of the training data and the distribution of the target data is minimized. In a set of experiments on MRI brain......-tissue segmentation with training and target data from four substantially different studies our method improved mean classification errors with up to 25% compared to common supervised-learning approaches....

  6. Evaluation of a practical expert defined approach to patient population segmentation: a case study in Singapore

    Directory of Open Access Journals (Sweden)

    Lian Leng Low

    2017-11-01

    Full Text Available Abstract Background Segmenting the population into groups that are relatively homogeneous in healthcare characteristics or needs is crucial to facilitate integrated care and resource planning. We aimed to evaluate the feasibility of segmenting the population into discrete, non-overlapping groups using a practical expert and literature driven approach. We hypothesized that this approach is feasible utilizing the electronic health record (EHR in SingHealth. Methods In addition to well-defined segments of “Mostly healthy”, “Serious acute illness but curable” and “End of life” segments that are also present in the Ministry of Health Singapore framework, patients with chronic diseases were segmented into “Stable chronic disease”, “Complex chronic diseases without frequent hospital admissions”, and “Complex chronic diseases with frequent hospital admissions”. Using the electronic health record (EHR, we applied this framework to all adult patients who had a healthcare encounter in the Singapore Health Services Regional Health System in 2012. ICD-9, 10 and polyclinic codes were used to define chronic diseases with a comprehensive look-back period of 5 years. Outcomes (hospital admissions, emergency attendances, specialist outpatient clinic attendances and mortality were analyzed for years 2012 to 2015. Results Eight hundred twenty five thousand eight hundred seventy four patients were included in this study with the majority being healthy without chronic diseases. The most common chronic disease was hypertension. Patients with “complex chronic disease” with frequent hospital admissions segment represented 0.6% of the eligible population, but accounted for the highest hospital admissions (4.33 ± 2.12 admissions; p < 0.001 and emergency attendances (ED (3.21 ± 3.16 ED visits; p < 0.001 per patient, and a high mortality rate (16%. Patients with metastatic disease accounted for the highest specialist outpatient

  7. AN ADAPTIVE APPROACH FOR SEGMENTATION OF 3D LASER POINT CLOUD

    Directory of Open Access Journals (Sweden)

    Z. Lari

    2012-09-01

    Full Text Available Automatic processing and object extraction from 3D laser point cloud is one of the major research topics in the field of photogrammetry. Segmentation is an essential step in the processing of laser point cloud, and the quality of extracted objects from laser data is highly dependent on the validity of the segmentation results. This paper presents a new approach for reliable and efficient segmentation of planar patches from a 3D laser point cloud. In this method, the neighbourhood of each point is firstly established using an adaptive cylinder while considering the local point density and surface trend. This neighbourhood definition has a major effect on the computational accuracy of the segmentation attributes. In order to efficiently cluster planar surfaces and prevent introducing ambiguities, the coordinates of the origin's projection on each point's best fitted plane are used as the clustering attributes. Then, an octree space partitioning method is utilized to detect and extract peaks from the attribute space. Each detected peak represents a specific cluster of points which are located on a distinct planar surface in the object space. Experimental results show the potential and feasibility of applying this method for segmentation of both airborne and terrestrial laser data.

  8. An Adaptive Approach for Segmentation of 3d Laser Point Cloud

    Science.gov (United States)

    Lari, Z.; Habib, A.; Kwak, E.

    2011-09-01

    Automatic processing and object extraction from 3D laser point cloud is one of the major research topics in the field of photogrammetry. Segmentation is an essential step in the processing of laser point cloud, and the quality of extracted objects from laser data is highly dependent on the validity of the segmentation results. This paper presents a new approach for reliable and efficient segmentation of planar patches from a 3D laser point cloud. In this method, the neighbourhood of each point is firstly established using an adaptive cylinder while considering the local point density and surface trend. This neighbourhood definition has a major effect on the computational accuracy of the segmentation attributes. In order to efficiently cluster planar surfaces and prevent introducing ambiguities, the coordinates of the origin's projection on each point's best fitted plane are used as the clustering attributes. Then, an octree space partitioning method is utilized to detect and extract peaks from the attribute space. Each detected peak represents a specific cluster of points which are located on a distinct planar surface in the object space. Experimental results show the potential and feasibility of applying this method for segmentation of both airborne and terrestrial laser data.

  9. Colour Vision Model-Based Approach for Segmentation of Traffic Signs

    Directory of Open Access Journals (Sweden)

    Kunbin Hong

    2008-02-01

    Full Text Available This paper presents a new approach to segment traffic signs from the rest of a scene via CIECAM, a colour appearance model. This approach not only takes CIECAM into practical application for the first time since it was standardised in 1998, but also introduces a new way of segmenting traffic signs in order to improve the accuracy of colour-based approach. Comparison with the other CIE spaces, including CIELUV and CIELAB, and RGB colour space is also carried out. The results show that CIECAM performs better than the other three spaces with 94%, 90%, and 85% accurate rates for sunny, cloudy, and rainy days, respectively. The results also confirm that CIECAM does predict the colour appearance similar to average observers.

  10. New Approach for Segmentation and Extraction of Single Tree from Point Clouds Data and Aerial Images

    Science.gov (United States)

    Homainejad, A. S.

    2016-06-01

    This paper addresses a new approach for reconstructing a 3D model from single trees via Airborne Laser Scanners (ALS) data and aerial images. The approach detects and extracts single tree from ALS data and aerial images. The existing approaches are able to provide bulk segmentation from a group of trees; however, some methods focused on detection and extraction of a particular tree from ALS and images. Segmentation of a single tree within a group of trees is mostly a mission impossible since the detection of boundary lines between the trees is a tedious job and basically it is not feasible. In this approach an experimental formula based on the height of the trees was developed and applied in order to define the boundary lines between the trees. As a result, each single tree was segmented and extracted and later a 3D model was created. Extracted trees from this approach have a unique identification and attribute. The output has application in various fields of science and engineering such as forestry, urban planning, and agriculture. For example in forestry, the result can be used for study in ecologically diverse, biodiversity and ecosystem.

  11. Improving automated multiple sclerosis lesion segmentation with a cascaded 3D convolutional neural network approach.

    Science.gov (United States)

    Valverde, Sergi; Cabezas, Mariano; Roura, Eloy; González-Villà, Sandra; Pareto, Deborah; Vilanova, Joan C; Ramió-Torrentà, Lluís; Rovira, Àlex; Oliver, Arnau; Lladó, Xavier

    2017-07-15

    In this paper, we present a novel automated method for White Matter (WM) lesion segmentation of Multiple Sclerosis (MS) patient images. Our approach is based on a cascade of two 3D patch-wise convolutional neural networks (CNN). The first network is trained to be more sensitive revealing possible candidate lesion voxels while the second network is trained to reduce the number of misclassified voxels coming from the first network. This cascaded CNN architecture tends to learn well from a small (n≤35) set of labeled data of the same MRI contrast, which can be very interesting in practice, given the difficulty to obtain manual label annotations and the large amount of available unlabeled Magnetic Resonance Imaging (MRI) data. We evaluate the accuracy of the proposed method on the public MS lesion segmentation challenge MICCAI2008 dataset, comparing it with respect to other state-of-the-art MS lesion segmentation tools. Furthermore, the proposed method is also evaluated on two private MS clinical datasets, where the performance of our method is also compared with different recent public available state-of-the-art MS lesion segmentation methods. At the time of writing this paper, our method is the best ranked approach on the MICCAI2008 challenge, outperforming the rest of 60 participant methods when using all the available input modalities (T1-w, T2-w and FLAIR), while still in the top-rank (3rd position) when using only T1-w and FLAIR modalities. On clinical MS data, our approach exhibits a significant increase in the accuracy segmenting of WM lesions when compared with the rest of evaluated methods, highly correlating (r≥0.97) also with the expected lesion volume. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. An innovative approach of QRS segmentation based on first-derivative, Hilbert and Wavelet Transforms.

    Science.gov (United States)

    Madeiro, João P V; Cortez, Paulo C; Marques, João A L; Seisdedos, Carlos R V; Sobrinho, Carlos R M R

    2012-11-01

    The QRS detection and segmentation processes constitute the first stages of a greater process, e.g., electrocardiogram (ECG) feature extraction. Their accuracy is a prerequisite to a satisfactory performance of the P and T wave segmentation, and also to the reliability of the heart rate variability analysis. This work presents an innovative approach of QRS detection and segmentation and the detailed results of the proposed algorithm based on First-Derivative, Hilbert and Wavelet Transforms, adaptive threshold and an approach of surface indicator. The method combines the adaptive threshold, Hilbert and Wavelet Transforms techniques, avoiding the whole ECG signal preprocessing. After each QRS detection, the computation of an indicator related to the area covered by the QRS complex envelope provides the detection of the QRS onset and offset. The QRS detection proposed technique is evaluated based on the well-known MIT-BIH Arrhythmia and QT databases, obtaining the average sensitivity of 99.15% and the positive predictability of 99.18% for the first database, and 99.75% and 99.65%, respectively, for the second one. The QRS segmentation approach is evaluated on the annotated QT database with the average segmentation errors of 2.85±9.90ms and 2.83±12.26ms for QRS onset and offset, respectively. Those results demonstrate the accuracy of the developed algorithm for a wide variety of QRS morphology and the adaptation of the algorithm parameters to the existing QRS morphological variations within a single record. Copyright © 2011 IPEM. Published by Elsevier Ltd. All rights reserved.

  13. Interactive approach to segment organs at risk in radiotherapy treatment planning

    Science.gov (United States)

    Dolz, Jose; Kirisli, Hortense A.; Viard, Romain; Massoptier, Laurent

    2014-03-01

    Accurate delineation of organs at risk (OAR) is required for radiation treatment planning (RTP). However, it is a very time consuming and tedious task. The use in clinic of image guided radiation therapy (IGRT) becomes more and more popular, thus increasing the need of (semi-)automatic methods for delineation of the OAR. In this work, an interactive segmentation approach to delineate OAR is proposed and validated. The method is based on the combination of watershed transformation, which groups small areas of similar intensities in homogeneous labels, and graph cuts approach, which uses these labels to create the graph. Segmentation information can be added in any view - axial, sagittal or coronal -, making the interaction with the algorithm easy and fast. Subsequently, this information is propagated within the whole volume, providing a spatially coherent result. Manual delineations made by experts of 6 OAR - lungs, kidneys, liver, spleen, heart and aorta - over a set of 9 computed tomography (CT) scans were used as reference standard to validate the proposed approach. With a maximum of 4 interactions, a Dice similarity coefficient (DSC) higher than 0.87 was obtained, which demonstrates that, with the proposed segmentation approach, only few interactions are required to achieve similar results as the ones obtained manually. The integration of this method in the RTP process may save a considerable amount of time, and reduce the annotation complexity.

  14. A new prostate segmentation approach using multispectral magnetic resonance imaging and a statistical pattern classifier

    NARCIS (Netherlands)

    Maan, Bianca; van der Heijden, Ferdinand; Fütterer, Jurgen J.

    2012-01-01

    Prostate segmentation is essential for calculating prostate volume, creating patient-specific prostate anatomical models and image fusion. Automatic segmentation methods are preferable because manual segmentation is timeconsuming and highly subjective. Most of the currently available segmentation

  15. Segmenting healthcare terminology users: a strategic approach to large scale evolutionary development.

    Science.gov (United States)

    Price, C; Briggs, K; Brown, P J

    1999-01-01

    Healthcare terminologies have become larger and more complex, aiming to support a diverse range of functions across the whole spectrum of healthcare activity. Prioritization of development, implementation and evaluation can be achieved by regarding the "terminology" as an integrated system of content-based and functional components. Matching these components to target segments within the healthcare community, supports a strategic approach to evolutionary development and provides essential product differentiation to enable terminology providers and systems suppliers to focus on end-user requirements.

  16. Volume measurements of individual muscles in human quadriceps femoris using atlas-based segmentation approaches.

    Science.gov (United States)

    Le Troter, Arnaud; Fouré, Alexandre; Guye, Maxime; Confort-Gouny, Sylviane; Mattei, Jean-Pierre; Gondin, Julien; Salort-Campana, Emmanuelle; Bendahan, David

    2016-04-01

    Atlas-based segmentation is a powerful method for automatic structural segmentation of several sub-structures in many organs. However, such an approach has been very scarcely used in the context of muscle segmentation, and so far no study has assessed such a method for the automatic delineation of individual muscles of the quadriceps femoris (QF). In the present study, we have evaluated a fully automated multi-atlas method and a semi-automated single-atlas method for the segmentation and volume quantification of the four muscles of the QF and for the QF as a whole. The study was conducted in 32 young healthy males, using high-resolution magnetic resonance images (MRI) of the thigh. The multi-atlas-based segmentation method was conducted in 25 subjects. Different non-linear registration approaches based on free-form deformable (FFD) and symmetric diffeomorphic normalization algorithms (SyN) were assessed. Optimal parameters of two fusion methods, i.e., STAPLE and STEPS, were determined on the basis of the highest Dice similarity index (DSI) considering manual segmentation (MSeg) as the ground truth. Validation and reproducibility of this pipeline were determined using another MRI dataset recorded in seven healthy male subjects on the basis of additional metrics such as the muscle volume similarity values, intraclass coefficient, and coefficient of variation. Both non-linear registration methods (FFD and SyN) were also evaluated as part of a single-atlas strategy in order to assess longitudinal muscle volume measurements. The multi- and the single-atlas approaches were compared for the segmentation and the volume quantification of the four muscles of the QF and for the QF as a whole. Considering each muscle of the QF, the DSI of the multi-atlas-based approach was high 0.87 ± 0.11 and the best results were obtained with the combination of two deformation fields resulting from the SyN registration method and the STEPS fusion algorithm. The optimal variables for FFD

  17. A Fast Color Image Segmentation Approach Using GDF with Improved Region-Level Ncut

    Directory of Open Access Journals (Sweden)

    Ying Li

    2018-01-01

    Full Text Available Color image segmentation is fundamental in image processing and computer vision. A novel approach, GDF-Ncut, is proposed to segment color images by integrating generalized data field (GDF and improved normalized cuts (Ncut. To start with, the hierarchy-grid structure is constructed in the color feature space of an image in an attempt to reduce the time complexity but preserve the quality of image segmentation. Then a fast hierarchy-grid clustering is performed under GDF potential estimation and therefore image pixels are merged into disjoint oversegmented but meaningful initial regions. Finally, these regions are presented as a weighted undirected graph, upon which Ncut algorithm merges homogenous initial regions to achieve final image segmentation. The use of the fast clustering improves the effectiveness of Ncut because regions-based graph is constructed instead of pixel-based graph. Meanwhile, during the processes of Ncut matrix computation, oversegmented regions are grouped into homogeneous parts for greatly ameliorating the intermediate problems from GDF and accordingly decreasing the sensitivity to noise. Experimental results on a variety of color images demonstrate that the proposed method significantly reduces the time complexity while partitioning image into meaningful and physically connected regions. The method is potentially beneficial to serve object extraction and pattern recognition.

  18. Segmentation of Locally Varying Numbers of Outer Retinal Layers by a Model Selection Approach.

    Science.gov (United States)

    Novosel, Jelena; Yzer, Suzanne; Vermeer, Koenraad A; van Vliet, Lucas J

    2017-06-01

    Extraction of image-based biomarkers, such as the presence, visibility, or thickness of a certain layer, from 3-D optical coherence tomography data provides relevant clinical information. We present a method to simultaneously determine the number of visible layers in the outer retina and segment them. The method is based on a model selection approach with special attention given to the balance between the quality of a fit and model complexity. This will ensure that a more complex model is selected only if this is sufficiently supported by the data. The performance of the method was evaluated on healthy and retinitis pigmentosa (RP) affected eyes. In addition, the reproducibility of automatic method and manual annotations was evaluated on healthy eyes. Good agreement between the segmentation performed manually by a medical doctor and results obtained from the automatic segmentation was found. The mean unsigned deviation for all outer retinal layers in healthy and RP affected eyes varied between 2.6 and 4.9 μm. The reproducibility of the automatic method was similar to the reproducibility of the manual segmentation. Overall, the method provides a flexible and accurate solution for determining the visibility and location of outer retinal layers and could be used as an aid for the disease diagnosis and monitoring.

  19. A pyramidal approach for automatic segmentation of multiple sclerosis lesions in brain MRI.

    Science.gov (United States)

    Pachai, C; Zhu, Y M; Grimaud, J; Hermier, M; Dromigny-Badin, A; Boudraa, A; Gimenez, G; Confavreux, C; Froment, J C

    1998-01-01

    Quantitative assessment of Magnetic Resonance Imaging (MRI) lesion load of patients with multiple sclerosis (MS) is the most objective approach for a better understanding of the history of the pathology, either natural or modified by therapies. To achieve an accurate and reproducible quantification of MS lesions in conventional brain MRI, an automatic segmentation algorithm based on a multiresolution approach using pyramidal data structures is proposed. The systematic pyramidal decomposition in the frequency domain provides a robust and flexible low level tool for MR image analysis. Context-dependent rules regarding MRI findings in MS are used as high level considerations for automatic lesion detection.

  20. A new approach to assymmetric feedback in a segmented broad area diode laser

    DEFF Research Database (Denmark)

    Jensen, Ole Bjarlin; Thestrup Nielsen, Birgitte; Petersen, Paul Michael

    2009-01-01

    We present the demonstration of a non-critical setup for asymmetric feedback in a segmented broad area diode laser. We compare the dependence of the beam quality on the position of the dispersive element for standard spectral beam combining and our new non-critical setup. We find that our new...... approach is significantly less critical to the position of the dispersive element. It is shown that we can displace the dispersive element by at least 50% of the focal length of the collimating lens away from the Fourier plane without compromising performance. Furthermore, our approach provides the same...

  1. A fully automatic approach for multimodal PET and MR image segmentation in gamma knife treatment planning.

    Science.gov (United States)

    Rundo, Leonardo; Stefano, Alessandro; Militello, Carmelo; Russo, Giorgio; Sabini, Maria Gabriella; D'Arrigo, Corrado; Marletta, Francesco; Ippolito, Massimo; Mauri, Giancarlo; Vitabile, Salvatore; Gilardi, Maria Carla

    2017-06-01

    Nowadays, clinical practice in Gamma Knife treatments is generally based on MRI anatomical information alone. However, the joint use of MRI and PET images can be useful for considering both anatomical and metabolic information about the lesion to be treated. In this paper we present a co-segmentation method to integrate the segmented Biological Target Volume (BTV), using [ 11 C]-Methionine-PET (MET-PET) images, and the segmented Gross Target Volume (GTV), on the respective co-registered MR images. The resulting volume gives enhanced brain tumor information to be used in stereotactic neuro-radiosurgery treatment planning. GTV often does not match entirely with BTV, which provides metabolic information about brain lesions. For this reason, PET imaging is valuable and it could be used to provide complementary information useful for treatment planning. In this way, BTV can be used to modify GTV, enhancing Clinical Target Volume (CTV) delineation. A novel fully automatic multimodal PET/MRI segmentation method for Leksell Gamma Knife ® treatments is proposed. This approach improves and combines two computer-assisted and operator-independent single modality methods, previously developed and validated, to segment BTV and GTV from PET and MR images, respectively. In addition, the GTV is utilized to combine the superior contrast of PET images with the higher spatial resolution of MRI, obtaining a new BTV, called BTV MRI . A total of 19 brain metastatic tumors, undergone stereotactic neuro-radiosurgery, were retrospectively analyzed. A framework for the evaluation of multimodal PET/MRI segmentation is also presented. Overlap-based and spatial distance-based metrics were considered to quantify similarity concerning PET and MRI segmentation approaches. Statistics was also included to measure correlation among the different segmentation processes. Since it is not possible to define a gold-standard CTV according to both MRI and PET images without treatment response assessment

  2. Semiautomated segmentation of head and neck cancers in 18F-FDG PET scans: A just-enough-interaction approach

    Science.gov (United States)

    Beichel, Reinhard R.; Van Tol, Markus; Ulrich, Ethan J.; Bauer, Christian; Chang, Tangel; Plichta, Kristin A.; Smith, Brian J.; Sunderland, John J.; Graham, Michael M.; Sonka, Milan; Buatti, John M.

    2016-01-01

    Purpose: The purpose of this work was to develop, validate, and compare a highly computer-aided method for the segmentation of hot lesions in head and neck 18F-FDG PET scans. Methods: A semiautomated segmentation method was developed, which transforms the segmentation problem into a graph-based optimization problem. For this purpose, a graph structure around a user-provided approximate lesion centerpoint is constructed and a suitable cost function is derived based on local image statistics. To handle frequently occurring situations that are ambiguous (e.g., lesions adjacent to each other versus lesion with inhomogeneous uptake), several segmentation modes are introduced that adapt the behavior of the base algorithm accordingly. In addition, the authors present approaches for the efficient interactive local and global refinement of initial segmentations that are based on the “just-enough-interaction” principle. For method validation, 60 PET/CT scans from 59 different subjects with 230 head and neck lesions were utilized. All patients had squamous cell carcinoma of the head and neck. A detailed comparison with the current clinically relevant standard manual segmentation approach was performed based on 2760 segmentations produced by three experts. Results: Segmentation accuracy measured by the Dice coefficient of the proposed semiautomated and standard manual segmentation approach was 0.766 and 0.764, respectively. This difference was not statistically significant (p = 0.2145). However, the intra- and interoperator standard deviations were significantly lower for the semiautomated method. In addition, the proposed method was found to be significantly faster and resulted in significantly higher intra- and interoperator segmentation agreement when compared to the manual segmentation approach. Conclusions: Lack of consistency in tumor definition is a critical barrier for radiation treatment targeting as well as for response assessment in clinical trials and in

  3. QFD-ANP Approach for the Conceptual Design of Research Vessels: A Case Study

    Science.gov (United States)

    Venkata Subbaiah, Kambagowni; Yeshwanth Sai, Koneru; Suresh, Challa

    2016-10-01

    Conceptual design is a subset of concept art wherein a new idea of product is created instead of a visual representation which would directly be used in a final product. The purpose is to understand the needs of conceptual design which are being used in engineering designs and to clarify the current conceptual design practice. Quality function deployment (QFD) is a customer oriented design approach for developing new or improved products and services to enhance customer satisfaction. House of quality (HOQ) has been traditionally used as planning tool of QFD which translates customer requirements (CRs) into design requirements (DRs). Factor analysis is carried out in order to reduce the CR portions of HOQ. The analytical hierarchical process is employed to obtain the priority ratings of CR's which are used in constructing HOQ. This paper mainly discusses about the conceptual design of an oceanographic research vessel using analytical network process (ANP) technique. Finally the QFD-ANP integrated methodology helps to establish the importance ratings of DRs.

  4. Improved radiological/nuclear source localization in variable NORM background: An MLEM approach with segmentation data

    Energy Technology Data Exchange (ETDEWEB)

    Penny, Robert D., E-mail: robert.d.penny@leidos.com [Leidos Inc., 10260 Campus Point Road, San Diego, CA (United States); Crowley, Tanya M.; Gardner, Barbara M.; Mandell, Myron J.; Guo, Yanlin; Haas, Eric B.; Knize, Duane J.; Kuharski, Robert A.; Ranta, Dale; Shyffer, Ryan [Leidos Inc., 10260 Campus Point Road, San Diego, CA (United States); Labov, Simon; Nelson, Karl; Seilhan, Brandon [Lawrence Livermore National Laboratory, Livermore, CA (United States); Valentine, John D. [Lawrence Berkeley National Laboratory, Berkeley, CA (United States)

    2015-06-01

    A novel approach and algorithm have been developed to rapidly detect and localize both moving and static radiological/nuclear (R/N) sources from an airborne platform. Current aerial systems with radiological sensors are limited in their ability to compensate for variable naturally occurring radioactive material (NORM) background. The proposed approach suppresses the effects of NORM background by incorporating additional information to segment the survey area into regions over which the background is likely to be uniform. The method produces pixelated Source Activity Maps (SAMs) of both target and background radionuclide activity over the survey area. The task of producing the SAMs requires (1) the development of a forward model which describes the transformation of radionuclide activity to detector measurements and (2) the solution of the associated inverse problem. The inverse problem is ill-posed as there are typically fewer measurements than unknowns. In addition the measurements are subject to Poisson statistical noise. The Maximum-Likelihood Expectation-Maximization (MLEM) algorithm is used to solve the inverse problem as it is well suited for under-determined problems corrupted by Poisson noise. A priori terrain information is incorporated to segment the reconstruction space into regions within which we constrain NORM background activity to be uniform. Descriptions of the algorithm and examples of performance with and without segmentation on simulated data are presented.

  5. Quantitative segmentation of fluorescence microscopy images of heterogeneous tissue: Approach for tuning algorithm parameters

    Science.gov (United States)

    Mueller, Jenna L.; Harmany, Zachary T.; Mito, Jeffrey K.; Kennedy, Stephanie A.; Kim, Yongbaek; Dodd, Leslie; Geradts, Joseph; Kirsch, David G.; Willett, Rebecca M.; Brown, J. Quincy; Ramanujam, Nimmi

    2013-02-01

    The combination of fluorescent contrast agents with microscopy is a powerful technique to obtain real time images of tissue histology without the need for fixing, sectioning, and staining. The potential of this technology lies in the identification of robust methods for image segmentation and quantitation, particularly in heterogeneous tissues. Our solution is to apply sparse decomposition (SD) to monochrome images of fluorescently-stained microanatomy to segment and quantify distinct tissue types. The clinical utility of our approach is demonstrated by imaging excised margins in a cohort of mice after surgical resection of a sarcoma. Representative images of excised margins were used to optimize the formulation of SD and tune parameters associated with the algorithm. Our results demonstrate that SD is a robust solution that can advance vital fluorescence microscopy as a clinically significant technology.

  6. Short time effects of radiotherapy on lymphatic vessels and restorative lymphatic pathways: experimental approaches ina mouse model.

    Science.gov (United States)

    Pastouret, F; Lievens, P; Leduc, O; Bourgeois, P; Tournel, K; Lamote, J; Zirak, C; Leduc, A

    2014-06-01

    Radiotherapy (RT) is an important component in the therapeutic approach to oncologic conditions. This study presents the investigative results on the impact of RT on lymphatic vessels and on the regenerative response of the lymphatic system in a mouse model. We first irradiated 3 groups of ten mice using brachytherapy in a single treatment of 20 Gy. We then performed morphological examination of the irradiated lymphatic vessels using an in vivo microscopic transillumination technique at 2, 4, and 6 weeks. Next we evaluated lymphatic flow using lymphoscintigraphy and in vivo microscopy at 6 to 11 weeks in: 10 additional mice following irradiation as above (IR), in 10 mice following incision of a lymphatic vessel (I), and in a non-treated control group of 10 mice (N). Intact lymphatic vessels were observed in all mice at 2, 4, and 8 weeks following the single dose of radiotherapy in the first group of mice and normal lymphatic flow was fully restored in the irradiated (IR) and incised (I) mice indicating that the reparative substitution lymphatic pathways are functioning normally. We found that following irradiation with one dose of 20 Gy, lymphatic vessels were not visibly damaged and also that lymphatic flow was consistently restored and substitutive lymphatic pathways formed.

  7. Large blood vessel stretch in lumbar spine through anterior surgical approach: An experimental study in adult goat

    Directory of Open Access Journals (Sweden)

    Liehua Liu

    2014-01-01

    Full Text Available Background: Various anterior lumbar surgical approaches, including the minimally invasive approach, have greatly improved in recent years. Vascular complications resulting from ALIF are frequently reported. Little information is available about the safety of large blood vessel stretch. We evaluated the right side stretch limit (RSSL of the abdominal aorta (AAA and the inferior vena cava (IVC without blood flow occlusion and investigated stretch-induced histological injury and thrombosis in the iliac and femoral arteries and veins and the stretched vessels. Materials and Methods: The RSSL of blood vessels in five adult goats was measured by counting the number of 0.5-cm-thick wood slabs that were inserted between the right lumbar edge and the stretch hook. Twenty seven adult goats were divided into three groups to investigate histological injury and thrombosis under a stretch to 0.5 cm (group I 1.5 cm (group II for 2 h, or no stretch (group III. Blood vessel samples from groups I and II were analyzed on postsurgical days 1, 3, and 7. Thrombogenesis was examined in the iliac and femoral arteries and veins. Results: The RSSL of large blood vessels in front of L4/5 was 1.5 cm from the right lumbar edge. All goats survived surgery without complications. No injury or thrombosis in the large blood vessels in front of the lumbar vertebrae and in the iliac or femoral arteries and veins was observed. Under light microscopy, group I showed slight swelling of endothelial cells in the AAA and no histological injury of the IVC. The AAA of group II showed endothelial cell damage, unclear organelles, and incomplete cell connections by electron microscopy. Conclusions: The AAA and IVC in a goat model can be stretched by ≤0.5 cm, with no thrombosis in the AAA, IVC, iliac or femoral arteries and veins.

  8. A hybrid approach based on logistic classification and iterative contrast enhancement algorithm for hyperintense multiple sclerosis lesion segmentation.

    Science.gov (United States)

    da Silva Senra Filho, Antonio Carlos

    2017-11-18

    Multiple sclerosis (MS) is a neurodegenerative disease with increasing importance in recent years, in which the T2 weighted with fluid attenuation inversion recovery (FLAIR) MRI imaging technique has been addressed for the hyperintense MS lesion assessment. Many automatic lesion segmentation approaches have been proposed in the literature in order to assist health professionals. In this study, a new hybrid lesion segmentation approach based on logistic classification (LC) and the iterative contrast enhancement (ICE) method is proposed (LC+ICE). T1 and FLAIR MRI images from 32 secondary progressive MS (SPMS) patients were used in the LC+ICE method, in which manual segmentation was used as the ground truth lesion segmentation. The DICE, Sensitivity, Specificity, Area under the ROC curve (AUC), and Volume Similarity measures showed that the LC+ICE method is able to provide a precise and robust lesion segmentation estimate, which was compared with two recent FLAIR lesion segmentation approaches. In addition, the proposed method also showed a stable segmentation among lesion loads, showing a wide applicability to different disease stages. The LC+ICE procedure is a suitable alternative to assist the manual FLAIR hyperintense MS lesion segmentation task.

  9. Classifying and profiling Social Networking Site users: a latent segmentation approach.

    Science.gov (United States)

    Alarcón-del-Amo, María-del-Carmen; Lorenzo-Romero, Carlota; Gómez-Borja, Miguel-Ángel

    2011-09-01

    Social Networking Sites (SNSs) have showed an exponential growth in the last years. The first step for an efficient use of SNSs stems from an understanding of the individuals' behaviors within these sites. In this research, we have obtained a typology of SNS users through a latent segmentation approach, based on the frequency by which users perform different activities within the SNSs, sociodemographic variables, experience in SNSs, and dimensions related to their interaction patterns. Four different segments have been obtained. The "introvert" and "novel" users are the more occasional. They utilize SNSs mainly to communicate with friends, although "introverts" are more passive users. The "versatile" user performs different activities, although occasionally. Finally, the "expert-communicator" performs a greater variety of activities with a higher frequency. They tend to perform some marketing-related activities such as commenting on ads or gathering information about products and brands as well as commenting ads. The companies can take advantage of these segmentation schemes in different ways: first, by tracking and monitoring information interchange between users regarding their products and brands. Second, they should match the SNS users' profiles with their market targets to use SNSs as marketing tools. Finally, for most business, the expert users could be interesting opinion leaders and potential brand influencers.

  10. A level-set approach to joint image segmentation and registration with application to CT lung imaging.

    Science.gov (United States)

    Swierczynski, Piotr; Papież, Bartłomiej W; Schnabel, Julia A; Macdonald, Colin

    2017-06-15

    Automated analysis of structural imaging such as lung Computed Tomography (CT) plays an increasingly important role in medical imaging applications. Despite significant progress in the development of image registration and segmentation methods, lung registration and segmentation remain a challenging task. In this paper, we present a novel image registration and segmentation approach, for which we develop a new mathematical formulation to jointly segment and register three-dimensional lung CT volumes. The new algorithm is based on a level-set formulation, which merges a classic Chan-Vese segmentation with the active dense displacement field estimation. Combining registration with segmentation has two key advantages: it allows to eliminate the problem of initializing surface based segmentation methods, and to incorporate prior knowledge into the registration in a mathematically justified manner, while remaining computationally attractive. We evaluate our framework on a publicly available lung CT data set to demonstrate the properties of the new formulation. The presented results show the improved accuracy for our joint segmentation and registration algorithm when compared to registration and segmentation performed separately. Copyright © 2017 Elsevier Ltd. All rights reserved.

  11. 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

    2017-07-21

    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, 2017. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

  12. Effort dynamics in a fisheries bioeconomic model: A vessel level approach through Game Theory

    Directory of Open Access Journals (Sweden)

    Gorka Merino

    2007-09-01

    Full Text Available Red shrimp, Aristeus antennatus (Risso, 1816 is one of the most important resources for the bottom-trawl fleets in the northwestern Mediterranean, in terms of both landings and economic value. A simple bioeconomic model introducing Game Theory for the prediction of effort dynamics at vessel level is proposed. The game is performed by the twelve vessels exploiting red shrimp in Blanes. Within the game, two solutions are performed: non-cooperation and cooperation. The first is proposed as a realistic method for the prediction of individual effort strategies and the second is used to illustrate the potential profitability of the analysed fishery. The effort strategy for each vessel is the number of fishing days per year and their objective is profit maximisation, individual profits for the non-cooperative solution and total profits for the cooperative one. In the present analysis, strategic conflicts arise from the differences between vessels in technical efficiency (catchability coefficient and economic efficiency (defined here. The ten-year and 1000-iteration stochastic simulations performed for the two effort solutions show that the best strategy from both an economic and a conservationist perspective is homogeneous effort cooperation. However, the results under non-cooperation are more similar to the observed data on effort strategies and landings.

  13. A combined approach for the enhancement and segmentation of mammograms using modified fuzzy C-means method in wavelet domain.

    Science.gov (United States)

    Srivastava, Subodh; Sharma, Neeraj; Singh, S K; Srivastava, R

    2014-07-01

    In this paper, a combined approach for enhancement and segmentation of mammograms is proposed. In preprocessing stage, a contrast limited adaptive histogram equalization (CLAHE) method is applied to obtain the better contrast mammograms. After this, the proposed combined methods are applied. In the first step of the proposed approach, a two dimensional (2D) discrete wavelet transform (DWT) is applied to all the input images. In the second step, a proposed nonlinear complex diffusion based unsharp masking and crispening method is applied on the approximation coefficients of the wavelet transformed images to further highlight the abnormalities such as micro-calcifications, tumours, etc., to reduce the false positives (FPs). Thirdly, a modified fuzzy c-means (FCM) segmentation method is applied on the output of the second step. In the modified FCM method, the mutual information is proposed as a similarity measure in place of conventional Euclidian distance based dissimilarity measure for FCM segmentation. Finally, the inverse 2D-DWT is applied. The efficacy of the proposed unsharp masking and crispening method for image enhancement is evaluated in terms of signal-to-noise ratio (SNR) and that of the proposed segmentation method is evaluated in terms of random index (RI), global consistency error (GCE), and variation of information (VoI). The performance of the proposed segmentation approach is compared with the other commonly used segmentation approaches such as Otsu's thresholding, texture based, k-means, and FCM clustering as well as thresholding. From the obtained results, it is observed that the proposed segmentation approach performs better and takes lesser processing time in comparison to the standard FCM and other segmentation methods in consideration.

  14. NEW APPROACHES TO CUSTOMER BASE SEGMENTATION FOR SMALL AND MEDIUM-SIZED ENTERPRISES

    Directory of Open Access Journals (Sweden)

    Meleancă Raluca-Cristina

    2012-12-01

    Full Text Available The primary purpose of this paper is to explore current praxis and theory related to customer segmentation and to offer an approach which is best suited for small and medium sized enterprises. The proposed solution is the result of an exploratory research aiming to recognize the main variables which influence the practice of segmenting the customer base and to study the most applied alternatives available for all types of enterprises. The research has been performed by studying a large set of secondary data, scientific literature and case studies regarding smaller companies from the European Union. The result of the research consists in an original approach to customer base segmentation, which combines aspects belonging to different well spread practices and applies them to the specific needs of a small or medium company, which typically has limited marketing resources in general and targeted marketing resources in particular. The significance of the proposed customer base segmentation approach lies in the fact that, even though smaller enterprises are in most economies the greatest in number compared to large companies, most of the literature on targeting practices has focused primarily on big companies dealing with a very large clientele, while the case of the smaller companies has been to some extent unfairly neglected. Targeted marketing is becoming more and more important for all types of companies nowadays, as a result of technology advances which make targeted communication easier and less expensive than in the past and also due to the fact that broad-based media have decreased their impact over the years. For a very large proportion of smaller companies, directing their marketing budgets towards targeted campaigns is a clever initiative, as broad based approaches are in many cases less effective and much more expensive. Targeted marketing stratagems are generally related to high tech domains such as artificial intelligence, data mining

  15. Delineating Individual Trees from Lidar Data: A Comparison of Vector- and Raster-based Segmentation Approaches

    Directory of Open Access Journals (Sweden)

    Maggi Kelly

    2013-08-01

    Full Text Available Light detection and ranging (lidar data is increasingly being used for ecosystem monitoring across geographic scales. This work concentrates on delineating individual trees in topographically-complex, mixed conifer forest across the California’s Sierra Nevada. We delineated individual trees using vector data and a 3D lidar point cloud segmentation algorithm, and using raster data with an object-based image analysis (OBIA of a canopy height model (CHM. The two approaches are compared to each other and to ground reference data. We used high density (9 pulses/m2, discreet lidar data and WorldView-2 imagery to delineate individual trees, and to classify them by species or species types. We also identified a new method to correct artifacts in a high-resolution CHM. Our main focus was to determine the difference between the two types of approaches and to identify the one that produces more realistic results. We compared the delineations via tree detection, tree heights, and the shape of the generated polygons. The tree height agreement was high between the two approaches and the ground data (r2: 0.93–0.96. Tree detection rates increased for more dominant trees (8–100 percent. The two approaches delineated tree boundaries that differed in shape: the lidar-approach produced fewer, more complex, and larger polygons that more closely resembled real forest structure.

  16. Image segmentation for uranium isotopic analysis by SIMS: Combined adaptive thresholding and marker controlled watershed approach

    Energy Technology Data Exchange (ETDEWEB)

    Willingham, David G.; Naes, Benjamin E.; Heasler, Patrick G.; Zimmer, Mindy M.; Barrett, Christopher A.; Addleman, Raymond S.

    2016-05-31

    A novel approach to particle identification and particle isotope ratio determination has been developed for nuclear safeguard applications. This particle search approach combines an adaptive thresholding algorithm and marker-controlled watershed segmentation (MCWS) transform, which improves the secondary ion mass spectrometry (SIMS) isotopic analysis of uranium containing particle populations for nuclear safeguards applications. The Niblack assisted MCWS approach (a.k.a. SEEKER) developed for this work has improved the identification of isotopically unique uranium particles under conditions that have historically presented significant challenges for SIMS image data processing techniques. Particles obtained from five NIST uranium certified reference materials (CRM U129A, U015, U150, U500 and U850) were successfully identified in regions of SIMS image data 1) where a high variability in image intensity existed, 2) where particles were touching or were in close proximity to one another and/or 3) where the magnitude of ion signal for a given region was count limited. Analysis of the isotopic distributions of uranium containing particles identified by SEEKER showed four distinct, accurately identified 235U enrichment distributions, corresponding to the NIST certified 235U/238U isotope ratios for CRM U129A/U015 (not statistically differentiated), U150, U500 and U850. Additionally, comparison of the minor uranium isotope (234U, 235U and 236U) atom percent values verified that, even in the absence of high precision isotope ratio measurements, SEEKER could be used to segment isotopically unique uranium particles from SIMS image data. Although demonstrated specifically for SIMS analysis of uranium containing particles for nuclear safeguards, SEEKER has application in addressing a broad set of image processing challenges.

  17. Global Kalman filter approaches to estimate absolute angles of lower limb segments.

    Science.gov (United States)

    Nogueira, Samuel L; Lambrecht, Stefan; Inoue, Roberto S; Bortole, Magdo; Montagnoli, Arlindo N; Moreno, Juan C; Rocon, Eduardo; Terra, Marco H; Siqueira, Adriano A G; Pons, Jose L

    2017-05-16

    In this paper we propose the use of global Kalman filters (KFs) to estimate absolute angles of lower limb segments. Standard approaches adopt KFs to improve the performance of inertial sensors based on individual link configurations. In consequence, for a multi-body system like a lower limb exoskeleton, the inertial measurements of one link (e.g., the shank) are not taken into account in other link angle estimations (e.g., foot). Global KF approaches, on the other hand, correlate the collective contribution of all signals from lower limb segments observed in the state-space model through the filtering process. We present a novel global KF (matricial global KF) relying only on inertial sensor data, and validate both this KF and a previously presented global KF (Markov Jump Linear Systems, MJLS-based KF), which fuses data from inertial sensors and encoders from an exoskeleton. We furthermore compare both methods to the commonly used local KF. The results indicate that the global KFs performed significantly better than the local KF, with an average root mean square error (RMSE) of respectively 0.942° for the MJLS-based KF, 1.167° for the matrical global KF, and 1.202° for the local KFs. Including the data from the exoskeleton encoders also resulted in a significant increase in performance. The results indicate that the current practice of using KFs based on local models is suboptimal. Both the presented KF based on inertial sensor data, as well our previously presented global approach fusing inertial sensor data with data from exoskeleton encoders, were superior to local KFs. We therefore recommend to use global KFs for gait analysis and exoskeleton control.

  18. Vessel Operating Units (Vessels)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains data for vessels that are greater than five net tons and have a current US Coast Guard documentation number. Beginning in1979, the NMFS...

  19. Intracoronary Compared to Intravenous Abciximab in Patients with ST Segment Elevation Myocardial Infarction Treated with Primary Percutaneous Coronary Intervention Reduces Mortality, Target Vessel Revascularization and Reinfarction after 1 Year

    DEFF Research Database (Denmark)

    Iversen, Allan Zeeberg; Galatius, Soeren; Abildgaard, Ulrik

    2011-01-01

    Objectives: Administration of the glycoprotein IIb/IIIa inhibitor abciximab to patients with ST segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (pPCI) improves outcome. Data have suggested that an intracoronary (IC) bolus might be superior...... to the standard intravenous (IV) administration. We have previously reported reduced short-term mortality and need for target vessel revascularization (TVR) with the IC route. We now present long-term data from our randomized trial on IC versus IV abciximab in pPCI-treated STEMI patients. Methods: A total of 355...

  20. Shape-Based Approach to Robust Image Segmentation Using Kernel PCA

    National Research Council Canada - National Science Library

    Dambreville, Samuel; Rathi, Yogesh; Tannenbaum, Allen

    2006-01-01

    Segmentation involves separating an object from the background. In this work, we propose a novel segmentation method combining image information with prior shape knowledge, within the level-set framework...

  1. A Self-Calibrating Multi-Band Region Growing Approach to Segmentation of Single and Multi-Band Images

    Energy Technology Data Exchange (ETDEWEB)

    Paglieroni, D W

    2002-12-20

    Image segmentation transforms pixel-level information from raw images to a higher level of abstraction in which related pixels are grouped into disjoint spatial regions. Such regions typically correspond to natural or man-made objects or structures, natural variations in land cover, etc. For many image interpretation tasks (such as land use assessment, automatic target cueing, defining relationships between objects, etc.), segmentation can be an important early step. Remotely sensed images (e.g., multi-spectral and hyperspectral images) often contain many spectral bands (i.e., multiple layers of 2D images). Multi-band images are important because they contain more information than single-band images. Objects or natural variations that are readily apparent in certain spectral bands may be invisible in 2D broadband images. In this paper, the classical region growing approach to image segmentation is generalized from single to multi-band images. While it is widely recognized that the quality of image segmentation is affected by which segmentation algorithm is used, this paper shows that algorithm parameter values can have an even more profound effect. A novel self-calibration framework is developed for automatically selecting parameter values that produce segmentations that most closely resemble a calibration edge map (derived separately using a simple edge detector). Although the framework is generic in the sense that it can imbed any core segmentation algorithm, this paper only demonstrates self-calibration with multi-band region growing. The framework is applied to a variety of AVIRIS image blocks at different spectral resolutions, in an effort to assess the impact of spectral resolution on segmentation quality. The image segmentations are assessed quantitatively, and it is shown that segmentation quality does not generally appear to be highly correlated with spectral resolution.

  2. Strategic market segmentation

    National Research Council Canada - National Science Library

    Maricic, Branko; Djordjevic, Aleksandar

    2015-01-01

    ..., 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...

  3. ASSESSING INTERNATIONAL MARKET SEGMENTATION APPROACHES: RELATED LITERATURE AT A GLANCE AND SUGGESSTIONS FOR GLOBAL COMPANIES

    OpenAIRE

    Nacar, Ramazan; Uray, Nimet

    2016-01-01

    With the increasing role of globalization, international market segmentation has become a critical success factor for global companies, which aim for international market expansion. Despite the practice of numerous methods and bases for international market segmentation, international market segmentation is still a complex and an under-researched area. By considering all these issues, underdeveloped and under-researched international market segmentation bases such as social, cultural, psychol...

  4. A SEGMENT-BASED APPROACH FOR DTM DERIVATION OF AIRBORNE LIDAR DATA

    Directory of Open Access Journals (Sweden)

    D. Tang

    2016-06-01

    Full Text Available With the characteristics of LIDAR system, raw point clouds represent both terrain and non-terrain surface. In order to generate DTM, the paper introduces one improved filtering method based on the segment-based algorithms. The method generates segments by clustering points based on surface fitting and uses topological and geometric properties for classification. In the process, three major steps are involved. First, the whole datasets is split into several small overlapping tiles. For each tile, by removing wall and vegetation points, accurate segments are found. The segments from all tiles are assigned unique segment number. In the following step, topological descriptions for the segment distribution pattern and height jump between adjacent segments are identified in each tile. Based on the topology and geometry, segment-based filtering algorithm is performed for classification in each tile. Then, based on the spatial location of the segment in one tile, two confidence levels are assigned to the classified segments. The segments with low confidence level are because of losing geometric or topological information in one tile. Thus, a combination algorithm is generated to detect corresponding parts of incomplete segment from multiple tiles. Then another classification algorithm is performed for these segments. The result of these segments will have high confidence level. After that, all the segments in one tile have high confidence level of classification result. The final DTM will add all the terrain segments and avoid duplicate points. At the last of the paper, the experiment show the filtering result and be compared with the other classical filtering methods, the analysis proves the method has advantage in the precision of DTM. But because of the complicated algorithms, the processing speed is little slower, that is the future improvement which should been researched.

  5. a Segment-Based Approach for DTM Derivation of Airborne LIDAR Data

    Science.gov (United States)

    Tang, Dejin; Zhou, Xiaoming; Jiang, Jie; Li, Caiping

    2016-06-01

    With the characteristics of LIDAR system, raw point clouds represent both terrain and non-terrain surface. In order to generate DTM, the paper introduces one improved filtering method based on the segment-based algorithms. The method generates segments by clustering points based on surface fitting and uses topological and geometric properties for classification. In the process, three major steps are involved. First, the whole datasets is split into several small overlapping tiles. For each tile, by removing wall and vegetation points, accurate segments are found. The segments from all tiles are assigned unique segment number. In the following step, topological descriptions for the segment distribution pattern and height jump between adjacent segments are identified in each tile. Based on the topology and geometry, segment-based filtering algorithm is performed for classification in each tile. Then, based on the spatial location of the segment in one tile, two confidence levels are assigned to the classified segments. The segments with low confidence level are because of losing geometric or topological information in one tile. Thus, a combination algorithm is generated to detect corresponding parts of incomplete segment from multiple tiles. Then another classification algorithm is performed for these segments. The result of these segments will have high confidence level. After that, all the segments in one tile have high confidence level of classification result. The final DTM will add all the terrain segments and avoid duplicate points. At the last of the paper, the experiment show the filtering result and be compared with the other classical filtering methods, the analysis proves the method has advantage in the precision of DTM. But because of the complicated algorithms, the processing speed is little slower, that is the future improvement which should been researched.

  6. An Unsupervised Approach to Activity Recognition and Segmentation based on Object-Use Fingerprints

    DEFF Research Database (Denmark)

    Gu, Tao; Chen, Shaxun; Tao, Xianping

    2010-01-01

    machine learning techniques typically require an appropriate training process in which training data need to be labeled manually. In this paper, we propose an unsupervised approach based on object-use fingerprints to recognize activities without human labeling. We show how to build our activity models...... based on object-use fingerprints, which are sets of contrast patterns describing significant differences of object use between any two activity classes. We then propose a fingerprint-based algorithm to recognize activities. We also propose two heuristic algorithms based on object relevance to segment...... a trace and detect the boundary of any two adjacent activities. We develop a wearable RFID system and conduct a real-world trace collection done by seven volunteers in a smart home over a period of 2 weeks. We conduct comprehensive experimental evaluations and comparison study. The results show that our...

  7. The Market Concept of the 21st Century: a New Approach to Consumer Segmentation

    Directory of Open Access Journals (Sweden)

    Maria Igorevna Sokolova

    2016-01-01

    Full Text Available World economic development in the 21st century keeps tendencies and contradictions of the previous century. Economic growth in a number of the countries and, as a result, growth of consumption adjoins to an aggravation of global problems of the present. It not only ecology and climatic changes that undoubtedly worth the attention of world community, but also the aggravation of social problems. Among the last the question of poverty takes the central place. Poverty is a universal problem, in solution of which take part local authorities, the international organizations, commercial and noncommercial structures. It is intolerable to ignore a catastrophic situation in fight against this problem. It is necessary to look for ways of resolving it not only by using the existing methods, but also developing new approaches. One of the most significant tendencies in the sphere of fight against poverty is the development of the commercial enterprises working in the population segment with a low income level which by means of the activity help millions of people worldwide to get out of poverty. In other words, attraction of the commercial capital by an economic justification of profitability and prospects of investments into the companies working in the population segment with a low income level can be one of the methods allowing to solve effectively a poverty problem. This approach includes this population in economic activity, makes them by full-fledged participants of the market, which benefits to the creation of potential for economic growth and is a key step to getting out of poverty.

  8. Mixed-methods analytic approach for determining potential impacts of vessel noise on sperm whale click behavior.

    Science.gov (United States)

    Azzara, Alyson J; von Zharen, Wyndylyn M; Newcomb, Joal J

    2013-12-01

    The Gulf of Mexico is a center of marine activities from seismic exploration to shipping, drilling, platform installation, lightering, and construction, among others. This analysis explored whether sperm whales respond to the passage of vessels using changes in total number of clicks during vessel passages as a proxy for potential variation in behavior. The data for this analysis were collected in 2001 as part of a larger Littoral Acoustic Demonstration Center project using the Environmental Acoustics Recording System buoys. These buoys were bottom moored, autonomous, and self-recording systems consisting of an omni-directional hydrophone and instrument package. Data from 36 days of continuous acoustic monitoring were recorded at a sampling rate of 11.725 kHz, and produced reliable recordings from 5 Hz to ∼5.8 kHz. Multiple preparatory steps were executed including calibration of an automatic click detector. Results indicate a significant decrease (32%) in the number of clicks detected as a ship approached an area. There were also significantly fewer clicks detected after the vessel passed than before (23%).

  9. Integrating social marketing into sustainable resource management at Padre Island National Seashore: an attitude-based segmentation approach.

    Science.gov (United States)

    Lai, Po-Hsin; Sorice, Michael G; Nepal, Sanjay K; Cheng, Chia-Kuen

    2009-06-01

    High demand for outdoor recreation and increasing diversity in outdoor recreation participants have imposed a great challenge on the National Park Service (NPS), which is tasked with the mission to provide open access for quality outdoor recreation and maintain the ecological integrity of the park system. In addition to management practices of education and restrictions, building a sense of natural resource stewardship among visitors may also facilitate the NPS ability to react to this challenge. The purpose of our study is to suggest a segmentation approach that is built on the social marketing framework and aimed at influencing visitor behaviors to support conservation. Attitude toward natural resource management, an indicator of natural resource stewardship, is used as the basis for segmenting park visitors. This segmentation approach is examined based on a survey of 987 visitors to the Padre Island National Seashore (PAIS) in Texas in 2003. Results of the K-means cluster analysis identify three visitor segments: Conservation-Oriented, Development-Oriented, and Status Quo visitors. This segmentation solution is verified using respondents' socio-demographic backgrounds, use patterns, experience preferences, and attitudes toward a proposed regulation. Suggestions are provided to better target the three visitor segments and facilitate a sense of natural resource stewardship among them.

  10. A novel supervised approach for segmentation of lung parenchyma from chest CT for computer-aided diagnosis.

    Science.gov (United States)

    Darmanayagam, Shiloah Elizabeth; Harichandran, Khanna Nehemiah; Cyril, Sunil Retmin Raj; Arputharaj, Kannan

    2013-06-01

    Segmentation of lung parenchyma from the chest computed tomography is an important task in analysis of chest computed tomography for diagnosis of lung disorders. It is a challenging task especially in the presence of peripherally placed pathology bearing regions. In this work, we propose a segmentation approach to segment lung parenchyma from chest. The first step is to segment the lungs using iterative thresholding followed by morphological operations. If the two lungs are not separated, the lung junction and its neighborhood are identified and local thresholding is applied. The second step is to extract shape features of the two lungs. The third step is to use a multilayer feed forward neural network to determine if the segmented lung parenchyma is complete, based on the extracted features. The final step is to reconstruct the two lungs in case of incomplete segmentation, by exploiting the fact that in majority of the cases, at least one of the two lungs would have been segmented correctly by the first step. Hence, the complete lung is determined based on the shape and region properties and the incomplete lung is reconstructed by applying graphical methods, namely, reflection and translation. The proposed approach has been tested in a computer-aided diagnosis system for diagnosis of lung disorders, namely, bronchiectasis, tuberculosis, and pneumonia. An accuracy of 97.37 % has been achieved by the proposed approach whereas the conventional thresholding approach was unable to detect peripheral pathology-bearing regions. The results obtained prove to be better than that achieved using conventional thresholding and morphological operations.

  11. Statistical Permutation-based Artery Mapping (SPAM): a novel approach to evaluate imaging signals in the vessel wall.

    Science.gov (United States)

    Seifert, Robert; Scherzinger, Aaron; Kiefer, Friedemann; Hermann, Sven; Jiang, Xiaoyi; Schäfers, Michael A

    2017-05-26

    Cardiovascular diseases are the leading cause of death worldwide. A prominent cause of cardiovascular events is atherosclerosis, a chronic inflammation of the arterial wall that leads to the formation of so called atherosclerotic plaques. There is a strong clinical need to develop new, non-invasive vascular imaging techniques in order to identify high-risk plaques, which might escape detection using conventional methods based on the assessment of the luminal narrowing. In this context, molecular imaging strategies based on fluorescent tracers and fluorescence reflectance imaging (FRI) seem well suited to assess molecular and cellular activity. However, such an analysis demands a precise and standardized analysis method, which is orientated on reproducible anatomical landmarks, ensuring to compare equivalent regions across different subjects. We propose a novel method, Statistical Permutation-based Artery Mapping (SPAM). Our approach is especially useful for the understanding of complex and heterogeneous regional processes during the course of atherosclerosis. Our method involves three steps, which are (I) standardisation with an additional intensity normalization, (II) permutation testing, and (III) cluster-enhancement. Although permutation testing and cluster enhancement are already well-established in functional magnetic resonance imaging, to the best of our knowledge these strategies have so far not been applied in cardiovascular molecular imaging. We tested our method using FRI images of murine aortic vessels in order to find recurring patterns in atherosclerotic plaques across multiple subjects. We demonstrate that our pixel-wise and cluster-enhanced testing approach is feasible and useful to analyse tracer distributions in FRI data sets of aortic vessels. We expect our method to be a useful tool within the field of molecular imaging of atherosclerotic plaques since cluster-enhanced permutation testing is a powerful approach for finding significant differences

  12. Individual muscle segmentation in MR images: A 3D propagation through 2D non-linear registration approaches.

    Science.gov (United States)

    Ogier, Augustin; Sdika, Michael; Foure, Alexandre; Le Troter, Arnaud; Bendahan, David

    2017-07-01

    Manual and automated segmentation of individual muscles in magnetic resonance images have been recognized as challenging given the high variability of shapes between muscles and subjects and the discontinuity or lack of visible boundaries between muscles. In the present study, we proposed an original algorithm allowing a semi-automatic transversal propagation of manually-drawn masks. Our strategy was based on several ascending and descending non-linear registration approaches which is similar to the estimation of a Lagrangian trajectory applied to manual masks. Using several manually-segmented slices, we have evaluated our algorithm on the four muscles of the quadriceps femoris group. We mainly showed that our 3D propagated segmentation was very accurate with an averaged Dice similarity coefficient value higher than 0.91 for the minimal manual input of only two manually-segmented slices.

  13. A level set approach for left ventricle detection in CT images using shape segmentation and optical flow

    Science.gov (United States)

    Brieva, Jorge; Moya-Albor, Ernesto; Escalante-Ramírez, Boris

    2015-01-01

    The left ventricle (LV) segmentation plays an important role in a subsequent process for the functional analysis of the LV. Typical segmentation of the endocardium wall in the ventricle excludes papillary muscles which leads to an incorrect measure of the ejected volume in the LV. In this paper we present a new variational strategy using a 2D level set framework that includes a local term for enhancing the low contrast structures and a 2D shape model. The shape model in the level set method is propagated to all image sequences corresponding to the cardiac cycles through the optical flow approach using the Hermite transform. To evaluate our strategy we use the Dice index and the Hausdorff distance to compare the segmentation results with the manual segmentation carried out by the physician.

  14. A fast convex optimization approach to segmenting 3D scar tissue from delayed-enhancement cardiac MR images.

    Science.gov (United States)

    Rajchl, Martin; Yuan, Jing; White, James A; Nambakhsh, Cyrus; Ukwatta, Eranga; Li, Feng; Stirrat, John; Peters, Terry M

    2012-01-01

    We propose a novel multi-region segmentation approach through a partially-ordered ports (POP) model to segment myocardial scar tissue solely from 3D cardiac delayed-enhancement MR images (DE-MRI). The algorithm makes use of prior knowledge of anatomical spatial consistency and employs customized label ordering to constrain the segmentation without prior knowledge of geometric representation. The proposed method eliminates the need for regional constraint segmentations, thus reduces processing time and potential sources of error. We solve the proposed optimization problem by means of convex relaxation and introduce its duality: the hierarchical continuous max-flow (HMF) model, which amounts to an efficient numerical solver to the resulting convex optimization problem. Experiments are performed over ten DE-MRI data sets. The results are compared to a FWHM (full-width at half-maximum) method and the inter- and intra-operator variabilities assessed.

  15. A scaling and experimental approach for investigating in-vessel cooling

    Energy Technology Data Exchange (ETDEWEB)

    Henry, R.E. [Fauske & Associates, Inc., Burr Ridge, IL (United States)

    1997-02-01

    The TMI-2 accident experienced the relocation of a large quantity of core material to the lower plenum. The TMI-2 vessel investigation project concluded that approximately 20 metric tonnes of once molten fuel material drained into the RPV lower head. As a result, the lower head wall experienced a thermal transient that has been characterized as reaching temperatures as high as 1100{degrees}C, then a cooling transient with a rate of 10 to 100{degrees}C/min. Two mechanisms have been proposed as possible explanations for this cooling behavior. One is the ingression of water through core material as a result of interconnected cracks in the frozen debris and/or water ingression around the crust which is formed on internal structures (core supports and in-core instrumentation) in the lower head. The second focuses on the lack of adhesion of oxidic core debris to the RPV wall when the debris contacts the wall. Furthermore, the potential for strain of the RPV lower head when the wall is overheated could provide for a significant cooling path for water to ingress between the RPV and the frozen core material next to the wall. To examine these proposed mechanisms, a set of scaled experiments have been developed to examine the potential for cooling. These are performed in a scaled system in which the high temperature molten material is iron termite and the RPV wall is carbon steel. A termite mass of 40 kg is used and the simulated reactor vessels have water in the lower head at pressures up to 2.2 MPa. Furthermore, two different thicknesses of the vessel wall are examined with the thicker vessel having virtually no potential for material creep during the experiment and the thinner wall having the potential for substantial creep. Moreover, the experiment includes the option of having molten iron as the first material to drain into the RPV lower head or molten aluminum oxide being the only material that drains into the test configuration.

  16. A clustering approach to segmenting users of internet-based risk calculators.

    Science.gov (United States)

    Harle, C A; Downs, J S; Padman, R

    2011-01-01

    Risk calculators are widely available Internet applications that deliver quantitative health risk estimates to consumers. Although these tools are known to have varying effects on risk perceptions, little is known about who will be more likely to accept objective risk estimates. To identify clusters of online health consumers that help explain variation in individual improvement in risk perceptions from web-based quantitative disease risk information. A secondary analysis was performed on data collected in a field experiment that measured people's pre-diabetes risk perceptions before and after visiting a realistic health promotion website that provided quantitative risk information. K-means clustering was performed on numerous candidate variable sets, and the different segmentations were evaluated based on between-cluster variation in risk perception improvement. Variation in responses to risk information was best explained by clustering on pre-intervention absolute pre-diabetes risk perceptions and an objective estimate of personal risk. Members of a high-risk overestimater cluster showed large improvements in their risk perceptions, but clusters of both moderate-risk and high-risk underestimaters were much more muted in improving their optimistically biased perceptions. Cluster analysis provided a unique approach for segmenting health consumers and predicting their acceptance of quantitative disease risk information. These clusters suggest that health consumers were very responsive to good news, but tended not to incorporate bad news into their self-perceptions much. These findings help to quantify variation among online health consumers and may inform the targeted marketing of and improvements to risk communication tools on the Internet.

  17. [Incidences of C5 nerve palsy after multi-segmental cervical decompression through different approaches].

    Science.gov (United States)

    Meng, Hailiang; Fang, Xiangyi; Hao, Dingjun; Wang, Weidong

    2015-03-01

    To investigate the incidence of C5 nerve root palsy after multi-segmental cervical decompression through different approaches. This study was conducted among 375 patients undergoing multi-segmental cervical decompression in anterior corpectomy and fusion fixation, anterior cervical corpectomy and fusion fixation + posterior decompression and fusion fixation, posterior cervical laminectomy decompression, fusion and internal fixation, and posterior laminoplasty and fusion groups. The exclusion criteria included lack of follow-up data, spinal cord injury preventing preoperative or postoperative motor testing, or surgery not involving the C5 level. The incidence of C5 palsy was determined and the potential risk factors C5 palsy were analyzed including age, sex, revision surgery, preoperative weakness, diabetes, smoking, number of levels decompressed, and a history of previous upper extremity surgery. Of the 375 patients, 60 patients were excluded and the data of 315 patients were analyzed, including 146 women and 169 men with a mean age of 57.7 years (range 39-72 years). The overall incidence of C5 nerve palsy was 6.03% (19/315) in these patients; in the subgroups receiving different surgeries, the incidence was 8.62% in the cervical road laminectomy and fusion fixation group, 7.79% in the anterior cervical corpectomy and fusion fixation + posterior decompression and fusion and internal fixation, 4.68% in the anterior corpectomy and fusion fixation group, and 3.85% in the posterior laminoplasty and fusion group. No significant difference was found in the incidences among the subgroups, but men were more likely than women to develop cervical nerve root palsy (8.28% vs 3.42%, PC5 nerve palsy following postoperative cervical spinal decompression was 6.03% in our cohort. The incidence of C5 nerve palsy did not differ significantly following different cervical decompression surgeries, but the incidence was the highest in the posterior cervical laminectomy and fusion and

  18. An Original Approach for Quantification of Blood Vessels on the Whole Tumour Section

    Directory of Open Access Journals (Sweden)

    Nga Tran Kim

    2003-01-01

    Full Text Available Relative abundance of tumour angiogenesis has been shown to be of clinical relevance in cancers of various locations such as the ovary. Nevertheless, several problems are encountered when quantifying tumour microvessels: (i as many other tumour markers, vascularity pattern is often heterogeneous within the tumour mass and even within the same histological section. As a consequence, an adequate acquisition method must be developed for accurate field sampling. (ii Manual microvessel counting is long, tedious and subject to poor reproducibility. Introduction in routine practice requires a fast, reproducible and reliable automatic image processing. In this study we present an original procedure combining a slide scanner image acquisition and a fully automatic image analysis sequence. The slide scanner offers the advantage of recording an image of the whole histological section for subsequent automatic blood vessel detection and hot spot area location. Microvessel density and surface fraction were measured for the whole section as well as within hot spots. Different immunostaining methods were tested in order to optimise the procedure. Moreover, the method proposed was submitted to a quality control procedure, with reference to interactive identification of microvessels at scanner level. This experiment showed that 93 to 97% of blood vessels were detected, according to the staining protocol used. Colour figures can be viewed on http://www.esacp.org/acp/2003/25‐2/kim.htm.

  19. The 4-vessel Sampling Approach to Integrative Studies of Human Placental Physiology In Vivo.

    Science.gov (United States)

    Holme, Ane M; Holm, Maia B; Roland, Marie C P; Horne, Hildegunn; Michelsen, Trond M; Haugen, Guttorm; Henriksen, Tore

    2017-08-02

    The human placenta is highly inaccessible for research while still in utero. The current understanding of human placental physiology in vivo is therefore largely based on animal studies, despite the high diversity among species in placental anatomy, hemodynamics and duration of the pregnancy. The vast majority of human placenta studies are ex vivo perfusion studies or in vitro trophoblast studies. Although in vitro studies and animal models are essential, extrapolation of the results from such studies to the human placenta in vivo is uncertain. We aimed to study human placenta physiology in vivo at term, and present a detailed protocol of the method. Exploiting the intraabdominal access to the uterine vein just before the uterine incision during planned cesarean section, we collect blood samples from the incoming and outgoing vessels on the maternal and fetal sides of the placenta. When combining concentration measurements from blood samples with volume blood flow measurements, we are able to quantify placental and fetal uptake and release of any compound. Furthermore, placental tissue samples from the same mother-fetus pairs can provide measurements of transporter density and activity and other aspects of placental functions in vivo. Through this integrative use of the 4-vessel sampling method we are able to test some of the current concepts of placental nutrient transfer and metabolism in vivo, both in normal and pathological pregnancies. Furthermore, this method enables the identification of substances secreted by the placenta to the maternal circulation, which could be an important contribution to the search for biomarkers of placenta dysfunction.

  20. Digital Cellular Solid Pressure Vessels: A Novel Approach for Human Habitation in Space

    Science.gov (United States)

    Cellucci, Daniel; Jenett, Benjamin; Cheung, Kenneth C.

    2017-01-01

    It is widely assumed that human exploration beyond Earth's orbit will require vehicles capable of providing long duration habitats that simulate an Earth-like environment - consistent artificial gravity, breathable atmosphere, and sufficient living space- while requiring the minimum possible launch mass. This paper examines how the qualities of digital cellular solids - high-performance, repairability, reconfigurability, tunable mechanical response - allow the accomplishment of long-duration habitat objectives at a fraction of the mass required for traditional structural technologies. To illustrate the impact digital cellular solids could make as a replacement to conventional habitat subsystems, we compare recent proposed deep space habitat structural systems with a digital cellular solids pressure vessel design that consists of a carbon fiber reinforced polymer (CFRP) digital cellular solid cylindrical framework that is lined with an ultra-high molecular weight polyethylene (UHMWPE) skin. We use the analytical treatment of a linear specific modulus scaling cellular solid to find the minimum mass pressure vessel for a structure and find that, for equivalent habitable volume and appropriate safety factors, the use of digital cellular solids provides clear methods for producing structures that are not only repairable and reconfigurable, but also higher performance than their conventionally manufactured counterparts.

  1. A fourth order PDE based fuzzy c- means approach for segmentation of microscopic biopsy images in presence of Poisson noise for cancer detection.

    Science.gov (United States)

    Kumar, Rajesh; Srivastava, Subodh; Srivastava, Rajeev

    2017-07-01

    For cancer detection from microscopic biopsy images, image segmentation step used for segmentation of cells and nuclei play an important role. Accuracy of segmentation approach dominate the final results. Also the microscopic biopsy images have intrinsic Poisson noise and if it is present in the image the segmentation results may not be accurate. The objective is to propose an efficient fuzzy c-means based segmentation approach which can also handle the noise present in the image during the segmentation process itself i.e. noise removal and segmentation is combined in one step. To address the above issues, in this paper a fourth order partial differential equation (FPDE) based nonlinear filter adapted to Poisson noise with fuzzy c-means segmentation method is proposed. This approach is capable of effectively handling the segmentation problem of blocky artifacts while achieving good tradeoff between Poisson noise removals and edge preservation of the microscopic biopsy images during segmentation process for cancer detection from cells. The proposed approach is tested on breast cancer microscopic biopsy data set with region of interest (ROI) segmented ground truth images. The microscopic biopsy data set contains 31 benign and 27 malignant images of size 896 × 768. The region of interest selected ground truth of all 58 images are also available for this data set. Finally, the result obtained from proposed approach is compared with the results of popular segmentation algorithms; fuzzy c-means, color k-means, texture based segmentation, and total variation fuzzy c-means approaches. The experimental results shows that proposed approach is providing better results in terms of various performance measures such as Jaccard coefficient, dice index, Tanimoto coefficient, area under curve, accuracy, true positive rate, true negative rate, false positive rate, false negative rate, random index, global consistency error, and variance of information as compared to other

  2. Page 1 Multiferforate Plates in Xylem Vessels of Monocotyledonous ...

    Indian Academy of Sciences (India)

    Transverse section of a root of Alocasia indica showing 6 multiperforate plates in the vessel segments of the metaxylem. X46. FIG. 2.-A number of vessel segments from the root of Crinum asiaticum showing the two ends, x 15. FIG. 3.-Figure showing the arrangement of adjacent vessel segments with long oblique ends.

  3. An image-segmentation-based framework to detect oil slicks from moving vessels in the Southern African oceans using SAR imagery

    CSIR Research Space (South Africa)

    Mdakane, Lizwe W

    2017-06-01

    Full Text Available Oil slick events caused due to bilge leakage/dumps from ships and from other anthropogenic sources pose a threat to the aquatic ecosystem and need to be monitored on a regular basis. An automatic image-segmentation-based framework to detect oil...

  4. An approach to melodic segmentation and classification based on filtering with the Haar-wavelet

    DEFF Research Database (Denmark)

    Velarde, Gissel; Weyde, Tillman; Meredith, David

    2013-01-01

    Haar wavelet transform. The melodies are first segmented using local maxima or zero-crossings of ws. The segments of ws are then classified using the k–nearest neighbour algorithm with Euclidian and city-block distances. The method proves more effective than using unfiltered pitch signals and Gestalt...

  5. Understanding heterogeneity among elderly consumers: an evaluation of segmentation approaches in the functional food market.

    Science.gov (United States)

    van der Zanden, Lotte D T; van Kleef, Ellen; de Wijk, René A; van Trijp, Hans C M

    2014-06-01

    It is beneficial for both the public health community and the food industry to meet nutritional needs of elderly consumers through product formats that they want. The heterogeneity of the elderly market poses a challenge, however, and calls for market segmentation. Although many researchers have proposed ways to segment the elderly consumer population, the elderly food market has received surprisingly little attention in this respect. Therefore, the present paper reviewed eight potential segmentation bases on their appropriateness in the context of functional foods aimed at the elderly: cognitive age, life course, time perspective, demographics, general food beliefs, food choice motives, product attributes and benefits sought, and past purchase. Each of the segmentation bases had strengths as well as weaknesses regarding seven evaluation criteria. Given that both product design and communication are useful tools to increase the appeal of functional foods, we argue that elderly consumers in this market may best be segmented using a preference-based segmentation base that is predictive of behaviour (for example, attributes and benefits sought), combined with a characteristics-based segmentation base that describes consumer characteristics (for example, demographics). In the end, the effectiveness of (combinations of) segmentation bases for elderly consumers in the functional food market remains an empirical matter. We hope that the present review stimulates further empirical research that substantiates the ideas presented in this paper.

  6. A Market Segmentation Approach for Higher Education Based on Rational and Emotional Factors

    Science.gov (United States)

    Angulo, Fernando; Pergelova, Albena; Rialp, Josep

    2010-01-01

    Market segmentation is an important topic for higher education administrators and researchers. For segmenting the higher education market, we have to understand what factors are important for high school students in selecting a university. Extant literature has probed the importance of rational factors such as teaching staff, campus facilities,…

  7. AN APPROACH FOR ACTIVE SEGMENTATION OF UNCONSTRAINED HANDWRITTEN KOREAN STRINGS USING RUN-LENGTH CODE

    NARCIS (Netherlands)

    JeongSuk, J.; Kim, G.

    2004-01-01

    We propose an active handwritten Hangul segmentation method. A manageable structure based on Run-length code is defined in order to apply to preprocessing and segmentation. Also three fundamental candidate estimation functions are in- troduced to detect the clues on touching points, and the

  8. A Multi-Objective Decision Making Approach for Solving the Image Segmentation Fusion Problem.

    Science.gov (United States)

    Khelifi, Lazhar; Mignotte, Max

    2017-08-01

    Image segmentation fusion is defined as the set of methods which aim at merging several image segmentations, in a manner that takes full advantage of the complementarity of each one. Previous relevant researches in this field have been impeded by the difficulty in identifying an appropriate single segmentation fusion criterion, providing the best possible, i.e., the more informative, result of fusion. In this paper, we propose a new model of image segmentation fusion based on multi-objective optimization which can mitigate this problem, to obtain a final improved result of segmentation. Our fusion framework incorporates the dominance concept in order to efficiently combine and optimize two complementary segmentation criteria, namely, the global consistency error and the F-measure (precision-recall) criterion. To this end, we present a hierarchical and efficient way to optimize the multi-objective consensus energy function related to this fusion model, which exploits a simple and deterministic iterative relaxation strategy combining the different image segments. This step is followed by a decision making task based on the so-called "technique for order performance by similarity to ideal solution". Results obtained on two publicly available databases with manual ground truth segmentations clearly show that our multi-objective energy-based model gives better results than the classical mono-objective one.

  9. Statistics-based segmentation using a continuous-scale naive Bayes approach

    DEFF Research Database (Denmark)

    Laursen, Morten Stigaard; Midtiby, Henrik Skov; Kruger, Norbert

    2014-01-01

    Segmentation is a popular preprocessing stage in the field of machine vision. In agricultural applications it can be used to distinguish between living plant material and soil in images. The normalized difference vegetation index (NDVI) and excess green (ExG) color features are often used...... segmentation over the normalized vegetation difference index and excess green. The inputs to this color feature are the R, G, B, and near-infrared color wells, their chromaticities, and NDVI, ExG, and excess red. We apply the developed technique to a dataset consisting of 20 manually segmented images captured...... in the segmentation of images with multiple color channels. In this paper, a Bayesian method is used to combine existing color features into a common color feature. This feature is then used to segment images into separate regions containing vegetation and soil. The common color feature produces an improved...

  10. A fully automated approach to prostate biopsy segmentation based on level-set and mean filtering

    Directory of Open Access Journals (Sweden)

    Juan Vidal

    2011-01-01

    Full Text Available With modern automated microscopes and digital cameras, pathologists no longer have to examine samples looking through microscope binoculars. Instead, the slide is digitized to an image, which can then be examined on a screen. This creates the possibility for computers to analyze the image. In this work, a fully automated approach to region of interest (ROI segmentation in prostate biopsy images is proposed. This will allow the pathologists to focus on the most important areas of the image. The method proposed is based on level-set and mean filtering techniques for lumen centered expansion and cell density localization respectively. The novelty of the technique lies in the ability to detect complete ROIs, where a ROI is composed by the conjunction of three different structures, that is, lumen, cytoplasm, and cells, as well as regions with a high density of cells. The method is capable of dealing with full biopsies digitized at different magnifications. In this paper, results are shown with a set of 100 H and E slides, digitized at 5×, and ranging from 12 MB to 500 MB. The tests carried out show an average specificity above 99% across the board and average sensitivities of 95% and 80%, respectively, for the lumen centered expansion and cell density localization. The algorithms were also tested with images at 10× magnification (up to 1228 MB obtaining similar results.

  11. A Multiatlas Approach for Segmenting Subcortical Brain Structures using Local Patch Distance

    Directory of Open Access Journals (Sweden)

    Neela RAMAMOORTHI

    2015-12-01

    Full Text Available In the diagnosis and treatment of various diseases, often segmenting the brain structures from MRI data is the key step. Since there are larger variations in the anatomical structures of the brain, segmentation becomes a crucial process. Using only the intensity information is not enough to segment structures since two or more structures may share the same tissues. Recently, the use of multiple pre-labeled images called atlases or templates are used in the process of segmentation of image data. Both single atlas and multiple atlases can be used. However, using multiple atlases in the segmentation process proves a dominant method in segmenting brain structures with challenging and overlapping structures. In this paper, we propose two multi atlas segmentation methods: Local Patch Distance Segmentation (LPDS and Weighted Local Patch Distance Segmentation (WLPDS. These methods use local patch distance in the label fusion step. LPDS uses local patch distance to find the best patch match for label propagation. WLPDS uses local patch distance to calculate local weights. The brain MRI images from the MICCAI 2012 segmentation challenge are chosen for experimental purposes. These datasets are publicly available and can be downloaded from MIDAS. The proposed techniques are compared with existing fusion methods such as majority voting and weighted majority voting using the similarity measures such as Dice overlap (DC, Jaccard coefficient (JC and Kappa statistics. For 20 test data sets, LPDS gives DICE=0.95±0.05, JACCARD=0.91±0.04 and KAPPA=0.94±0.07. WLPDS gives DICE=0.98±0.02, JACCARD=0.92±0.03 and KAPPA=0.95±0.04.

  12. Genome-wide identification of conserved intronic non-coding sequences using a Bayesian segmentation approach.

    Science.gov (United States)

    Algama, Manjula; Tasker, Edward; Williams, Caitlin; Parslow, Adam C; Bryson-Richardson, Robert J; Keith, Jonathan M

    2017-03-27

    Computational identification of non-coding RNAs (ncRNAs) is a challenging problem. We describe a genome-wide analysis using Bayesian segmentation to identify intronic elements highly conserved between three evolutionarily distant vertebrate species: human, mouse and zebrafish. We investigate the extent to which these elements include ncRNAs (or conserved domains of ncRNAs) and regulatory sequences. We identified 655 deeply conserved intronic sequences in a genome-wide analysis. We also performed a pathway-focussed analysis on genes involved in muscle development, detecting 27 intronic elements, of which 22 were not detected in the genome-wide analysis. At least 87% of the genome-wide and 70% of the pathway-focussed elements have existing annotations indicative of conserved RNA secondary structure. The expression of 26 of the pathway-focused elements was examined using RT-PCR, providing confirmation that they include expressed ncRNAs. Consistent with previous studies, these elements are significantly over-represented in the introns of transcription factors. This study demonstrates a novel, highly effective, Bayesian approach to identifying conserved non-coding sequences. Our results complement previous findings that these sequences are enriched in transcription factors. However, in contrast to previous studies which suggest the majority of conserved sequences are regulatory factor binding sites, the majority of conserved sequences identified using our approach contain evidence of conserved RNA secondary structures, and our laboratory results suggest most are expressed. Functional roles at DNA and RNA levels are not mutually exclusive, and many of our elements possess evidence of both. Moreover, ncRNAs play roles in transcriptional and post-transcriptional regulation, and this may contribute to the over-representation of these elements in introns of transcription factors. We attribute the higher sensitivity of the pathway-focussed analysis compared to the genome

  13. Risks in surgery-first orthognathic approach: complications of segmental osteotomies of the jaws. A systematic review.

    Science.gov (United States)

    Pelo, S; Saponaro, G; Patini, R; Staderini, E; Giordano, A; Gasparini, G; Garagiola, U; Azzuni, C; Cordaro, M; Foresta, E; Moro, A

    2017-01-01

    To date, no systematic review has been undertaken to identify the complications of segmental osteotomies. The aim of the present systematic review was to analyze the type and incidence of complications of segmental osteotomies, as well as the time of subjective and/or clinical onset of the intra- and post-operative problems. A search was conducted in two electronic databases (MEDLINE - Pubmed database and Scopus) for articles published in English between 1 January 2000 and 30 August 2015; only human studies were selected. Case report studies were excluded. Two independent researchers selected the studies and extracted the data. Two studies were selected, four additional publications were recovered from the bibliography search of the selected articles, and one additional article was added through a manual search. The results of this systematic review demonstrate a relatively low rate of complications in segmental osteotomies, suggesting this surgical approach is safe and reliable in routine orthognathic surgery. Due to the small number of studies included in this systematic review, the rate of complication related to surgery first approach may be slightly higher than those associated with traditional orthognathic surgery, since the rate of complications of segmental osteotomies must be added to the complication rate of basal osteotomies. A surgery-first approach could be considered riskier than a traditional one, but further studies that include a greater number of subjects should be conducted to confirm these findings.

  14. Tissue engineering human small-caliber autologous vessels using a xenogenous decellularized connective tissue matrix approach: preclinical comparative biomechanical studies.

    Science.gov (United States)

    Heine, Jörg; Schmiedl, Andreas; Cebotari, Serghei; Karck, Matthias; Mertsching, Heike; Haverich, Axel; Kallenbach, Klaus

    2011-10-01

    Suggesting that bioartificial vascular scaffolds cannot but tissue-engineered vessels can withstand biomechanical stress, we developed in vitro methods for preclinical biological material testings. The aim of the study was to evaluate the influence of revitalization of xenogenous scaffolds on biomechanical stability of tissue-engineered vessels. For measurement of radial distensibility, a salt-solution inflation method was used. The longitudinal tensile strength test (DIN 50145) was applied on bone-shaped specimen: tensile/tear strength (SigmaB/R), elongation at maximum yield stress/rupture (DeltaB/R), and modulus of elasticity were determined of native (NAs; n = 6), decellularized (DAs; n = 6), and decellularized carotid arteries reseeded with human vascular smooth muscle cells and human vascular endothelial cells (RAs; n = 7). Radial distensibility of DAs was significantly lower (113%) than for NAs (135%) (P caliber vascular graft testing, this study proved that revitalization of decellularized connective tissue scaffolds led to vascular graft stability able to withstand biomechanical stress mimicking the human circulation. This tissue engineering approach provides a sufficiently stable autologized graft. © 2011, Copyright the Authors. Artificial Organs © 2011, International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

  15. A Hybrid Hierarchical Approach for Brain Tissue Segmentation by Combining Brain Atlas and Least Square Support Vector Machine

    Science.gov (United States)

    Kasiri, Keyvan; Kazemi, Kamran; Dehghani, Mohammad Javad; Helfroush, Mohammad Sadegh

    2013-01-01

    In this paper, we present a new semi-automatic brain tissue segmentation method based on a hybrid hierarchical approach that combines a brain atlas as a priori information and a least-square support vector machine (LS-SVM). The method consists of three steps. In the first two steps, the skull is removed and the cerebrospinal fluid (CSF) is extracted. These two steps are performed using the toolbox FMRIB's automated segmentation tool integrated in the FSL software (FSL-FAST) developed in Oxford Centre for functional MRI of the brain (FMRIB). Then, in the third step, the LS-SVM is used to segment grey matter (GM) and white matter (WM). The training samples for LS-SVM are selected from the registered brain atlas. The voxel intensities and spatial positions are selected as the two feature groups for training and test. SVM as a powerful discriminator is able to handle nonlinear classification problems; however, it cannot provide posterior probability. Thus, we use a sigmoid function to map the SVM output into probabilities. The proposed method is used to segment CSF, GM and WM from the simulated magnetic resonance imaging (MRI) using Brainweb MRI simulator and real data provided by Internet Brain Segmentation Repository. The semi-automatically segmented brain tissues were evaluated by comparing to the corresponding ground truth. The Dice and Jaccard similarity coefficients, sensitivity and specificity were calculated for the quantitative validation of the results. The quantitative results show that the proposed method segments brain tissues accurately with respect to corresponding ground truth. PMID:24696800

  16. A Combined Random Forests and Active Contour Model Approach for Fully Automatic Segmentation of the Left Atrium in Volumetric MRI

    Directory of Open Access Journals (Sweden)

    Chao Ma

    2017-01-01

    Full Text Available Segmentation of the left atrium (LA from cardiac magnetic resonance imaging (MRI datasets is of great importance for image guided atrial fibrillation ablation, LA fibrosis quantification, and cardiac biophysical modelling. However, automated LA segmentation from cardiac MRI is challenging due to limited image resolution, considerable variability in anatomical structures across subjects, and dynamic motion of the heart. In this work, we propose a combined random forests (RFs and active contour model (ACM approach for fully automatic segmentation of the LA from cardiac volumetric MRI. Specifically, we employ the RFs within an autocontext scheme to effectively integrate contextual and appearance information from multisource images together for LA shape inferring. The inferred shape is then incorporated into a volume-scalable ACM for further improving the segmentation accuracy. We validated the proposed method on the cardiac volumetric MRI datasets from the STACOM 2013 and HVSMR 2016 databases and showed that it outperforms other latest automated LA segmentation methods. Validation metrics, average Dice coefficient (DC and average surface-to-surface distance (S2S, were computed as 0.9227±0.0598 and 1.14±1.205 mm, versus those of 0.6222–0.878 and 1.34–8.72 mm, obtained by other methods, respectively.

  17. Wireless capsule endoscopy video segmentation using an unsupervised learning approach based on probabilistic latent semantic analysis with scale invariant features.

    Science.gov (United States)

    Shen, Yao; Guturu, Parthasarathy Partha; Buckles, Bill P

    2012-01-01

    Since wireless capsule endoscopy (WCE) is a novel technology for recording the videos of the digestive tract of a patient, the problem of segmenting the WCE video of the digestive tract into subvideos corresponding to the entrance, stomach, small intestine, and large intestine regions is not well addressed in the literature. A selected few papers addressing this problem follow supervised leaning approaches that presume availability of a large database of correctly labeled training samples. Considering the difficulties in procuring sizable WCE training data sets needed for achieving high classification accuracy, we introduce in this paper an unsupervised learning approach that employs Scale Invariant Feature Transform (SIFT) for extraction of local image features and the probabilistic latent semantic analysis (pLSA) model used in the linguistic content analysis for data clustering. Results of experimentation indicate that this method compares well in classification accuracy with the state-of-the-art supervised classification approaches to WCE video segmentation.

  18. Segmented Assimilation: An Approach to Studying Acculturation and Obesity Among Latino Adults in the United States.

    Science.gov (United States)

    Flórez, Karen R; Abraído-Lanza, Ana

    Segmented assimilation theory posits that immigrants experience distinct paths of assimilation. Using cluster analysis and data from the National Latino and Asian American Survey, this study sought to apply this theory in relation to obesity among Latinos. Four clusters emerged: a "second-generation classic," a "third-generation classic," an "underclass," and a "segmented assimilation" pattern. In analyses controlling for sociodemographic confounders (eg, age), second-generation classic individuals had higher odds of obesity (odds ratio = 2.70, 95% confidence interval = 1.47-4.93) relative to the segmented pattern. Similarly, third-generation classic individuals had higher odds of obesity (odds ratio = 3.23, 95% confidence interval = 1.74-6.01) compared with segmented assimilation individuals.

  19. Muscle gap approach under a minimally invasive channel technique for treating long segmental lumbar spinal stenosis: A retrospective study.

    Science.gov (United States)

    Bin, Yang; De Cheng, Wang; Wei, Wang Zong; Hui, Li

    2017-08-01

    This study aimed to compare the efficacy of muscle gap approach under a minimally invasive channel surgical technique with the traditional median approach.In the Orthopedics Department of Traditional Chinese and Western Medicine Hospital, Tongzhou District, Beijing, 68 cases of lumbar spinal canal stenosis underwent surgery using the muscle gap approach under a minimally invasive channel technique and a median approach between September 2013 and February 2016. Both approaches adopted lumbar spinal canal decompression, intervertebral disk removal, cage implantation, and pedicle screw fixation. The operation time, bleeding volume, postoperative drainage volume, and preoperative and postoperative visual analog scale (VAS) score and Japanese Orthopedics Association score (JOA) were compared between the 2 groups.All patients were followed up for more than 1 year. No significant difference between the 2 groups was found with respect to age, gender, surgical segments. No diversity was noted in the operation time, intraoperative bleeding volume, preoperative and 1 month after the operation VAS score, preoperative and 1 month after the operation JOA score, and 6 months after the operation JOA score between 2 groups (P > .05). The amount of postoperative wound drainage (260.90 ± 160 mL vs 447.80 ± 183.60 mL, P gap approach group than in the median approach group (P gap approach under a minimally invasive channel group, the average drainage volume was reduced by 187 mL, and the average VAS score 6 months after the operation was reduced by an average of 0.48.The muscle gap approach under a minimally invasive channel technique is a feasible method to treat long segmental lumbar spinal canal stenosis. It retains the integrity of the posterior spine complex to the greatest extent, so as to reduce the adjacent spinal segmental degeneration and soft tissue trauma. Satisfactory short-term and long-term clinical results were obtained.

  20. Triple vessel percutaneous coronary intervention in a patient with situs inversus dextrocardia using a transradial approach.

    Science.gov (United States)

    Potdar, Anil; Sapkal, Ganeshrao; Sharma, Satyavan

    2016-09-01

    Situs inversus dextrocardia is a challenging situation for an interventional cardiologist. This report presents a rare case where multivessel percutaneous coronary intervention was performed in a single sitting using transradial approach. The challenges encountered in the procedure and clues to successful outcome are discussed. Copyright © 2016 Cardiological Society of India. Published by Elsevier B.V. All rights reserved.

  1. Analysis of Speeding Behaviour During Approaching the U-Turn Facility Road Segment Based On Driving Simulation Test

    Directory of Open Access Journals (Sweden)

    Nemmang M. S.

    2017-01-01

    Full Text Available The main purose of this study is to analysis the speeding behavior during approaching the U-turn facility road segment based on driving simulation test. In previous studies, it has been shown that speeding behavior is a complex problem that requires a full understanding of drivers’ attitudes and beliefs. Such understanding is needed to improve the speeding behavior of drivers that comes from the effective design and interventions. Therefore, this study will analyse the speeding behavior in approaching the U-turn facility as a key variable in this study which may affect the collision result. Totally 50 participants were recruited in this experiments based on driving simulator. The scenarios and road environment in the driving simulator were based on site location at FT050 Jalan Batu Pahat – Kluang, Johor. Results shows significant increase in speed of up to 40.01% more than the speed limit at the approaching the Uturn facility road segment. The paper concluded that speeding behavior during approaching the U-turn facility road segment based on driving simulation test will trigger significant increasing of speed.

  2. Safety of Shipping when Navigating on the PS Class Container Vessel “Emma Maersk” While Approaching DCT Terminal in Gda?sk Port Pó?nocny

    Directory of Open Access Journals (Sweden)

    Grzegorz Rutkowski

    2016-09-01

    Full Text Available In this paper author presents the methods that can be used for estimating the safety of shipping (navigational risk in the restricted sea areas of the Gulf of Gdansk by means of a three-dimensional model of ship’s domain specified for the PS Class container vessels “Emma Maersk”. The essence of the method suggested in the thesis is the systematic approach to a sea vessel operation in the aspect of estimating its safety while approaching DCT terminal in Gda?sk Port Pó?nocny in the divergent exterior conditions.

  3. Semi-automated segmentation of neuroblastoma nuclei using the gradient energy tensor: a user driven approach

    Science.gov (United States)

    Kromp, Florian; Taschner-Mandl, Sabine; Schwarz, Magdalena; Blaha, Johanna; Weiss, Tamara; Ambros, Peter F.; Reiter, Michael

    2015-02-01

    We propose a user-driven method for the segmentation of neuroblastoma nuclei in microscopic fluorescence images involving the gradient energy tensor. Multispectral fluorescence images contain intensity and spatial information about antigene expression, fluorescence in situ hybridization (FISH) signals and nucleus morphology. The latter serves as basis for the detection of single cells and the calculation of shape features, which are used to validate the segmentation and to reject false detections. Accurate segmentation is difficult due to varying staining intensities and aggregated cells. It requires several (meta-) parameters, which have a strong influence on the segmentation results and have to be selected carefully for each sample (or group of similar samples) by user interactions. Because our method is designed for clinicians and biologists, who may have only limited image processing background, an interactive parameter selection step allows the implicit tuning of parameter values. With this simple but intuitive method, segmentation results with high precision for a large number of cells can be achieved by minimal user interaction. The strategy was validated on handsegmented datasets of three neuroblastoma cell lines.

  4. SegAuth: A Segment-based Approach to Behavioral Biometric Authentication.

    Science.gov (United States)

    Li, Yanyan; Xie, Mengjun; Bian, Jiang

    2016-10-01

    Many studies have been conducted to apply behavioral biometric authentication on/with mobile devices and they have shown promising results. However, the concern about the verification accuracy of behavioral biometrics is still common given the dynamic nature of behavioral biometrics. In this paper, we address the accuracy concern from a new perspective-behavior segments, that is, segments of a gesture instead of the whole gesture as the basic building block for behavioral biometric authentication. With this unique perspective, we propose a new behavioral biometric authentication method called SegAuth, which can be applied to various gesture or motion based authentication scenarios. SegAuth can achieve high accuracy by focusing on each user's distinctive gesture segments that frequently appear across his or her gestures. In SegAuth, a time series derived from a gesture/motion is first partitioned into segments and then transformed into a set of string tokens in which the tokens representing distinctive, repetitive segments are associated with higher genuine probabilities than those tokens that are common across users. An overall genuine score calculated from all the tokens derived from a gesture is used to determine the user's authenticity. We have assessed the effectiveness of SegAuth using 4 different datasets. Our experimental results demonstrate that SegAuth can achieve higher accuracy consistently than existing popular methods on the evaluation datasets.

  5. Reducing consumption of confectionery foods: A post-hoc segmentation analysis using a social cognition approach.

    Science.gov (United States)

    Naughton, Paul; McCarthy, Mary; McCarthy, Sinéad

    2017-10-01

    Considering confectionary consumption behaviour this cross-sectional study used social cognition variables to identify distinct segments in terms of their motivation and efforts to decrease their consumption of such foods with the aim of informing targeted social marketing campaigns. Using Latent Class analysis on a sample of 500 adults four segments were identified: unmotivated, triers, successful actors, and thrivers. The unmotivated and triers segments reported low levels of perceived need and perceived behavioural control (PBC) in addition to high levels of habit and hedonic hunger with regards their consumption of confectionery foods. Being a younger adult was associated with higher odds of being in the unmotivated and triers segments and being female was associated with higher odds of being in the triers and successful actors segments. The findings indicate that in the absence of strong commitment to eating low amounts of confectionery foods (i.e. perceived need) people will continue to overconsume free sugars regardless of motivation to change. It is therefore necessary to identify relevant messages or 'triggers' related to sugar consumption that resonate with young adults in particular. For those motivated to change, counteracting unhealthy eating habits and the effects of hedonic hunger may necessitate changes to food environments in order to make the healthy choice more appealing and accessible. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. A New User Dependent Iris Recognition System Based on an Area Preserving Pointwise Level Set Segmentation Approach

    Directory of Open Access Journals (Sweden)

    Nakissa Barzegar

    2009-01-01

    Full Text Available This paper presents a new user dependent approach in iris recognition systems. In the proposed method, consistent bits of iris code are calculated, based on the user specifications, using the user's mask. Another contribution of our work is in the iris segmentation phase, where a new pointwise level set approach with area preserving has been used for determining inner and outer iris boundaries, both exclusively performed in one step. Thanks to the special properties of this segmentation technique, there is no constraint about angles of head tilt. Furthermore, we showed that this algorithm is robust in noisy situations and can locate irises which are partly occluded by eyelid and eyelashes. Experimental results, on three renowned iris databases (CASIAIrisV3, Bath, and Ubiris, show that our method outperforms some of the existing methods, both in terms of accuracy and response time.

  7. An adaptive approach for the segmentation and extraction of planar and linear/cylindrical features from laser scanning data

    Science.gov (United States)

    Lari, Zahra; Habib, Ayman

    2014-07-01

    Laser scanning systems have been established as leading tools for the collection of high density three-dimensional data over physical surfaces. The collected point cloud does not provide semantic information about the characteristics of the scanned surfaces. Therefore, different processing techniques have been developed for the extraction of useful information from this data which could be applied for diverse civil, industrial, and military applications. Planar and linear/cylindrical features are among the most important primitive information to be extracted from laser scanning data, especially those collected in urban areas. This paper introduces a new approach for the identification, parameterization, and segmentation of these features from laser scanning data while considering the internal characteristics of the utilized point cloud - i.e., local point density variation and noise level in the dataset. In the first step of this approach, a Principal Component Analysis of the local neighborhood of individual points is implemented to identify the points that belong to planar and linear/cylindrical features and select their appropriate representation model. For the detected planar features, the segmentation attributes are then computed through an adaptive cylinder neighborhood definition. Two clustering approaches are then introduced to segment and extract individual planar features in the reconstructed parameter domain. For the linear/cylindrical features, their directional and positional parameters are utilized as the segmentation attributes. A sequential clustering technique is proposed to isolate the points which belong to individual linear/cylindrical features through directional and positional attribute subspaces. Experimental results from simulated and real datasets demonstrate the feasibility of the proposed approach for the extraction of planar and linear/cylindrical features from laser scanning data.

  8. Different approaches to synovial membrane volume determination by magnetic resonance imaging: manual versus automated segmentation

    DEFF Research Database (Denmark)

    Østergaard, Mikkel

    1997-01-01

    or synovial membrane volume, e.g. no systematic errors were found. The inter-MRI variation, evaluated in three knees and three wrists, was higher than by manual segmentation, particularly due to sensitivity to malalignment artefacts. Examination of test objects proved the high accuracy of the general...... methodology for volume determinations (maximal error 6.3%). Preceded by the determination of reproducibility and the optimal threshold at the available MR unit, automated 'threshold' segmentation appears to be acceptable when changes rather than absolute values of synovial membrane volumes are most important...

  9. Definitive guiding flange prosthesis: A definitive approach in segmental mandibulectomy defect

    Directory of Open Access Journals (Sweden)

    Sumanth Babu

    2016-01-01

    Full Text Available Mandibular discontinuity defects following a segmental mandibulectomy defects present a major challenge to the rehabilitation team. With no immediate intervention to rehabilitate the patient, definitive mandibular guidance prostheses with a metal guiding flange and acrylic teeth on the resected side can be used successfully to stabilize the occlusion and correct the deviation. The present case report describes the prosthodontic rehabilitation of a patient with a segmental mandibulectomy using a mandibular prosthesis with a metal guide flange and a maxillary stabilizing metal framework.

  10. Homogenization of atmospheric pressure time series recorded at VLBI stations using a segmentation LASSO approach

    Science.gov (United States)

    Balidakis, Kyriakos; Heinkelmann, Robert; Lu, Cuixian; Soja, Benedikt; Karbon, Maria; Nilsson, Tobias; Glaser, Susanne; Andres Mora-Diaz, Julian; Anderson, James; Liu, Li; Raposo-Pulido, Virginia; Xu, Minghui; Schuh, Harald

    2015-04-01

    Time series of meteorological parameters recorded at VLBI (Very Long Baseline Interferometry) observatories allow us to realistically model and consequently to eliminate the atmosphere-induced effects in the VLBI products to a large extent. Nevertheless, this advantage of VLBI is not fully exploited since such information is contaminated with inconsistencies, such as uncertainties regarding the calibration and location of the meteorological sensors, outliers, missing data points, and breaks. It has been shown that such inconsistencies in meteorological data used for VLBI data analysis impose problems in the geodetic products (e.g vertical site position) and result in mistakes in geophysical interpretation. The aim of the procedure followed here is to optimally model the tropospheric delay and bending effects that are still the main sources of error in VLBI data analysis. In this study, the meteorological data recorded with sensors mounted in the vicinity of VLBI stations have been homogenized spanning the period from 1979 until today. In order to meet this objective, inhomogeneities were detected and adjusted using test results and metadata. Some of the approaches employed include Alexandersson's Standard Normal Homogeneity Test and an iterative procedure, of which the segmentation part is based on a dynamic programming algorithm and the functional part on a LASSO (Least Absolute Shrinkage and Selection Operator) estimator procedure. For the provision of reference time series that are necessary to apply the aforementioned methods, ECMWF's (European Centre for Medium-Range Weather Forecasts) ERA-Interim reanalysis surface data were employed. Special care was taken regarding the datum definition of this model. Due to the significant height difference between the VLBI antenna's reference point and the elevation included in geopotential fields of the specific numerical weather models, a hypsometric adjustment is applied using the absolute pressure level from the WMO

  11. Remote Sensing Image Fusion at the Segment Level Using a Spatially-Weighted Approach: Applications for Land Cover Spectral Analysis and Mapping

    Directory of Open Access Journals (Sweden)

    Brian Johnson

    2015-01-01

    Full Text Available Segment-level image fusion involves segmenting a higher spatial resolution (HSR image to derive boundaries of land cover objects, and then extracting additional descriptors of image segments (polygons from a lower spatial resolution (LSR image. In past research, an unweighted segment-level fusion (USF approach, which extracts information from a resampled LSR image, resulted in more accurate land cover classification than the use of HSR imagery alone. However, simply fusing the LSR image with segment polygons may lead to significant errors due to the high level of noise in pixels along the segment boundaries (i.e., pixels containing multiple land cover types. To mitigate this, a spatially-weighted segment-level fusion (SWSF method was proposed for extracting descriptors (mean spectral values of segments from LSR images. SWSF reduces the weights of LSR pixels located on or near segment boundaries to reduce errors in the fusion process. Compared to the USF approach, SWSF extracted more accurate spectral properties of land cover objects when the ratio of the LSR image resolution to the HSR image resolution was greater than 2:1, and SWSF was also shown to increase classification accuracy. SWSF can be used to fuse any type of imagery at the segment level since it is insensitive to spectral differences between the LSR and HSR images (e.g., different spectral ranges of the images or different image acquisition dates.

  12. An Automated Approach for Kidney Segmentation in Three-Dimensional Ultrasound Images.

    Science.gov (United States)

    Marsousi, Mahdi; Plataniotis, Konstantinos N; Stergiopoulos, Stergios

    2017-07-01

    Automated segmentation of kidneys in three-dimensional (3-D) abdominal ultrasound volumes is a task of paramount importance in automated diagnosis of abdominal trauma. However, ultrasound speckle noise, low-contrast boundaries, partial kidney occlusion, and probe misalignment restrict the utility of the solution, especially when it is used in emergency rooms and Focused Assessment with Sonography Trauma applications. This paper introduces a systematic and cost-effective method capable of detecting and segmenting the kidney's shape in acquired 3-D ultrasound volumes, using off-line training datasets. This paper offers a new shape model representation, called the complex-valued implicit shape model, to generate a 3-D kidney shape model by combining prior knowledge of training shapes and anatomical knowledge. We apply shape-to-volume registration, based on a new similarity metric, to detect the kidney shape by fitting the 3-D shape model on 3-D ultrasound volumes. Upon kidney detection, the fitted shape model is used to initialize and evolve a new level-set function, called complex-valued rational level-set with shape prior, to segment the kidney's shape. Experimentation using both simulated and actual ultrasound volumes indicate that the proposed solution provides a better performance over the state-of-the-art volumetric ultrasound segmentation methods.

  13. Optimisation of the formulation of a bubble bath by a chemometric approach market segmentation and optimisation.

    Science.gov (United States)

    Marengo, Emilio; Robotti, Elisa; Gennaro, Maria Carla; Bertetto, Mariella

    2003-03-01

    The optimisation of the formulation of a commercial bubble bath was performed by chemometric analysis of Panel Tests results. A first Panel Test was performed to choose the best essence, among four proposed to the consumers; the best essence chosen was used in the revised commercial bubble bath. Afterwards, the effect of changing the amount of four components (the amount of primary surfactant, the essence, the hydratant and the colouring agent) of the bubble bath was studied by a fractional factorial design. The segmentation of the bubble bath market was performed by a second Panel Test, in which the consumers were requested to evaluate the samples coming from the experimental design. The results were then treated by Principal Component Analysis. The market had two segments: people preferring a product with a rich formulation and people preferring a poor product. The final target, i.e. the optimisation of the formulation for each segment, was obtained by the calculation of regression models relating the subjective evaluations given by the Panel and the compositions of the samples. The regression models allowed to identify the best formulations for the two segments ofthe market.

  14. Segmentation of the pectoral muscle in breast MRI using atlas-based approaches

    NARCIS (Netherlands)

    Gubern-Mérida, A.; Kallenberg, M.; Martí, R.; Karssemeijer, N.

    2012-01-01

    Pectoral muscle segmentation is an important step in automatic breast image analysis methods and crucial for multi-modal image registration. In breast MRI, accurate delineation of the pectoral is important for volumetric breast density estimation and for pharmacokinetic analysis of dynamic contrast

  15. Association between proximal internal carotid artery steno-occlusive disease and diffuse wall thickening in its petrous segment: a magnetic resonance vessel wall imaging study

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Xiaoyi; Li, Dongye [Capital Medical University and Beijing Institute for Brain Disorders, Center for Brain Disorders Research, Beijing (China); Tsinghua University School of Medicine, Center for Biomedical Imaging Research, Department of Biomedical Engineering, Beijing (China); Zhao, Huilin [Shanghai Jiao Tong University, Department of Radiology, Renji Hospital, School of Medicine, Shanghai (China); Chen, Zhensen; Qiao, Huiyu; He, Le; Li, Rui [Tsinghua University School of Medicine, Center for Biomedical Imaging Research, Department of Biomedical Engineering, Beijing (China); Cui, Yuanyuan [PLA General Hospital, Department of Radiology, Beijing (China); Zhou, Zechen [Philips Research China, Healthcare Department, Beijing (China); Yuan, Chun [Tsinghua University School of Medicine, Center for Biomedical Imaging Research, Department of Biomedical Engineering, Beijing (China); University of Washington, Department of Radiology, Seattle, WA (United States); Zhao, Xihai [Tsinghua University School of Medicine, Center for Biomedical Imaging Research, Department of Biomedical Engineering, Beijing (China); Beijing Institute for Brain Disorders, Center for Stroke, Beijing (China)

    2017-05-15

    Significant stenosis or occlusion in carotid arteries may lead to diffuse wall thickening (DWT) in the arterial wall of downstream. This study aimed to investigate the correlation between proximal internal carotid artery (ICA) steno-occlusive disease and DWT in ipsilateral petrous ICA. Symptomatic patients with atherosclerotic stenosis (>0%) in proximal ICA were recruited and underwent carotid MR vessel wall imaging. The 3D motion sensitized-driven equilibrium prepared rapid gradient-echo (3D-MERGE) was acquired for characterizing the wall thickness and longitudinal extent of the lesions in petrous ICA and the distance from proximal lesion to the petrous ICA. The stenosis degree in proximal ICA was measured on the time-of-flight (TOF) images. In total, 166 carotid arteries from 125 patients (mean age 61.0 ± 10.5 years, 99 males) were eligible for final analysis and 64 showed DWT in petrous ICAs. The prevalence of severe DWT in petrous ICA was 1.4%, 5.3%, 5.9%, and 80.4% in ipsilateral proximal ICAs with stenosis category of 1%-49%, 50%-69%, 70%-99%, and total occlusion, respectively. Proximal ICA stenosis was significantly correlated with the wall thickness in petrous ICA (r = 0.767, P < 0.001). Logistic regression analysis showed that proximal ICA stenosis was independently associated with DWT in ipsilateral petrous ICA (odds ratio (OR) = 2.459, 95% confidence interval (CI) 1.896-3.189, P < 0.001). Proximal ICA steno-occlusive disease is independently associated with DWT in ipsilateral petrous ICA. (orig.)

  16. The Spiral Arm Segments of the Galaxy within 3 kpc from the Sun: A Statistical Approach

    Science.gov (United States)

    Griv, Evgeny; Jiang, Ing-Guey; Hou, Li-Gang

    2017-08-01

    As can be reasonably expected, upcoming large-scale APOGEE, GAIA, GALAH, LAMOST, and WEAVE stellar spectroscopic surveys will yield rather noisy Galactic distributions of stars. In view of the possibility of employing these surveys, our aim is to present a statistical method to extract information about the spiral structure of the Galaxy from currently available data, and to demonstrate the effectiveness of this method. The model differs from previous works studying how objects are distributed in space in its calculation of the statistical significance of the hypothesis that some of the objects are actually concentrated in a spiral. A statistical analysis of the distribution of cold dust clumps within molecular clouds, H II regions, Cepheid stars, and open clusters in the nearby Galactic disk within 3 kpc from the Sun is carried out. As an application of the method, we obtain distances between the Sun and the centers of the neighboring Sagittarius arm segment, the Orion arm segment in which the Sun is located, and the Perseus arm segment. Pitch angles of the logarithmic spiral segments and their widths are also estimated. The hypothesis that the collected objects accidentally form spirals is refuted with almost 100% statistical confidence. We show that these four independent distributions of young objects lead to essentially the same results. We also demonstrate that our newly deduced values of the mean distances and pitch angles for the segments are not too far from those found recently by Reid et al. using VLBI-based trigonometric parallaxes of massive star-forming regions.

  17. A Bayesian approach to fiber orientation estimation guided by volumetric tract segmentation.

    Science.gov (United States)

    Ye, Chuyang; Prince, Jerry L

    2016-12-01

    Diffusion magnetic resonance imaging (dMRI) provides information about the microstructure of white matter in the human brain. From dMRI, streamlining tractography is often used to reconstruct computational representations of white matter tracts from which differences in structural connectivity can be explored. In the fiber tracking process, anatomical information can help reduce tracking errors caused by crossing fibers and image noise. In this paper, we propose a Bayesian method for estimating fiber orientations (FOs) guided by anatomical tract information using diffusion tensor imaging (DTI), which is a standard clinical and research dMRI protocol. The proposed method is named Fiber Orientation Reconstruction guided by Tract Segmentation (FORTS). A first step segments and labels the white matter tracts volumetrically, including explicit representations of crossing regions. A second step estimates the FOs using the diffusion information and the anatomical knowledge from segmented white matter tracts. A single FO is estimated in the noncrossing regions while two FOs are estimated in the crossing regions. A third step carries out streamlining tractography that uses information from both the segmented tracts and the estimated FOs. Experiments performed on a digital crossing phantom, a physical phantom, and brain DTI of 18 healthy subjects show that FORTS is able to use the anatomical information to produce FOs with better accuracy and to reduce anatomically incorrect streamlines. In particular, on the brain DTI data, we studied the connectivity of anatomically defined tracts to cortical areas, which is not straightforwardly achievable using only volumetric tract segmentation. These connectivity results demonstrate the potential application of FORTS to scientific studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Automatic segmentation of 4D cardiac MR images for extraction of ventricular chambers using a spatio-temporal approach

    Science.gov (United States)

    Atehortúa, Angélica; Zuluaga, Maria A.; Ourselin, Sébastien; Giraldo, Diana; Romero, Eduardo

    2016-03-01

    An accurate ventricular function quantification is important to support evaluation, diagnosis and prognosis of several cardiac pathologies. However, expert heart delineation, specifically for the right ventricle, is a time consuming task with high inter-and-intra observer variability. A fully automatic 3D+time heart segmentation framework is herein proposed for short-axis-cardiac MRI sequences. This approach estimates the heart using exclusively information from the sequence itself without tuning any parameters. The proposed framework uses a coarse-to-fine approach, which starts by localizing the heart via spatio-temporal analysis, followed by a segmentation of the basal heart that is then propagated to the apex by using a non-rigid-registration strategy. The obtained volume is then refined by estimating the ventricular muscle by locally searching a prior endocardium- pericardium intensity pattern. The proposed framework was applied to 48 patients datasets supplied by the organizers of the MICCAI 2012 Right Ventricle segmentation challenge. Results show the robustness, efficiency and competitiveness of the proposed method both in terms of accuracy and computational load.

  19. Prostate segmentation: an efficient convex optimization approach with axial symmetry using 3-D TRUS and MR images.

    Science.gov (United States)

    Qiu, Wu; Yuan, Jing; Ukwatta, Eranga; Sun, Yue; Rajchl, Martin; Fenster, Aaron

    2014-04-01

    We propose a novel global optimization-based approach to segmentation of 3-D prostate transrectal ultrasound (TRUS) and T2 weighted magnetic resonance (MR) images, enforcing inherent axial symmetry of prostate shapes to simultaneously adjust a series of 2-D slice-wise segmentations in a "global" 3-D sense. We show that the introduced challenging combinatorial optimization problem can be solved globally and exactly by means of convex relaxation. In this regard, we propose a novel coherent continuous max-flow model (CCMFM), which derives a new and efficient duality-based algorithm, leading to a GPU-based implementation to achieve high computational speeds. Experiments with 25 3-D TRUS images and 30 3-D T2w MR images from our dataset, and 50 3-D T2w MR images from a public dataset, demonstrate that the proposed approach can segment a 3-D prostate TRUS/MR image within 5-6 s including 4-5 s for initialization, yielding a mean Dice similarity coefficient of 93.2%±2.0% for 3-D TRUS images and 88.5%±3.5% for 3-D MR images. The proposed method also yields relatively low intra- and inter-observer variability introduced by user manual initialization, suggesting a high reproducibility, independent of observers.

  20. Electric field theory based approach to search-direction line definition in image segmentation: application to optimal femur-tibia cartilage segmentation in knee-joint 3-D MR

    Science.gov (United States)

    Yin, Y.; Sonka, M.

    2010-03-01

    A novel method is presented for definition of search lines in a variety of surface segmentation approaches. The method is inspired by properties of electric field direction lines and is applicable to general-purpose n-D shapebased image segmentation tasks. Its utility is demonstrated in graph construction and optimal segmentation of multiple mutually interacting objects. The properties of the electric field-based graph construction guarantee that inter-object graph connecting lines are non-intersecting and inherently covering the entire object-interaction space. When applied to inter-object cross-surface mapping, our approach generates one-to-one and all-to-all vertex correspondent pairs between the regions of mutual interaction. We demonstrate the benefits of the electric field approach in several examples ranging from relatively simple single-surface segmentation to complex multiobject multi-surface segmentation of femur-tibia cartilage. The performance of our approach is demonstrated in 60 MR images from the Osteoarthritis Initiative (OAI), in which our approach achieved a very good performance as judged by surface positioning errors (average of 0.29 and 0.59 mm for signed and unsigned cartilage positioning errors, respectively).

  1. A new and general approach to signal denoising and eye movement classification based on segmented linear regression.

    Science.gov (United States)

    Pekkanen, Jami; Lappi, Otto

    2017-12-18

    We introduce a conceptually novel method for eye-movement signal analysis. The method is general in that it does not place severe restrictions on sampling frequency, measurement noise or subject behavior. Event identification is based on segmentation that simultaneously denoises the signal and determines event boundaries. The full gaze position time-series is segmented into an approximately optimal piecewise linear function in O(n) time. Gaze feature parameters for classification into fixations, saccades, smooth pursuits and post-saccadic oscillations are derived from human labeling in a data-driven manner. The range of oculomotor events identified and the powerful denoising performance make the method useable for both low-noise controlled laboratory settings and high-noise complex field experiments. This is desirable for harmonizing the gaze behavior (in the wild) and oculomotor event identification (in the laboratory) approaches to eye movement behavior. Denoising and classification performance are assessed using multiple datasets. Full open source implementation is included.

  2. Lower Lumbar Segmental Arteries Can Intersect Over the Intervertebral Disc in the Oblique Lateral Interbody Fusion Approach With a Risk for Arterial Injury: Radiological Analysis of Lumbar Segmental Arteries by Using Magnetic Resonance Imaging.

    Science.gov (United States)

    Orita, Sumihisa; Inage, Kazuhide; Sainoh, Takeshi; Fujimoto, Kazuki; Sato, Jun; Shiga, Yasuhiro; Kanamoto, Hirohito; Abe, Koki; Yamauchi, Kazuyo; Aoki, Yasuchika; Nakamura, Junichi; Matsuura, Yusuke; Suzuki, Takane; Kubota, Go; Eguchi, Yawara; Terakado, Atsushi; Takahashi, Kazuhisa; Ohtori, Seiji

    2017-02-01

    A retrospective radiological study on vascular anatomy. The aim of this study was to evaluate the anatomical and radiological features of lumbar segmental arteries with respect to the surgical field of the oblique lateral interbody fusion (OLIF) approach by using magnetic resonance imaging (MRI). OLIF surgery restores disc height and enables indirect decompression of narrowed spinal canals through an oblique lateral approach to the spine, by using a specially designed retractor. In a minimal surgical field, injuring segmental arteries can cause massive hemorrhage. We reviewed 272 lumbar MRIs. In the sagittal images, the intersection of one-third of the anterior and median lines of the intervertebral disc (IVD) was considered the center of the virtually installed OLIF retractor. The cephalad/caudal distances from the center and branch angles of segmental arteries to the longitudinal axes of the aorta were measured to determine whether the segmental arteries run into the surgical area. Statistical significance was set at P 90°) in L4 and L5 arteries. The average distance to the center of the caudal adjacent IVD was significantly larger, and there were generally low possibilities for the existence of segmental arteries below half of the vertebral height, where the surgeons can install fixation pins with ease and safety. Among the lumbar segmental arteries, L5 showed specific characteristics with significant deviation, a four times (4.1% vs. L1-L3 segmental arteries) higher adjacency rate, and a two-fifth (38.6% vs. 100%) lower existence rate. Segmental arteries can be involved in the surgical field of OLIF especially in the lower lumbar spine level of L4 and L5 arteries, which can directly run across IVDs. L5 segmental arteries can also be iliolumbar arteries that have an abnormal trajectory by nature. 4.

  3. A fully automated approach for baby cry signal segmentation and boundary detection of expiratory and inspiratory episodes.

    Science.gov (United States)

    Abou-Abbas, Lina; Tadj, Chakib; Fersaie, Hesam Alaie

    2017-09-01

    The detection of cry sounds is generally an important pre-processing step for various applications involving cry analysis such as diagnostic systems, electronic monitoring systems, emotion detection, and robotics for baby caregivers. Given its complexity, an automatic cry segmentation system is a rather challenging topic. In this paper, a framework for automatic cry sound segmentation for application in a cry-based diagnostic system has been proposed. The contribution of various additional time- and frequency-domain features to increase the robustness of a Gaussian mixture model/hidden Markov model (GMM/HMM)-based cry segmentation system in noisy environments is studied. A fully automated segmentation algorithm to extract cry sound components, namely, audible expiration and inspiration, is introduced and is grounded on two approaches: statistical analysis based on GMMs or HMMs classifiers and a post-processing method based on intensity, zero crossing rate, and fundamental frequency feature extraction. The main focus of this paper is to extend the systems developed in previous works to include a post-processing stage with a set of corrective and enhancing tools to improve the classification performance. This full approach allows to precisely determine the start and end points of the expiratory and inspiratory components of a cry signal, EXP and INSV, respectively, in any given sound signal. Experimental results have indicated the effectiveness of the proposed solution. EXP and INSV detection rates of approximately 94.29% and 92.16%, respectively, were achieved by applying a tenfold cross-validation technique to avoid over-fitting.

  4. Analysis of segmental phosphate absorption in intact rats. A compartmental analysis approach.

    OpenAIRE

    Kayne, L H; D'Argenio, D Z; Meyer, J H; Hu, M S; Jamgotchian, N; Lee, D B

    1993-01-01

    Available information supports the dominance of the proximal intestine in inorganic phosphate (Pi) absorption. However, there is no strategy for analyzing segmental Pi absorption from a spontaneously propelled meal in an intact animal. We propose a solution using compartmental analysis. After intragastric administration of a 32P-labeled Pi liquid meal containing a nonabsorbable marker, [14C]polyethylene glycol (PEG), rats were killed at 2, 10, 20, 30, 60, 120, and 240 min. The gastrointestina...

  5. STEM Employment in the New Economy: A Labor Market Segmentation Approach

    Science.gov (United States)

    Torres-Olave, Blanca M.

    2013-01-01

    The present study examined the extent to which the U.S. STEM labor market is stratified in terms of quality of employment. Through a series of cluster analyses and Chi-square tests on data drawn from the 2008 Survey of Income Program Participation (SIPP), the study found evidence of segmentation in the highly-skilled STEM and non-STEM samples,…

  6. Approaches to automatic parameter fitting in a microscopy image segmentation pipeline: An exploratory parameter space analysis

    OpenAIRE

    Christian Held; Tim Nattkemper; Ralf Palmisano; Thomas Wittenberg

    2013-01-01

    Introduction: Research and diagnosis in medicine and biology often require the assessment of a large amount of microscopy image data. Although on the one hand, digital pathology and new bioimaging technologies find their way into clinical practice and pharmaceutical research, some general methodological issues in automated image analysis are still open. Methods: In this study, we address the problem of fitting the parameters in a microscopy image segmentation pipeline. We propose to fit the p...

  7. A hybrid approach to segmenting hair in dermoscopic images using a universal kernel

    OpenAIRE

    Nguyen, Nhi Hoang

    2009-01-01

    Hair occlusion often causes automated melanoma diagnostic systems to fail. We present a new method to segment hair in dermoscopic images. First, all possible dark and light hairs are amplified without prejudice with a universal matched filtering kernel. We then process the filter response with a novel tracing algorithm to get a raw hair mask. This raw mask is skeletonized to contain only the centerlines of all the possible hairs. Then the centerlines are verified by applying a model checker o...

  8. Local adaptive approach toward segmentation of microscopic images of activated sludge flocs

    Science.gov (United States)

    Khan, Muhammad Burhan; Nisar, Humaira; Ng, Choon Aun; Lo, Po Kim; Yap, Vooi Voon

    2015-11-01

    Activated sludge process is a widely used method to treat domestic and industrial effluents. The conditions of activated sludge wastewater treatment plant (AS-WWTP) are related to the morphological properties of flocs (microbial aggregates) and filaments, and are required to be monitored for normal operation of the plant. Image processing and analysis is a potential time-efficient monitoring tool for AS-WWTPs. Local adaptive segmentation algorithms are proposed for bright-field microscopic images of activated sludge flocs. Two basic modules are suggested for Otsu thresholding-based local adaptive algorithms with irregular illumination compensation. The performance of the algorithms has been compared with state-of-the-art local adaptive algorithms of Sauvola, Bradley, Feng, and c-mean. The comparisons are done using a number of region- and nonregion-based metrics at different microscopic magnifications and quantification of flocs. The performance metrics show that the proposed algorithms performed better and, in some cases, were comparable to the state-of the-art algorithms. The performance metrics were also assessed subjectively for their suitability for segmentations of activated sludge images. The region-based metrics such as false negative ratio, sensitivity, and negative predictive value gave inconsistent results as compared to other segmentation assessment metrics.

  9. A level-set based approach for anterior teeth segmentation in cone beam computed tomography images.

    Science.gov (United States)

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

    2014-07-01

    Cone beam CT (CBCT) has gained popularity in dentistry for 3D imaging of the jaw bones and teeth due to its high resolution and relatively lower radiation exposure compared to multi-slice CT (MSCT). However, image segmentation of the tooth from CBCT is more complex than from MSCT due to lower bone signal-to-noise. This paper describes a level-set method to extract tooth shape from CBCT images of the head. We improve the variational level set framework with three novel energy terms: (1) dual intensity distribution models to represent the two regions inside and outside the tooth; (2) a robust shape prior to impose a shape constraint on the contour evolution; and (3) using the thickness of the tooth dentine wall as a constraint to avoid leakage and shrinkage problems in the segmentation process. The proposed method was compared with several existing methods and was shown to give improved segmentation accuracy. Copyright © 2014 Elsevier Ltd. All rights reserved.

  10. Photocoagulation of dermal blood vessels with multiple laser pulses in an in vivo microvascular model.

    Science.gov (United States)

    Jia, Wangcun; Tran, Nadia; Sun, Victor; Marinček, Marko; Majaron, Boris; Choi, Bernard; Nelson, J Stuart

    2012-02-01

    Current laser therapy of port wine stain (PWS) birthmarks with a single laser pulse (SLP) does not produce complete lesion removal in the majority of patients. To improve PWS therapeutic efficacy, we evaluated the performance of an approach based on multiple laser pulses (MLP) to enhance blood vessel photocoagulation. The hamster dorsal window chamber model was used. Radiant exposure (RE), pulse repetition rate (f(r)), total number of pulses (n(p)), and length of vessel irradiated were varied. Blood vessels in the window were irradiated with either SLP with RE of 4-7 J/cm(2) or MLP with RE per pulse of 1.4-5.0 J/cm(2), f(r) of 0.5-26.0 Hz, and n(p) of 2-5. The laser wavelength was 532 nm and pulse duration was 1 ms. Either a 2 mm vessel segment or entire vessel branch was irradiated. Digital photographs and laser speckle images of the window were recorded before and at specific time points after laser irradiation to monitor laser-induced blood vessel structural and functional changes, respectively. We found that: (1) for a SLP approach, the RE required to induce blood vessel photocoagulation was 7 J/cm(2) as compared to only 2 J/cm(2) per pulse for the MLP approach; (2) for MLP, two pulses at a repetition rate of 5 Hz and a RE of 3 J/cm(2) can induce photocoagulation of more than 80% of irradiated blood vessel; and (3) irradiation of a longer segment of blood vessel resulted in lower reperfusion rate. The MLP approach can induce blood vessel photocoagulation at much lower RE per pulse as compared to SLP. The 5 Hz f(r) and the need for two pulses are achievable with modern laser technology, which makes the MLP approach practical in the clinical management of PWS birthmarks. Copyright © 2012 Wiley Periodicals, Inc.

  11. Concept design of the DEMO divertor cassette-to-vacuum vessel locking system adopting a systems engineering approach

    Energy Technology Data Exchange (ETDEWEB)

    Di Gironimo, G., E-mail: giuseppe.digironimo@unina.it [Università degli Studi di Napoli “Federico II”, Dipartimento di Ingegneria Industriale, Piazzale Tecchio 80, 80135 Napoli (Italy); Carfora, D. [Tampere University of Technology, Korkeakoulunkatu 6, 33720 Tampere (Finland); VTT Technical Research Centre of Finland, Tekniikankatu 1, PO Box 1300, FI-33101 Tampere (Finland); Università degli Studi di Napoli “Federico II”, Dipartimento di Ingegneria Industriale, Piazzale Tecchio 80, 80135 Napoli (Italy); Esposito, G.; Lanzotti, A.; Marzullo, D. [Università degli Studi di Napoli “Federico II”, Dipartimento di Ingegneria Industriale, Piazzale Tecchio 80, 80135 Napoli (Italy); Siuko, M. [VTT Technical Research Centre of Finland, Tekniikankatu 1, PO Box 1300, FI-33101 Tampere (Finland)

    2015-05-15

    Highlights: • An iterative and incremental design process for cassette-to-VV locking system of DEMO divertor is presented. • Three different concepts have been developed with a systematic design approach. • The final concept has been selected with Fuzzy-Analytic Hierarchy Process in virtual reality. - Abstract: This paper deals with pre-concept studies of DEMO divertor cassette-to-vacuum vessel locking system under the work program WP13-DAS-07-T06: Divertor Remote Maintenance System pre-concept study. An iterative design process, consistent with Systems Engineering guidelines and named Iterative and Participative Axiomatic Design Process (IPADeP), is used in this paper to propose new innovative solutions for divertor locking system, which can overcome the difficulties in applying the ITER principles to DEMO. The solutions conceived have been analysed from the structural point of view using the software Ansys and, eventually, evaluated using the methodology known as Fuzzy-Analytic Hierarchy Process. Due to the lack and the uncertainty of the requirements in this early conceptual design stage, the aim is to cover a first iteration of an iterative and incremental process to propose an innovative design concept to be developed in more details as the information will be completed.

  12. Blood vessel tortuosity selects against evolution of aggressive tumor cells in confined tissue environments: A modeling approach.

    Directory of Open Access Journals (Sweden)

    András Szabó

    2017-07-01

    Full Text Available Cancer is a disease of cellular regulation, often initiated by genetic mutation within cells, and leading to a heterogeneous cell population within tissues. In the competition for nutrients and growth space within the tumors the phenotype of each cell determines its success. Selection in this process is imposed by both the microenvironment (neighboring cells, extracellular matrix, and diffusing substances, and the whole of the organism through for example the blood supply. In this view, the development of tumor cells is in close interaction with their increasingly changing environment: the more cells can change, the more their environment will change. Furthermore, instabilities are also introduced on the organism level: blood supply can be blocked by increased tissue pressure or the tortuosity of the tumor-neovascular vessels. This coupling between cell, microenvironment, and organism results in behavior that is hard to predict. Here we introduce a cell-based computational model to study the effect of blood flow obstruction on the micro-evolution of cells within a cancerous tissue. We demonstrate that stages of tumor development emerge naturally, without the need for sequential mutation of specific genes. Secondly, we show that instabilities in blood supply can impact the overall development of tumors and lead to the extinction of the dominant aggressive phenotype, showing a clear distinction between the fitness at the cell level and survival of the population. This provides new insights into potential side effects of recent tumor vasculature normalization approaches.

  13. A novel and robust Bayesian approach for segmentation of psoriasis lesions and its risk stratification.

    Science.gov (United States)

    Shrivastava, Vimal K; Londhe, Narendra D; Sonawane, Rajendra S; Suri, Jasjit S

    2017-10-01

    The need for characterization of psoriasis lesion severity is clinically valuable and vital for dermatologists since it provides a reliable and precise decision on risk assessment. The automated delineation of lesion is a prerequisite prior to characterization, which is challenging itself. Thus, this paper has two major objectives: (a) design of a segmentation system which can model by learning the lesion characteristics and this is posed as a Bayesian model; (b) develop a psoriasis risk assessment system (pRAS) by crisscrossing the blocks which drives the fundamental machine learning paradigm. The segmentation system uses the knowledge derived by the experts along with the features reflected by the lesions to build a Bayesian framework that helps to classify each pixel of the image into lesion vs. Since this lesion has several stages and grades, hence the system undergoes the risk assessment to classify into five levels of severity: healthy, mild, moderate, severe and very severe. We build nine kinds of pRAS utilizing different combinations of the key blocks. These nine pRAS systems use three classifiers (Support Vector Machine (SVM), Decision Tree (DT) and Neural Network (NN)) and three feature selection techniques (Principal Component Analysis (PCA), Fisher Discriminant Ratio (FDR) and Mutual Information (MI)). The two major experiments conducted using these nine systems were: (i) selection of best system combination based on classification accuracy and (ii) understanding the reliability of the system. This leads us to computation of key system performance parameters such as: feature retaining power, aggregated feature effect and reliability index besides conventional attributes like accuracy, sensitivity, specificity. Using the database used in this study consisted of 670 psoriasis images, the combination of SVM and FDR was revealed as the optimal pRAS system and yielded a classification accuracy of 99.84% using cross-validation protocol. Further, SVM

  14. Evaluating accuracy of striatal, pallidal, and thalamic segmentation methods: Comparing automated approaches to manual delineation.

    Science.gov (United States)

    Makowski, Carolina; Béland, Sophie; Kostopoulos, Penelope; Bhagwat, Nikhil; Devenyi, Gabriel A; Malla, Ashok K; Joober, Ridha; Lepage, Martin; Chakravarty, M Mallar

    2017-03-01

    Accurate automated quantification of subcortical structures is a greatly pursued endeavour in neuroimaging. In an effort to establish the validity and reliability of these methods in defining the striatum, globus pallidus, and thalamus, we investigated differences in volumetry between manual delineation and automated segmentations derived by widely used FreeSurfer and FSL packages, and a more recent segmentation method, the MAGeT-Brain algorithm. In a first set of experiments, the basal ganglia and thalamus of thirty subjects (15 first episode psychosis [FEP], 15 controls) were manually defined and compared to the labels generated by the three automated methods. Our results suggest that all methods overestimate volumes compared to the manually derived "gold standard", with the least pronounced differences produced using MAGeT. The least between-method variability was noted for the striatum, whereas marked differences between manual segmentation and MAGeT compared to FreeSurfer and FSL emerged for the globus pallidus and thalamus. Correlations between manual segmentation and automated methods were strongest for MAGeT (range: 0.51 to 0.92; pmanual labels and automated methods at the lower end of the distribution (i.e. smaller structures), which was most prominent for bilateral thalamus across automated pipelines, and left globus pallidus for FSL. We then went on to examine volume and shape of the basal ganglia structures using automated techniques in 135 FEP patients and 88 controls. The striatum and globus pallidus were significantly larger in FEP patients compared to controls bilaterally, irrespective of the method used. MAGeT-Brain was more sensitive to shape-based group differences, and uncovered widespread surface expansions in the striatum and globus pallidus bilaterally in FEP patients compared to controls, and surface contractions in bilateral thalamus (FDR-corrected). By contrast, after using a recommended cluster-wise thresholding method, FSL only detected

  15. STEM employment in the new economy: A labor market segmentation approach

    Science.gov (United States)

    Torres-Olave, Blanca M.

    The present study examined the extent to which the U.S. STEM labor market is stratified in terms of quality of employment. Through a series of cluster analyses and Chi-square tests on data drawn from the 2008 Survey of Income Program Participation (SIPP), the study found evidence of segmentation in the highly-skilled STEM and non-STEM samples, which included workers with a subbaccalaureate diploma or above. The cluster analyses show a pattern consistent with Labor Market Segmentation theory: Higher wages are associated with other primary employment characteristics, including health insurance and pension benefits, as well as full-time employment. In turn, lower wages showed a tendency to cluster with secondary employment characteristics, such as part-time employment, multiple employment, and restricted access to health insurance and pension benefits. The findings also suggest that women have a higher likelihood of being employed in STEM jobs with secondary characteristics. The findings reveal a far more variegated employment landscape than is usually presented in national reports of the STEM workforce. There is evidence that, while STEM employment may be more resilient than non-STEM employment to labor restructuring trends in the new economy, the former is far from immune to secondary labor characteristics. There is a need for ongoing dialogue between STEM education (at all levels), employers, policymakers, and other stakeholders to truly understand not only the barriers to equity in employment relations, but also the mechanisms that create and maintain segmentation and how they may impact women, underrepresented minorities, and the foreign-born.

  16. Segmenting Multiple Sclerosis Lesions Using a Spatially Constrained K-Nearest Neighbour Approach

    DEFF Research Database (Denmark)

    Lyksborg, Mark; Larsen, Rasmus; Sørensen, Per Soelberg

    2012-01-01

    We propose a method for the segmentation of Multiple Sclerosis lesions. The method is based on probability maps derived from a K-Nearest Neighbours classification. These are used as a non parametric likelihood in a Bayesian formulation with a prior that assumes connectivity of neighbouring voxels......, the diffusion MRI measures of Fractional Anisotropy (FA), Mean Diffusivity (MD) and several spatial features. Results show a benefit from the inclusion of diffusion primarily to the most difficult cases. Results shows that combining probabilistic K-Nearest Neighbour with a Markov Random Field formulation leads...

  17. Segmenting Multiple Sclerosis Lesions using a Spatially Constrained K-Nearest Neighbour approach

    DEFF Research Database (Denmark)

    Lyksborg, Mark; Larsen, Rasmus; Sørensen, Per Soelberg

    2012-01-01

    We propose a method for the segmentation of Multiple Sclerosis lesions. The method is based on probability maps derived from a K-Nearest Neighbours classication. These are used as a non parametric likelihood in a Bayesian formulation with a prior that assumes connectivity of neighbouring voxels......, the diusion MRI measures of Fractional Anisotropy (FA), Mean Diusivity (MD) and several spatial features. Results show a benet from the inclusion of diusion primarily to the most dicult cases. Results shows that combining probabilistic K-Nearest Neighbour with a Markov Random Field formulation leads...

  18. Mobility Behavior of the Elderly: an attitude-based segmentation approach for a heterogeneous target group

    DEFF Research Database (Denmark)

    Haustein, Sonja

    2012-01-01

    The western population is ageing. Based on the assumption that the elderly are a quite heterogeneous population group with an increasing impact on the transport system, mobility types of the elderly were identified. By means of 1,500 standardized telephone interviews, mobility behavior and possible...... determinantes including infrastructural, sociodemographic and attitudinal variables, were assessed. The most important factors, identified by five regression analyses, served as type-constituent variables in a series of cluster analyses. The final cluster solution resulted in four segments of the elderly named...... of the diverse lifestyles, attitudes, travel behavior and needs of the elderly. Furthermore, it identifies starting points for the reduction of car use....

  19. An improved lesion detection approach based on similarity measurement between fuzzy intensity segmentation and spatial probability maps.

    Science.gov (United States)

    Shen, Shan; Szameitat, Andre J; Sterr, Annette

    2010-02-01

    The application of automatic segmentation methods in lesion detection is desirable. However, such methods are restricted by intensity similarities between lesioned and healthy brain tissue. Using multi-spectral magnetic resonance imaging (MRI) modalities may overcome this problem but it is not always practicable. In this article, a lesion detection approach requiring a single MRI modality is presented, which is an improved method based on a recent publication. This new method assumes that a low similarity should be found in the regions of lesions when the likeness between an intensity based fuzzy segmentation and a location based tissue probabilities is measured. The usage of a normalized similarity measurement enables the current method to fine-tune the threshold for lesion detection, thus maximizing the possibility of reaching high detection accuracy. Importantly, an extra cleaning step is included in the current approach which removes enlarged ventricles from detected lesions. The performance investigation using simulated lesions demonstrated that not only the majority of lesions were well detected but also normal tissues were identified effectively. Tests on images acquired in stroke patients further confirmed the strength of the method in lesion detection. When compared with the previous version, the current approach showed a higher sensitivity in detecting small lesions and had less false positives around the ventricle and the edge of the brain. Copyright 2010 Elsevier Inc. All rights reserved.

  20. Segmenting into Adequate Units for Automatic Recognition of Emotion-Related Episodes: A Speech-Based Approach

    Directory of Open Access Journals (Sweden)

    Anton Batliner

    2010-01-01

    Full Text Available We deal with the topic of segmenting emotion-related (emotional/affective episodes into adequate units for analysis and automatic processing/classification—a topic that has not been addressed adequately so far. We concentrate on speech and illustrate promising approaches by using a database with children's emotional speech. We argue in favour of the word as basic unit and map sequences of words on both syntactic and ‘‘emotionally consistent” chunks and report classification performances for an exhaustive modelling of our data by mapping word-based paralinguistic emotion labels onto three classes representing valence (positive, neutral, negative, and onto a fourth rest (garbage class.

  1. Segmentation of multiple sclerosis lesions in MRI: an image analysis approach

    Science.gov (United States)

    Krishnan, Kalpagam; Atkins, M. Stella

    1998-06-01

    This paper describes an intensity-based method for the segmentation of multiple sclerosis lesions in dual-echo PD and T2-weighted magnetic resonance brain images. The method consists of two stages: feature extraction and image analysis. For feature extraction, we use a ratio filter transformation on the proton density (PD) and spin-spin (T2) data sequences to extract the white matter, cerebrospinal fluid and the lesion features. The one and two dimensional histograms of the features are then analyzed to obtain different parameters, which provide the basis for subsequent image analysis operations to detect the multiple sclerosis lesions. In the image analysis stage, the PD images of the volume are first pre-processed to enhance the lesion tissue areas. White matter and cerebrospinal fluid masks are then generated and applied on the enhanced volume to remove non- lesion areas. Segmentation of lesions is performed in two steps: conspicuous lesions are extracted in the first step, followed by the extraction of the subtle lesions.

  2. Cluster analysis of fruit and vegetable-related perceptions: an alternative approach of consumer segmentation.

    Science.gov (United States)

    Simunaniemi, A-M; Nydahl, M; Andersson, A

    2013-02-01

    Audience segmentation optimises health communication aimed to promote healthy dietary habits, such as fruit and vegetable (F&V) consumption. The present study aimed to segment respondents into clusters based on F&V-related perceptions, and to describe these clusters with respect to F&V consumption and sex. The cross-sectional study was conducted using a semi-structured questionnaire. The respondents were randomly selected among Swedish adults (n = 1304; response rate 51%; 56% women). A two-step cluster analysis was conducted followed by a binary logistic regression with cluster membership as a dependent variable. The clusters were compared using t-tests and chi-squared tests. P vegetables (both sexes) and fruit (women only), whereas men in the Indifferent cluster (n = 715) consumed more juice. Indifferent cluster reported more F&V consumption preventing factors, such as storage and preparation difficulties and low satisfaction with F&V selection and price. Not liking or not having a habit of F&V consumption, laziness, forgetting and a lack of time were mentioned as main barriers to F&V consumption. The Indifferent cluster reports more practical and life-style related difficulties. The Positive cluster consumes more vegetables, perceives fewer F&V-related difficulties, and looks for more dietary information. The findings confirm that cluster analysis is an appropriate way of identifying consumer subgroups for targeted health and nutrition communication. © 2012 The Authors. Journal of Human Nutrition and Dietetics © 2012 The British Dietetic Association Ltd.

  3. Segmentation based building detection approach from LiDAR point cloud

    Directory of Open Access Journals (Sweden)

    Anandakumar M. Ramiya

    2017-06-01

    Full Text Available Accurate building detection and reconstruction is an important challenge posed to the remote sensing community dealing with LiDAR point cloud. The inherent geometric nature of LiDAR point cloud provides a new dimension to the remote sensing data which can be used to produce accurate 3D building models at relatively less time compared to traditional photogrammetry based 3D reconstruction methods. 3D segmentation is a key step to bring out the implicit geometrical information from the LiDAR point cloud. This research proposes to use open source point cloud library (PCL for 3D segmentation of LiDAR point cloud and presents a novel histogram based methodology to separate the building clusters from the non building clusters. The proposed methodology has been applied on two different airborne LiDAR datasets acquired over part of urban region around Niagara Falls, Canada and southern Washington, USA. An overall building detection accuracy of 100% and 82% respectively is achieved for the two datasets. The performance of proposed methodology has been compared with the commercially available Terrasolid software. The results show that the buildings detected using open source point cloud library produce comparable results with the buildings detected using commercial software (buildings detection accuracy: 86.3% and 89.2% respectively for the two datasets.

  4. Strategy-aligned fuzzy approach for market segment evaluation and selection: a modular decision support system by dynamic network process (DNP)

    Science.gov (United States)

    Mohammadi Nasrabadi, Ali; Hosseinpour, Mohammad Hossein; Ebrahimnejad, Sadoullah

    2013-05-01

    In competitive markets, market segmentation is a critical point of business, and it can be used as a generic strategy. In each segment, strategies lead companies to their targets; thus, segment selection and the application of the appropriate strategies over time are very important to achieve successful business. This paper aims to model a strategy-aligned fuzzy approach to market segment evaluation and selection. A modular decision support system (DSS) is developed to select an optimum segment with its appropriate strategies. The suggested DSS has two main modules. The first one is SPACE matrix which indicates the risk of each segment. Also, it determines the long-term strategies. The second module finds the most preferred segment-strategies over time. Dynamic network process is applied to prioritize segment-strategies according to five competitive force factors. There is vagueness in pairwise comparisons, and this vagueness has been modeled using fuzzy concepts. To clarify, an example is illustrated by a case study in Iran's coffee market. The results show that success possibility of segments could be different, and choosing the best ones could help companies to be sure in developing their business. Moreover, changing the priority of strategies over time indicates the importance of long-term planning. This fact has been supported by a case study on strategic priority difference in short- and long-term consideration.

  5. [Pulmonary blood vessels in goats].

    Science.gov (United States)

    Roos, H; Hegner, K; Vollmerhaus, B

    1999-05-01

    The blood vessels in the lung of the goat, which until now have received little attention, are described in detail for the first time. With regard to the segments of the lung, blood vessels are bronchovascular units in the lobi craniales, lobus medius and lobus accessorius, but bronchoartery units in the lobi caudales. We investigated the types of branches of the Aa. pulmonales dextra et sinistra, the inter- and intraspecific principles of the outlet of the pulmonary veins and the importance of bronchopulmonary segmentation of the lungs.

  6. Semi-automatic integrated segmentation approaches and contour extraction applied to computed tomography scan images.

    Science.gov (United States)

    Khoodoruth, B Dhalila S Y; Rughooputh, Harry C S; Lefer, Wilfrid

    2008-01-01

    We propose to segment two-dimensional CT scans traumatic brain injuries with various methods. These methods are hybrid, feature extraction, level sets, region growing, and watershed which are analysed based upon their parametric and nonparametric arguments. The pixel intensities, gradient magnitude, affinity map, and catchment basins of these methods are validated based upon various constraints evaluations. In this article, we also develop a new methodology for a computational pipeline that uses bilateral filtering, diffusion properties, watershed, and filtering with mathematical morphology operators for the contour extraction of the lesion in the feature available based mainly on the gradient function. The evaluations of the classification of these lesions are very briefly outlined in this context and are being undertaken by pattern recognition in another paper work.

  7. Using a service sector segmented approach to identify community stakeholders who can improve access to suicide prevention services for veterans.

    Science.gov (United States)

    Matthieu, Monica M; Gardiner, Giovanina; Ziegemeier, Ellen; Buxton, Miranda

    2014-04-01

    Veterans in need of social services may access many different community agencies within the public and private sectors. Each of these settings has the potential to be a pipeline for attaining needed health, mental health, and benefits services; however, many service providers lack information on how to conceptualize where Veterans go for services within their local community. This article describes a conceptual framework for outreach that uses a service sector segmented approach. This framework was developed to aid recruitment of a provider-based sample of stakeholders (N = 70) for a study on improving access to the Department of Veterans Affairs and community-based suicide prevention services. Results indicate that although there are statistically significant differences in the percent of Veterans served by the different service sectors (F(9, 55) = 2.71, p = 0.04), exposure to suicidal Veterans and providers' referral behavior is consistent across the sectors. Challenges to using this framework include isolating the appropriate sectors for targeted outreach efforts. The service sector segmented approach holds promise for identifying and referring at-risk Veterans in need of services. Reprint & Copyright © 2014 Association of Military Surgeons of the U.S.

  8. An Approach to Understanding Cohesive Slurry Settling, Mobilization, and Hydrogen Gas Retention in Pulsed Jet Mixed Vessels

    Energy Technology Data Exchange (ETDEWEB)

    Gauglitz, Phillip A.; Wells, Beric E.; Fort, James A.; Meyer, Perry A.

    2009-05-22

    The Hanford Waste Treatment and Immobilization Plant (WTP) is being designed and built to pretreat and vitrify a large portion of the waste in Hanford’s 177 underground waste storage tanks. Numerous process vessels will hold waste at various stages in the WTP. Some of these vessels have mixing-system requirements to maintain conditions where the accumulation of hydrogen gas stays below acceptable limits, and the mixing within the vessels is sufficient to release hydrogen gas under normal conditions and during off-normal events. Some of the WTP process streams are slurries of solid particles suspended in Newtonian fluids that behave as non-Newtonian slurries, such as Bingham yield-stress fluids. When these slurries are contained in the process vessels, the particles can settle and become progressively more concentrated toward the bottom of the vessels, depending on the effectiveness of the mixing system. One limiting behavior is a settled layer beneath a particle-free liquid layer. The settled layer, or any region with sufficiently high solids concentration, will exhibit non-Newtonian rheology where it is possible for the settled slurry to behave as a soft solid with a yield stress. In this report, these slurries are described as settling cohesive slurries.

  9. A new approach to study of seabird-fishery overlap: Connecting chick feeding with parental foraging and overlap with fishing vessels

    Directory of Open Access Journals (Sweden)

    Junichi Sugishita

    2015-07-01

    Full Text Available Incidental fisheries bycatch is recognised as a major threat to albatross populations worldwide. However, fishery discards and offal produced in large quantities might benefit some scavenging seabirds. Here, we demonstrate an integrated approach to better understand the ecological ramifications of fine-scale overlap between seabirds and fisheries. As a case study, we examined whether foraging in association with a fishing vessel is advantageous for chick provisioning in terms of quantity of food delivered to chicks, in northern royal albatross (Diomedea sanfordi at Taiaroa Head, New Zealand. Fine-scale overlap between albatrosses and vessels was quantified by integrating GPS tracking and Vessel Monitoring Systems (VMS. Meal size delivered to chicks was measured using custom-designed nest balances, and monitoring of attendance of adults fitted with radio transmitters was used in conjunction with time-lapse photography at the nest allowed us to allocate each feeding event to a specific parent. The combination of these techniques enabled comparison of meal sizes delivered to chicks with parental foraging trip durations with or without fishing vessels association. A total of 45 foraging trips and associated chick feeding events were monitored during the chick-rearing period in 2012. Differences in the meal size and foraging trip duration relative to foraging overlap with fisheries were examined using a linear mixed-effect model, adjusted for chick age. Our results, based on three birds, suggest that foraging in association with vessels does not confer an advantage for chick feeding for this population that demonstrated low rates of overlap while foraging. The integrated research design presented can be applied to other seabird species that are susceptible to bycatch, and offers a valuable approach to evaluate habitat quality by linking habitat use and foraging success in terms of total amount of food delivered to offspring.

  10. SU-F-J-97: A Joint Registration and Segmentation Approach for Large Bladder Deformations in Adaptive Radiotherapy

    Energy Technology Data Exchange (ETDEWEB)

    Derksen, A; Koenig, L; Heldmann, S [Fraunhofer MEVIS, Luebeck (Germany); Meine, H [Fraunhofer MEVIS, Bremen (Germany)

    2016-06-15

    Purpose: To improve results of deformable image registration (DIR) in adaptive radiotherapy for large bladder deformations in CT/CBCT pelvis imaging. Methods: A variational multi-modal DIR algorithm is incorporated in a joint iterative scheme, alternating between segmentation based bladder matching and registration. Using an initial DIR to propagate the bladder contour to the CBCT, in a segmentation step the contour is improved by discrete image gradient sampling along all surface normals and adapting the delineation to match the location of each maximum (with a search range of +−5/2mm at the superior/inferior bladder side and step size of 0.5mm). An additional graph-cut based constraint limits the maximum difference between neighboring points. This improved contour is utilized in a subsequent DIR with a surface matching constraint. By calculating an euclidean distance map of the improved contour surface, the new constraint enforces the DIR to map each point of the original contour onto the improved contour. The resulting deformation is then used as a starting guess to compute a deformation update, which can again be used for the next segmentation step. The result is a dense deformation, able to capture much larger bladder deformations. The new method is evaluated on ten CT/CBCT male pelvis datasets, calculating Dice similarity coefficients (DSC) between the final propagated bladder contour and a manually delineated gold standard on the CBCT image. Results: Over all ten cases, an average DSC of 0.93±0.03 is achieved on the bladder. Compared with the initial DIR (0.88±0.05), the DSC is equal (2 cases) or improved (8 cases). Additionally, DSC accuracy of femoral bones (0.94±0.02) was not affected. Conclusion: The new approach shows that using the presented alternating segmentation/registration approach, the results of bladder DIR in the pelvis region can be greatly improved, especially for cases with large variations in bladder volume. Fraunhofer MEVIS received

  11. A new approach to study of seabird-fishery overlap: Connecting chick feeding with parental foraging and overlap with fishing vessels

    OpenAIRE

    Sugishita, Junichi; Leigh G Torres; Seddon, Philip J.

    2015-01-01

    Incidental fisheries bycatch is recognised as a major threat to albatross populations worldwide. However, fishery discards and offal produced in large quantities might benefit some scavenging seabirds. Here, we demonstrate an integrated approach to better understand the ecological ramifications of fine-scale overlap between seabirds and fisheries. As a case study, we examined whether foraging in association with a fishing vessel is advantageous for chick provisioning in terms of quantity of f...

  12. Research vessels

    Digital Repository Service at National Institute of Oceanography (India)

    Rao, P.S.

    by the research vessels RV Gaveshani and ORV Sagar Kanya are reported. The work carried out by the three charted ships is also recorded. A short note on cruise plans for the study of ferromanganese nodules is added...

  13. Scaling properties and fractality in the distribution of coding segments in eukaryotic genomes revealed through a block entropy approach

    Science.gov (United States)

    Athanasopoulou, Labrini; Athanasopoulos, Stavros; Karamanos, Kostas; Almirantis, Yannis

    2010-11-01

    Statistical methods, including block entropy based approaches, have already been used in the study of long-range features of genomic sequences seen as symbol series, either considering the full alphabet of the four nucleotides or the binary purine or pyrimidine character set. Here we explore the alternation of short protein-coding segments with long noncoding spacers in entire chromosomes, focusing on the scaling properties of block entropy. In previous studies, it has been shown that the sizes of noncoding spacers follow power-law-like distributions in most chromosomes of eukaryotic organisms from distant taxa. We have developed a simple evolutionary model based on well-known molecular events (segmental duplications followed by elimination of most of the duplicated genes) which reproduces the observed linearity in log-log plots. The scaling properties of block entropy H(n) have been studied in several works. Their findings suggest that linearity in semilogarithmic scale characterizes symbol sequences which exhibit fractal properties and long-range order, while this linearity has been shown in the case of the logistic map at the Feigenbaum accumulation point. The present work starts with the observation that the block entropy of the Cantor-like binary symbol series scales in a similar way. Then, we perform the same analysis for the full set of human chromosomes and for several chromosomes of other eukaryotes. A similar but less extended linearity in semilogarithmic scale, indicating fractality, is observed, while randomly formed surrogate sequences clearly lack this type of scaling. Genomic sequences always present entropy values much lower than their random surrogates. Symbol sequences produced by the aforementioned evolutionary model follow the scaling found in genomic sequences, thus corroborating the conjecture that “segmental duplication-gene elimination” dynamics may have contributed to the observed long rangeness in the coding or noncoding alternation in

  14. Automated segmentation of MS lesions in FLAIR, DIR and T2-w MR images via an information theoretic approach

    Science.gov (United States)

    Hill, Jason E.; Matlock, Kevin; Pal, Ranadip; Nutter, Brian; Mitra, Sunanda

    2016-03-01

    Magnetic Resonance Imaging (MRI) is a vital tool in the diagnosis and characterization of multiple sclerosis (MS). MS lesions can be imaged with relatively high contrast using either Fluid Attenuated Inversion Recovery (FLAIR) or Double Inversion Recovery (DIR). Automated segmentation and accurate tracking of MS lesions from MRI remains a challenging problem. Here, an information theoretic approach to cluster the voxels in pseudo-colorized multispectral MR data (FLAIR, DIR, T2-weighted) is utilized to automatically segment MS lesions of various sizes and noise levels. The Improved Jump Method (IJM) clustering, assisted by edge suppression, is applied to the segmentation of white matter (WM), gray matter (GM), cerebrospinal fluid (CSF) and MS lesions, if present, into a subset of slices determined to be the best MS lesion candidates via Otsu's method. From this preliminary clustering, the modal data values for the tissues can be determined. A Euclidean distance is then used to estimate the fuzzy memberships of each brain voxel for all tissue types and their 50/50 partial volumes. From these estimates, binary discrete and fuzzy MS lesion masks are constructed. Validation is provided by using three synthetic MS lesions brains (mild, moderate and severe) with labeled ground truths. The MS lesions of mild, moderate and severe designations were detected with a sensitivity of 83.2%, and 88.5%, and 94.5%, and with the corresponding Dice similarity coefficient (DSC) of 0.7098, 0.8739, and 0.8266, respectively. The effect of MRI noise is also examined by simulated noise and the application of a bilateral filter in preprocessing.

  15. Investigation of biomechanical behavior of lumbar vertebral segments with dynamic stabilization device using finite element approach

    Science.gov (United States)

    Deoghare, Ashish B.; Kashyap, Siddharth; Padole, Pramod M.

    2013-03-01

    Degenerative disc disease is a major source of lower back pain and significantly alters the biomechanics of the lumbar spine. Dynamic stabilization device is a remedial technique which uses flexible materials to stabilize the affected lumbar region while preserving the natural anatomy of the spine. The main objective of this research work is to investigate the stiffness variation of dynamic stabilization device under various loading conditions under compression, axial rotation and flexion. Three dimensional model of the two segment lumbar spine is developed using computed tomography (CT) scan images. The lumbar structure developed is analyzed in ANSYS workbench. Two types of dynamic stabilization are considered: one with stabilizing device as pedicle instrumentation and second with stabilization device inserted around the inter-vertebral disc. Analysis suggests that proper positioning of the dynamic stabilization device is of paramount significance prior to the surgery. Inserting the device in the posterior region indicates the adverse effects as it shows increase in the deformation of the inter-vertebral disc. Analysis executed by positioning stabilizing device around the inter-vertebral disc yields better result for various stiffness values under compression and other loadings. [Figure not available: see fulltext.

  16. Approaches to automatic parameter fitting in a microscopy image segmentation pipeline: An exploratory parameter space analysis

    Science.gov (United States)

    Held, Christian; Nattkemper, Tim; Palmisano, Ralf; Wittenberg, Thomas

    2013-01-01

    Introduction: Research and diagnosis in medicine and biology often require the assessment of a large amount of microscopy image data. Although on the one hand, digital pathology and new bioimaging technologies find their way into clinical practice and pharmaceutical research, some general methodological issues in automated image analysis are still open. Methods: In this study, we address the problem of fitting the parameters in a microscopy image segmentation pipeline. We propose to fit the parameters of the pipeline's modules with optimization algorithms, such as, genetic algorithms or coordinate descents, and show how visual exploration of the parameter space can help to identify sub-optimal parameter settings that need to be avoided. Results: This is of significant help in the design of our automatic parameter fitting framework, which enables us to tune the pipeline for large sets of micrographs. Conclusion: The underlying parameter spaces pose a challenge for manual as well as automated parameter optimization, as the parameter spaces can show several local performance maxima. Hence, optimization strategies that are not able to jump out of local performance maxima, like the hill climbing algorithm, often result in a local maximum. PMID:23766941

  17. Approaches to automatic parameter fitting in a microscopy image segmentation pipeline: An exploratory parameter space analysis

    Directory of Open Access Journals (Sweden)

    Christian Held

    2013-01-01

    Full Text Available Introduction: Research and diagnosis in medicine and biology often require the assessment of a large amount of microscopy image data. Although on the one hand, digital pathology and new bioimaging technologies find their way into clinical practice and pharmaceutical research, some general methodological issues in automated image analysis are still open. Methods: In this study, we address the problem of fitting the parameters in a microscopy image segmentation pipeline. We propose to fit the parameters of the pipeline′s modules with optimization algorithms, such as, genetic algorithms or coordinate descents, and show how visual exploration of the parameter space can help to identify sub-optimal parameter settings that need to be avoided. Results: This is of significant help in the design of our automatic parameter fitting framework, which enables us to tune the pipeline for large sets of micrographs. Conclusion: The underlying parameter spaces pose a challenge for manual as well as automated parameter optimization, as the parameter spaces can show several local performance maxima. Hence, optimization strategies that are not able to jump out of local performance maxima, like the hill climbing algorithm, often result in a local maximum.

  18. APPROACH TO ESTIMATION OF THE MARKET VOLUME FOR COMPANIES OPERATING IN THE B2B SEGMENT

    Directory of Open Access Journals (Sweden)

    Alla B. Kochergina

    2014-01-01

    Full Text Available This article shows the approach for estimating amount of alive enterprises inRussia. The main focus is on the way of detecting an business-active companiesusing the formal signs. The author proposes some signs for indicating of thebusiness activity. The developed model allows to clarify the amount of active enterprises in stages using those signs. The author provides the approach how to applythis model for different markets.

  19. Tissue segmentation-assisted analysis of fMRI for human motor response: an approach combining artificial neural network and fuzzy C means

    OpenAIRE

    Chiu, MJ; Lin, CC; Chuang, KH; Chen, JH; Huang, KM

    2001-01-01

    The authors have developed an automated algorithm for segmentation of magnetic resonance images (MRI) of the human brain. They investigated the quantitative analysis of tissue-specific human motor response through an approach combining gradient echo functional MRI and automated segmentation analysis. Fifteen healthy volunteers, placed in a 1.5 T clinical MR imager, performed a self-paced finger opposition throughout the activation periods. T1-weighted images (WI), T2WI, and proton density WI ...

  20. Early-Stage White Matter Lesions Detected by Multispectral MRI Segmentation Predict Progressive Cognitive Decline

    NARCIS (Netherlands)

    Jokinen, H.; Goncalves, N.; Vigario, R.; Lipsanen, J.; Fazekas, F.; Schmidt, R.; Barkhof, F.; Madureira, S.; Verdelho, A.; Inzitari, D.; Pantoni, L.; Erkinjuntti, T.

    2015-01-01

    White matter lesions (WML) are the main brain imaging surrogate of cerebral small-vessel disease. A new MRI tissue segmentation method, based on a discriminative clustering approach without explicit model-based added prior, detects partial WML volumes, likely representing very early-stage changes in

  1. A multiple kernel classification approach based on a Quadratic Successive Geometric Segmentation methodology with a fault diagnosis case.

    Science.gov (United States)

    Honório, Leonardo M; Barbosa, Daniele A; Oliveira, Edimar J; Garcia, Paulo A Nepomuceno; Santos, Murillo F

    2018-01-11

    This work presents a new approach for solving classification and learning problems. The Successive Geometric Segmentation technique is applied to encapsulate large datasets by using a series of Oriented Bounding Hyper Box (OBHBs). Each OBHB is obtained through linear separation analysis and each one represents a specific region in a pattern's solution space. Also, each OBHB can be seen as a data abstraction layer and be considered as an individual Kernel. Thus, it is possible by applying a quadratic discriminant function, to assemble a set of nonlinear surfaces separating each desirable pattern. This approach allows working with large datasets using high speed linear analysis tools and yet providing a very accurate non-linear classifier as final result. The methodology was tested using the UCI Machine Learning repository and a Power Transformer Fault Diagnosis real scenario problem. The results were compared with different approaches provided by literature and, finally, the potential and further applications of the methodology were also discussed. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  2. A novel method of protein secondary structure prediction with high segment overlap measure: support vector machine approach.

    Science.gov (United States)

    Hua, S; Sun, Z

    2001-04-27

    We have introduced a new method of protein secondary structure prediction which is based on the theory of support vector machine (SVM). SVM represents a new approach to supervised pattern classification which has been successfully applied to a wide range of pattern recognition problems, including object recognition, speaker identification, gene function prediction with microarray expression profile, etc. In these cases, the performance of SVM either matches or is significantly better than that of traditional machine learning approaches, including neural networks.The first use of the SVM approach to predict protein secondary structure is described here. Unlike the previous studies, we first constructed several binary classifiers, then assembled a tertiary classifier for three secondary structure states (helix, sheet and coil) based on these binary classifiers. The SVM method achieved a good performance of segment overlap accuracy SOV=76.2 % through sevenfold cross validation on a database of 513 non-homologous protein chains with multiple sequence alignments, which out-performs existing methods. Meanwhile three-state overall per-residue accuracy Q(3) achieved 73.5 %, which is at least comparable to existing single prediction methods. Furthermore a useful "reliability index" for the predictions was developed. In addition, SVM has many attractive features, including effective avoidance of overfitting, the ability to handle large feature spaces, information condensing of the given data set, etc. The SVM method is conveniently applied to many other pattern classification tasks in biology. Copyright 2001 Academic Press.

  3. Segmentation of Brain Lesions in MRI and CT Scan Images: A Hybrid Approach Using k-Means Clustering and Image Morphology

    Science.gov (United States)

    Agrawal, Ritu; Sharma, Manisha; Singh, Bikesh Kumar

    2018-01-01

    Manual segmentation and analysis of lesions in medical images is time consuming and subjected to human errors. Automated segmentation has thus gained significant attention in recent years. This article presents a hybrid approach for brain lesion segmentation in different imaging modalities by combining median filter, k means clustering, Sobel edge detection and morphological operations. Median filter is an essential pre-processing step and is used to remove impulsive noise from the acquired brain images followed by k-means segmentation, Sobel edge detection and morphological processing. The performance of proposed automated system is tested on standard datasets using performance measures such as segmentation accuracy and execution time. The proposed method achieves a high accuracy of 94% when compared with manual delineation performed by an expert radiologist. Furthermore, the statistical significance test between lesion segmented using automated approach and that by expert delineation using ANOVA and correlation coefficient achieved high significance values of 0.986 and 1 respectively. The experimental results obtained are discussed in lieu of some recently reported studies.

  4. DIALIGN-TX: greedy and progressive approaches for segment-based multiple sequence alignment

    Directory of Open Access Journals (Sweden)

    Morgenstern Burkhard

    2008-05-01

    Full Text Available Abstract Background DIALIGN-T is a reimplementation of the multiple-alignment program DIALIGN. Due to several algorithmic improvements, it produces significantly better alignments on locally and globally related sequence sets than previous versions of DIALIGN. However, like the original implementation of the program, DIALIGN-T uses a a straight-forward greedy approach to assemble multiple alignments from local pairwise sequence similarities. Such greedy approaches may be vulnerable to spurious random similarities and can therefore lead to suboptimal results. In this paper, we present DIALIGN-TX, a substantial improvement of DIALIGN-T that combines our previous greedy algorithm with a progressive alignment approach. Results Our new heuristic produces significantly better alignments, especially on globally related sequences, without increasing the CPU time and memory consumption exceedingly. The new method is based on a guide tree; to detect possible spurious sequence similarities, it employs a vertex-cover approximation on a conflict graph. We performed benchmarking tests on a large set of nucleic acid and protein sequences For protein benchmarks we used the benchmark database BALIBASE 3 and an updated release of the database IRMBASE 2 for assessing the quality on globally and locally related sequences, respectively. For alignment of nucleic acid sequences, we used BRAliBase II for global alignment and a newly developed database of locally related sequences called DIRM-BASE 1. IRMBASE 2 and DIRMBASE 1 are constructed by implanting highly conserved motives at random positions in long unalignable sequences. Conclusion On BALIBASE3, our new program performs significantly better than the previous program DIALIGN-T and outperforms the popular global aligner CLUSTAL W, though it is still outperformed by programs that focus on global alignment like MAFFT, MUSCLE and T-COFFEE. On the locally related test sets in IRMBASE 2 and DIRM-BASE 1, our method

  5. Automated segmentation of 3D anatomical structures on CT images by using a deep convolutional network based on end-to-end learning approach

    Science.gov (United States)

    Zhou, Xiangrong; Takayama, Ryosuke; Wang, Song; Zhou, Xinxin; Hara, Takeshi; Fujita, Hiroshi

    2017-02-01

    We have proposed an end-to-end learning approach that trained a deep convolutional neural network (CNN) for automatic CT image segmentation, which accomplished a voxel-wised multiple classification to directly map each voxel on 3D CT images to an anatomical label automatically. The novelties of our proposed method were (1) transforming the anatomical structures segmentation on 3D CT images into a majority voting of the results of 2D semantic image segmentation on a number of 2D-slices from different image orientations, and (2) using "convolution" and "deconvolution" networks to achieve the conventional "coarse recognition" and "fine extraction" functions which were integrated into a compact all-in-one deep CNN for CT image segmentation. The advantage comparing to previous works was its capability to accomplish real-time image segmentations on 2D slices of arbitrary CT-scan-range (e.g. body, chest, abdomen) and produced correspondingly-sized output. In this paper, we propose an improvement of our proposed approach by adding an organ localization module to limit CT image range for training and testing deep CNNs. A database consisting of 240 3D CT scans and a human annotated ground truth was used for training (228 cases) and testing (the remaining 12 cases). We applied the improved method to segment pancreas and left kidney regions, respectively. The preliminary results showed that the accuracies of the segmentation results were improved significantly (pancreas was 34% and kidney was 8% increased in Jaccard index from our previous results). The effectiveness and usefulness of proposed improvement for CT image segmentations were confirmed.

  6. Management of anterior segment penetrating injuries with traumatic cataract by pentagon approach in paediatric age group: Constraints and outcome

    Directory of Open Access Journals (Sweden)

    Parihar Jitendra

    2000-01-01

    Full Text Available Purpose: To evaluate the efficacy of multiple combined procedure (Pentagon approach as single-step secondary repair in cases of extensive keratolenticular trauma in paediatric age group. Methods: Retrospective evaluation of 18 patients of penetrating injuries with sclero-keratolenticular trauma, who underwent multiple procedure as single-step secondary repair by a single team of two surgeons during a 4 year period. Surgical procedure included reconstruction of anterior segment, synechiolysis, excision of membrane, lensectomy, open sky vitrectomy, PC IOL implantation over frill and penetrating keratoplasty. Meticulous antiamblyopia measures were applied in all cases. Results: Extensive vasoproliferative membrane, complicated cataract and anterior vitreous condensation were significant intra-operative hurdles. Moderate uveitis, secondary glaucoma, persistent epithelial defects were problems noted. Eleven (61.22% patients attained good visual outcome. Regrafting was required in remaining cases due to delayed graft failure. Conclusion: Despite being a highly complex technique, Pentagon approach provides effective management profile in terms of graft success and functional outcome, especially in keratolenticular trauma, in children.

  7. The multiscale importance of road segments in a network disruption scenario: a risk-based approach.

    Science.gov (United States)

    Freiria, Susana; Tavares, Alexandre O; Pedro Julião, Rui

    2015-03-01

    This article addresses the problem of the multiscale importance of road networks, with the aim of helping to establish a more resilient network in the event of a road disruption scenario. A new model for identifying the most important roads is described and applied on a local and regional scale. The work presented here represents a step forward, since it focuses on the interaction between identifying the most important roads in a network that connect people and health services, the specificity of the natural hazards that threaten the normal functioning of the network, and an assessment of the consequences of three real-world interruptions from a multiscale perspective. The case studies concern three different past events: road interruptions due to a flood, a forest fire, and a mass movement. On the basis of the results obtained, it is possible to establish the roads for which risk management should be a priority. The multiscale perspective shows that in a road interruption the regional system may have the capacity to reorganize itself, although the interruption may have consequences for local dynamics. Coordination between local and regional scales is therefore important. The model proposed here allows for the scaling of emergency response facilities and human and physical resources. It represents an innovative approach to defining priorities, not only in the prevention phase but also in terms of the response to natural disasters, such as awareness of the consequences of road disruption for the rescue services sent out to local communities. © 2014 Society for Risk Analysis.

  8. 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...

  9. Classification and evaluation strategies of auto-segmentation approaches for PET: Report of AAPM task group No. 211.

    Science.gov (United States)

    Hatt, Mathieu; Lee, John A; Schmidtlein, Charles R; Naqa, Issam El; Caldwell, Curtis; De Bernardi, Elisabetta; Lu, Wei; Das, Shiva; Geets, Xavier; Gregoire, Vincent; Jeraj, Robert; MacManus, Michael P; Mawlawi, Osama R; Nestle, Ursula; Pugachev, Andrei B; Schöder, Heiko; Shepherd, Tony; Spezi, Emiliano; Visvikis, Dimitris; Zaidi, Habib; Kirov, Assen S

    2017-06-01

    on advanced image analysis paradigms provide generally more accurate segmentation than approaches based on PET activity thresholds, particularly for realistic configurations. However, this may not be the case for simple shape lesions in situations with a narrower range of parameters, where simpler methods may also perform well. Recent algorithms which employ some type of consensus or automatic selection between several PET-AS methods have potential to overcome the limitations of the individual methods when appropriately trained. In either case, accuracy evaluation is required for each different PET scanner and scanning and image reconstruction protocol. For the simpler, less robust approaches, adaptation to scanning conditions, tumor type, and tumor location by optimization of parameters is necessary. The results from the method evaluation stage can be used to estimate the contouring uncertainty. All PET-AS contours should be critically verified by a physician. A standard test, i.e., a benchmark dedicated to evaluating both existing and future PET-AS algorithms needs to be designed, to aid clinicians in evaluating and selecting PET-AS algorithms and to establish performance limits for their acceptance for clinical use. The initial steps toward designing and building such a standard are undertaken by the task group members. © 2017 American Association of Physicists in Medicine.

  10. Comparison of Lower Limb Segments Kinematics in a Taekwondo Kick. An Approach to the Proximal to Distal Motion

    Directory of Open Access Journals (Sweden)

    Estevan Isaac

    2015-09-01

    Full Text Available In taekwondo, there is a lack of consensus about how the kick sequence occurs. The aim of this study was to analyse the peak velocity (resultant and value in each plane of lower limb segments (thigh, shank and foot, and the time to reach this peak velocity in the kicking lower limb during the execution of the roundhouse kick technique. Ten experienced taekwondo athletes (five males and five females; mean age of 25.3 ±5.1 years; mean experience of 12.9 ±5.3 years participated voluntarily in this study performing consecutive kicking trials to a target located at their sternum height. Measurements for the kinematic analysis were performed using two 3D force plates and an eight camera motion capture system. The results showed that the proximal segment reached a lower peak velocity (resultant and in each plane than distal segments (except the peak velocity in the frontal plane where the thigh and shank presented similar values, with the distal segment taking the longest to reach this peak velocity (p < 0.01. Also, at the instant every segment reached the peak velocity, the velocity of the distal segment was higher than the proximal one (p < 0.01. It provides evidence about the sequential movement of the kicking lower limb segments. In conclusion, during the roundhouse kick in taekwondo inter-segment motion seems to be based on a proximo-distal pattern.

  11. The segmented arch approach: a method for orthodontic treatment of a severe Class III open-bite malocclusion.

    Science.gov (United States)

    Espinar-Escalona, Eduardo; Barrera-Mora, José María; Llamas-Carreras, José María; Ruiz-Navarro, María Belén

    2013-02-01

    An open bite is a common malocclusion, and it is generally associated with several linked etiologic factors. When establishing the treatment plan, it is essential to consider every aspect of the various etiologic causes and their evolution; this will help to correct it. This article reports the case of a girl aged 10.7 years with a skeletal Class III malocclusion and an open bite. The treatment mechanics were based on compensatory dental changes performed to close the bite and correct the skeletal Class III malocclusion. The patient had a deep maxillary deficiency, and the lower facial third was severely enlarged. In this article, we aimed to describe a simple mechanical approach that will close the bite through changes in the occlusal plane (segmentation of arches). It is an extremely simple method that is easily tolerated by the patient. It not only closes the bite effectively but also helps to correct the unilateral or bilateral lack of occlusal interdigitation between the dental arches. A Class III patient with an anterior open bite is shown in this article to illustrate the effectiveness of these treatment mechanics. Copyright © 2013 American Association of Orthodontists. Published by Mosby, Inc. All rights reserved.

  12. a segmentation approach

    African Journals Online (AJOL)

    kirstam

    the United States of America (USA), while minimal research has been conducted in African countries. While there is a negative and grounded perception surrounding black diners being poor tippers in the USA, hardly any research has focused on the dining or tipping behaviour of this dining market from a developing ...

  13. Multi-parametric (ADC/PWI/T2-w) image fusion approach for accurate semi-automatic segmentation of tumorous regions in glioblastoma multiforme.

    Science.gov (United States)

    Fathi Kazerooni, Anahita; Mohseni, Meysam; Rezaei, Sahar; Bakhshandehpour, Gholamreza; Saligheh Rad, Hamidreza

    2015-02-01

    Glioblastoma multiforme (GBM) brain tumor is heterogeneous in nature, so its quantification depends on how to accurately segment different parts of the tumor, i.e. viable tumor, edema and necrosis. This procedure becomes more effective when metabolic and functional information, provided by physiological magnetic resonance (MR) imaging modalities, like diffusion-weighted-imaging (DWI) and perfusion-weighted-imaging (PWI), is incorporated with the anatomical magnetic resonance imaging (MRI). In this preliminary tumor quantification work, the idea is to characterize different regions of GBM tumors in an MRI-based semi-automatic multi-parametric approach to achieve more accurate characterization of pathogenic regions. For this purpose, three MR sequences, namely T2-weighted imaging (anatomical MR imaging), PWI and DWI of thirteen GBM patients, were acquired. To enhance the delineation of the boundaries of each pathogenic region (peri-tumoral edema, viable tumor and necrosis), the spatial fuzzy C-means algorithm is combined with the region growing method. The results show that exploiting the multi-parametric approach along with the proposed semi-automatic segmentation method can differentiate various tumorous regions with over 80 % sensitivity, specificity and dice score. The proposed MRI-based multi-parametric segmentation approach has the potential to accurately segment tumorous regions, leading to an efficient design of the pre-surgical treatment planning.

  14. Charisma: an integrated approach to automatic H&E-stained skeletal muscle cell segmentation using supervised learning and novel robust clump splitting.

    Science.gov (United States)

    Janssens, Thomas; Antanas, Laura; Derde, Sarah; Vanhorebeek, Ilse; Van den Berghe, Greet; Güiza Grandas, Fabian

    2013-12-01

    Histological image analysis plays a key role in understanding the effects of disease and treatment responses at the cellular level. However, evaluating histology images by hand is time-consuming and subjective. While semi-automatic and automatic approaches for image segmentation give acceptable results in some branches of histological image analysis, until now this has not been the case when applied to skeletal muscle histology images. We introduce Charisma, a new top-down cell segmentation framework for histology images which combines image processing techniques, a supervised trained classifier and a novel robust clump splitting algorithm. We evaluate our framework on real-world data from intensive care unit patients. Considering both segmentation and cell property distributions, the results obtained by our method correspond well to the ground truth, outperforming other examined methods. Copyright © 2013 Elsevier B.V. All rights reserved.

  15. The basis for improving and reforming long-term care. Part 4: identifying meaningful improvement approaches (segment 2).

    Science.gov (United States)

    Levenson, Steven A

    2010-03-01

    While many aspects of nursing home care have improved over time, numerous issues persist. Presently, a potpourri of approaches and a push to "fix" the problem have overshadowed efforts to correctly define the problems and identify their diverse causes. This fourth and final article in the series (divided between last month's issue and this one) recommends strategies to make sense of improvement and reform efforts. This month's concluding segment covers additional proposed approaches. Despite the challenges of the current environment, all of the proposed strategies could potentially be applied with little or no delay. Despite having brought vast increases in knowledge, the research effort may be losing its traction as a formidable force for meaningful change. It is necessary to rethink the questions being asked and the scope of answers being sought. A shift to overcoming implementation challenges is needed. In addition, it is essential to address issues of jurisdiction (the apparent "ownership" of assessment and decision making over patient problems or body parts) and reductionism (the excessive management of these issues and problems without proper context) that result in fragmented and problematic care. Issues of knowledge and skill also need to be addressed, with greater emphasis on key generic and technical competencies of staff and practitioners, in addition to factual knowledge. There is a need to rethink the approach to measuring performance and trying to improve quality of care and services. There are significant limits to trying to use quality measures to improve outcomes and performance. Ultimately, vast improvement is needed in applying care principles and practices, independent of regulatory sources. Reimbursement needs to be revamped so that it helps promote care that is consistent with human biology and other key concepts. Finally, improving long-term care will require a coordinated societal effort. All social institutions and health care settings need

  16. Anterior versus posterior approach in Lenke 5C adolescent idiopathic scoliosis: a meta-analysis of fusion segments and radiological outcomes.

    Science.gov (United States)

    Luo, Ming; Wang, Wengang; Shen, Mingkui; Xia, Lei

    2016-07-11

    Radiological outcomes between anterior and posterior approach in Lenke 5C curves were still controversial. Meta-analysis on published articles to compare fusion segments and radiological outcomes between the two surgical approaches was performed. Electronic database was conducted for searching studies concerning the anterior versus posterior approach in Lenke 5C curves. After quality assessment, data of means, standard deviations, and sample sizes were extracted. RevMan 5.3 was adopted for data analysis. Seven case-control studies involving 308 Lenke 5C AIS patients were identified in the meta-analysis. No significant differences were noted in correction rate of thoracolumbar/lumbar curve (95 % CI -6.02 to 4.32, P = 0.75) and incidence of proximal junctional kyphosis (95 % CI 0.12 to 7.19, P = 0.94) of final follow-up, in change values of thoracolumbar/lumbar curve (95 % CI -3.28 to 7.19, P = 0.46) and thoracic kyphosis (95 % CI -4.10 to 0.13, P = 0.07). The anterior approach represented a significant shorter fusion segments compared to posterior approach (95 % CI -1.72 to -0.71, P < 0.00001). The posterior approach obtained a larger increasing Cobb angle of lumbar lordosis than the anterior approach (95 % CI -6.06 to -0.61, P = 0.02). The anterior and posterior approach can obtain comparable coronal correction, change values of thoracic kyphosis, and incidence of proximal junctional kyphosis. The anterior approach saves approximate one more fusion segment, and the posterior approach can obtain a larger increasing Cobb angle of lumbar lordosis, from preoperation to final follow-up. The article type of this study is meta-analysis and prospective registration is not required.

  17. Vessel discoloration detection in malarial retinopathy

    Science.gov (United States)

    Agurto, C.; Nemeth, S.; Barriga, S.; Soliz, P.; MacCormick, I.; Taylor, T.; Harding, S.; Lewallen, S.; Joshi, V.

    2016-03-01

    Cerebral malaria (CM) is a life-threatening clinical syndrome associated with malarial infection. It affects approximately 200 million people, mostly sub-Saharan African children under five years of age. Malarial retinopathy (MR) is a condition in which lesions such as whitening and vessel discoloration that are highly specific to CM appear in the retina. Other unrelated diseases can present with symptoms similar to CM, therefore the exact nature of the clinical symptoms must be ascertained in order to avoid misdiagnosis, which can lead to inappropriate treatment and, potentially, death. In this paper we outline the first system to detect the presence of discolored vessels associated with MR as a means to improve the CM diagnosis. We modified and improved our previous vessel segmentation algorithm by incorporating the `a' channel of the CIELab color space and noise reduction. We then divided the segmented vasculature into vessel segments and extracted features at the wall and in the centerline of the segment. Finally, we used a regression classifier to sort the segments into discolored and not-discolored vessel classes. By counting the abnormal vessel segments in each image, we were able to divide the analyzed images into two groups: normal and presence of vessel discoloration due to MR. We achieved an accuracy of 85% with sensitivity of 94% and specificity of 67%. In clinical practice, this algorithm would be combined with other MR retinal pathology detection algorithms. Therefore, a high specificity can be achieved. By choosing a different operating point in the ROC curve, our system achieved sensitivity of 67% with specificity of 100%.

  18. Segmental neurofibromatosis and malignancy.

    Science.gov (United States)

    Dang, Julie D; Cohen, Philip R

    2010-01-01

    Segmental neurofibromatosis is an uncommon variant of neurofibromatosis type I characterized by neurofibromas and/or café-au-lait macules localized to one sector of the body. Although patients with neurofibromatosis type I have an associated increased risk of certain malignancies, malignancy has only occasionally been reported in patients with segmental neurofibromatosis. The published reports of patients with segmental neurofibromatosis who developed malignancy were reviewed and the characteristics of these patients and their cancers were summarized. Ten individuals (6 women and 4 men) with segmental neurofibromatosis and malignancy have been reported. The malignancies include malignant peripheral nerve sheath tumor (3), malignant melanoma (2), breast cancer (1), colon cancer (1), gastric cancer (1), lung cancer (1), and Hodgkin lymphoma (1). The most common malignancies in patients with segmental neurofibromatosis are derived from neural crest cells: malignant peripheral nerve sheath tumor and malignant melanoma. The incidence of malignancy in patients with segmental neurofibromatosis may approach that of patients with neurofibromatosis type I.

  19. Vessel tree extraction using locally optimal paths

    DEFF Research Database (Denmark)

    Lo, Pechin Chien Pau; van Ginneken, Bram; de Bruijne, Marleen

    2010-01-01

    This paper proposes a method to extract vessel trees by continually extending detected branches with locally optimal paths. Our approach uses a cost function from a multi scale vessel enhancement filter. Optimal paths are selected based on rules that take into account the geometric characteristics...... of the vessel tree. Experiments were performed on 10 low dose chest CT scans for which the pulmonary vessel trees were extracted. The proposed method is shown to extract a better connected vessel tree and extract more of the small peripheral vessels in comparison to applying a threshold on the output...

  20. Multi-Feature Segmentation for High-Resolution Polarimetric SAR Data Based on Fractal Net Evolution Approach

    Directory of Open Access Journals (Sweden)

    Qihao Chen

    2017-06-01

    Full Text Available Segmentation techniques play an important role in understanding high-resolution polarimetric synthetic aperture radar (PolSAR images. PolSAR image segmentation is widely used as a preprocessing step for subsequent classification, scene interpretation and extraction of surface parameters. However, speckle noise and rich spatial features of heterogeneous regions lead to blurred boundaries of high-resolution PolSAR image segmentation. A novel segmentation algorithm is proposed in this study in order to address the problem and to obtain accurate and precise segmentation results. This method integrates statistical features into a fractal net evolution algorithm (FNEA framework, and incorporates polarimetric features into a simple linear iterative clustering (SLIC superpixel generation algorithm. First, spectral heterogeneity in the traditional FNEA is substituted by the G0 distribution statistical heterogeneity in order to combine the shape and statistical features of PolSAR data. The statistical heterogeneity between two adjacent image objects is measured using a log likelihood function. Second, a modified SLIC algorithm is utilized to generate compact superpixels as the initial samples for the G0 statistical model, which substitutes the polarimetric distance of the Pauli RGB composition for the CIELAB color distance. The segmentation results were obtained by weighting the G0 statistical feature and the shape features, based on the FNEA framework. The validity and applicability of the proposed method was verified with extensive experiments on simulated data and three real-world high-resolution PolSAR images from airborne multi-look ESAR, spaceborne single-look RADARSAT-2, and multi-look TerraSAR-X data sets. The experimental results indicate that the proposed method obtains more accurate and precise segmentation results than the other methods for high-resolution PolSAR images.

  1. 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.

  2. A comprehensive approach to the segmentation of multichannel three-dimensional MR brain images in multiple sclerosis.

    Science.gov (United States)

    Datta, Sushmita; Narayana, Ponnada A

    2013-01-01

    Accurate classification and quantification of brain tissues is important for monitoring disease progression, measurement of atrophy, and correlating magnetic resonance (MR) measures with clinical disability. Classification of MR brain images in the presence of lesions, such as multiple sclerosis (MS), is particularly challenging. Images obtained with lower resolution often suffer from partial volume averaging leading to false classifications. While partial volume averaging can be reduced by acquiring volumetric images at high resolution, image segmentation and quantification can be technically challenging. In this study, we integrated the brain anatomical knowledge with non-parametric and parametric statistical classifiers for automatically classifying tissues and lesions on high resolution multichannel three-dimensional images acquired on 60 MS brains. The results of automatic lesion segmentation were reviewed by the expert. The agreement between results obtained by the automated analysis and the expert was excellent as assessed by the quantitative metrics, low absolute volume difference percent (36.18 ± 34.90), low average symmetric surface distance (1.64 mm ± 1.30 mm), high true positive rate (84.75 ± 12.69), and low false positive rate (34.10 ± 16.00). The segmented results were also in close agreement with the corrected results as assessed by Bland-Altman and regression analyses. Finally, our lesion segmentation was validated using the MS lesion segmentation grand challenge dataset (MICCAI 2008).

  3. A comprehensive approach to the segmentation of multichannel three-dimensional MR brain images in multiple sclerosis☆

    Science.gov (United States)

    Datta, Sushmita; Narayana, Ponnada A.

    2013-01-01

    Accurate classification and quantification of brain tissues is important for monitoring disease progression, measurement of atrophy, and correlating magnetic resonance (MR) measures with clinical disability. Classification of MR brain images in the presence of lesions, such as multiple sclerosis (MS), is particularly challenging. Images obtained with lower resolution often suffer from partial volume averaging leading to false classifications. While partial volume averaging can be reduced by acquiring volumetric images at high resolution, image segmentation and quantification can be technically challenging. In this study, we integrated the brain anatomical knowledge with non-parametric and parametric statistical classifiers for automatically classifying tissues and lesions on high resolution multichannel three-dimensional images acquired on 60 MS brains. The results of automatic lesion segmentation were reviewed by the expert. The agreement between results obtained by the automated analysis and the expert was excellent as assessed by the quantitative metrics, low absolute volume difference percent (36.18 ± 34.90), low average symmetric surface distance (1.64 mm ± 1.30 mm), high true positive rate (84.75 ± 12.69), and low false positive rate (34.10 ± 16.00). The segmented results were also in close agreement with the corrected results as assessed by Bland–Altman and regression analyses. Finally, our lesion segmentation was validated using the MS lesion segmentation grand challenge dataset (MICCAI 2008). PMID:24179773

  4. An SPM8-Based Approach for Attenuation Correction Combining Segmentation and Nonrigid Template Formation: Application to Simultaneous PET/MR Brain Imaging

    DEFF Research Database (Denmark)

    Izquierdo-Garcia, David; Hansen, Adam E; Förster, Stefan

    2014-01-01

    /MR scanners. METHODS: Coregistered anatomic MR and CT images of 15 glioblastoma subjects were used to generate the templates. The MR images from these subjects were first segmented into 6 tissue classes (gray matter, white matter, cerebrospinal fluid, bone, soft tissue, and air), which were then nonrigidly......UNLABELLED: We present an approach for head MR-based attenuation correction (AC) based on the Statistical Parametric Mapping 8 (SPM8) software, which combines segmentation- and atlas-based features to provide a robust technique to generate attenuation maps (μ maps) from MR data in integrated PET...... coregistered using a diffeomorphic approach. A similar procedure was used to coregister the anatomic MR data for a new subject to the template. Finally, the CT-like images obtained by applying the inverse transformations were converted to linear attenuation coefficients to be used for AC of PET data...

  5. A modified shifted means-based segmentation approach to detect active regions and coronal holes in the solar dynamics observatory images

    Science.gov (United States)

    Suresh, Santosh; Dube, Roger; Glenn, Chance, Sr.

    2012-05-01

    Solar images taken at different wavelengths enable scientists to visualize and analyze the suns activities. The Solar Dynamics Observatory (SDO) provides high-resolution images of the sun, with cadence in seconds, taken at varying wavelengths, resulting in finely detailed, almost continuous data for researcher's examination. We propose an approach to find active regions and coronal holes that involves shifted means based segmentation, and voting based edge linking to link fragments combined with Moore's neighbor tracing algorithm to highlight the regions of interest. This approach is illustrated by using the images taken by the AIA telescopes onboard of the SDO mission. We obtain a segmented image that clearly isolates the active regions. Moreover this method is comparatively faster than the commonly used fuzzy logic based methods. This method is capable of forming a foundation for the analysis of various other features of the sun like detection of prominences.

  6. Intracoronary Compared to Intravenous Abciximab in Patients with ST Segment Elevation Myocardial Infarction Treated with Primary Percutaneous Coronary Intervention Reduces Mortality, Target Vessel Revascularization and Reinfarction after 1 Year

    DEFF Research Database (Denmark)

    Iversen, Allan Zeeberg; Galatius, Soeren; Abildgaard, Ulrik

    2011-01-01

    to the standard intravenous (IV) administration. We have previously reported reduced short-term mortality and need for target vessel revascularization (TVR) with the IC route. We now present long-term data from our randomized trial on IC versus IV abciximab in pPCI-treated STEMI patients. Methods: A total of 355...

  7. Automatic Detection and Distinction of Retinal Vessel Bifurcations and Crossings in Colour Fundus Photography

    Directory of Open Access Journals (Sweden)

    Harry Pratt

    2017-12-01

    Full Text Available The analysis of retinal blood vessels present in fundus images, and the addressing of problems such as blood clot location, is important to undertake accurate and appropriate treatment of the vessels. Such tasks are hampered by the challenge of accurately tracing back problems along vessels to their source. This is due to the unresolved issue of distinguishing automatically between vessel bifurcations and vessel crossings in colour fundus photographs. In this paper, we present a new technique for addressing this problem using a convolutional neural network approach to firstly locate vessel bifurcations and crossings and then to classifying them as either bifurcations or crossings. Our method achieves high accuracies for junction detection and classification on the DRIVE dataset and we show further validation on an unseen dataset from which no data has been used for training. Combined with work in automated segmentation, this method has the potential to facilitate: reconstruction of vessel topography, classification of veins and arteries and automated localisation of blood clots and other disease symptoms leading to improved management of eye disease.

  8. A model-based approach for estimation of changes in lumbar segmental kinematics associated with alterations in trunk muscle forces.

    Science.gov (United States)

    Shojaei, Iman; Arjmand, Navid; Meakin, Judith R; Bazrgari, Babak

    2017-10-06

    The kinematics information from imaging, if combined with optimization-based biomechanical models, may provide a unique platform for personalized assessment of trunk muscle forces (TMFs). Such a method, however, is feasible only if differences in lumbar spine kinematics due to differences in TMFs can be captured by the current imaging techniques. A finite element model of the spine within an optimization procedure was used to estimate segmental kinematics of lumbar spine associated with five different sets of TMFs. Each set of TMFs was associated with a hypothetical trunk neuromuscular strategy that optimized one aspect of lower back biomechanics. For each set of TMFs, the segmental kinematics of lumbar spine was estimated for a single static trunk flexed posture involving, respectively, 40° and 10° of thoracic and pelvic rotations. Minimum changes in the angular and translational deformations of a motion segment with alterations in TMFs ranged from 0° to 0.7° and 0 mm to 0.04 mm, respectively. Maximum changes in the angular and translational deformations of a motion segment with alterations in TMFs ranged from 2.4° to 7.6° and 0.11 mm to 0.39 mm, respectively. The differences in kinematics of lumbar segments between each combination of two sets of TMFs in 97% of cases for angular deformation and 55% of cases for translational deformation were within the reported accuracy of current imaging techniques. Therefore, it might be possible to use image-based kinematics of lumbar segments along with computational modeling for personalized assessment of TMFs. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Improving Segmentation of 3D Retina Layers Based on Graph Theory Approach for Low Quality OCT Images

    Directory of Open Access Journals (Sweden)

    Stankiewicz Agnieszka

    2016-06-01

    Full Text Available This paper presents signal processing aspects for automatic segmentation of retinal layers of the human eye. The paper draws attention to the problems that occur during the computer image processing of images obtained with the use of the Spectral Domain Optical Coherence Tomography (SD OCT. Accuracy of the retinal layer segmentation for a set of typical 3D scans with a rather low quality was shown. Some possible ways to improve quality of the final results are pointed out. The experimental studies were performed using the so-called B-scans obtained with the OCT Copernicus HR device.

  10. Optic Disc Segmentation by Balloon Snake with Texture from Color Fundus Image

    Science.gov (United States)

    Sun, Jinyang; Luan, Fangjun; Wu, Hanhui

    2015-01-01

    A well-established method for diagnosis of glaucoma is the examination of the optic nerve head based on fundus image as glaucomatous patients tend to have larger cup-to-disc ratios. The difficulty of optic segmentation is due to the fuzzy boundaries and peripapillary atrophy (PPA). In this paper a novel method for optic nerve head segmentation is proposed. It uses template matching to find the region of interest (ROI). The method of vessel erasing in the ROI is based on PDE inpainting which will make the boundary smoother. A novel optic disc segmentation approach using image texture is explored in this paper. A cluster method based on image texture is employed before the optic disc segmentation step to remove the edge noise such as cup boundary and vessels. We replace image force in the snake with image texture and the initial contour of the balloon snake is inside the optic disc to avoid the PPA. The experimental results show the superior performance of the proposed method when compared to some traditional segmentation approaches. An average segmentation dice coefficient of 94% has been obtained. PMID:25861249

  11. Optic Disc Segmentation by Balloon Snake with Texture from Color Fundus Image

    Directory of Open Access Journals (Sweden)

    Jinyang Sun

    2015-01-01

    Full Text Available A well-established method for diagnosis of glaucoma is the examination of the optic nerve head based on fundus image as glaucomatous patients tend to have larger cup-to-disc ratios. The difficulty of optic segmentation is due to the fuzzy boundaries and peripapillary atrophy (PPA. In this paper a novel method for optic nerve head segmentation is proposed. It uses template matching to find the region of interest (ROI. The method of vessel erasing in the ROI is based on PDE inpainting which will make the boundary smoother. A novel optic disc segmentation approach using image texture is explored in this paper. A cluster method based on image texture is employed before the optic disc segmentation step to remove the edge noise such as cup boundary and vessels. We replace image force in the snake with image texture and the initial contour of the balloon snake is inside the optic disc to avoid the PPA. The experimental results show the superior performance of the proposed method when compared to some traditional segmentation approaches. An average segmentation dice coefficient of 94% has been obtained.

  12. Multimodal Segmentation of Optic Disc and Cup from SD-OCT and Color Fundus Photographs Using a Machine-Learning Graph-Based Approach

    Science.gov (United States)

    Miri, Mohammad Saleh; Abràmoff, Michael D.; Lee, Kyungmoo; Niemeijer, Meindert; Wang, Jui-Kai; Kwon, Young H.

    2015-01-01

    In this work, a multimodal approach is proposed to use the complementary information from fundus photographs and spectral domain optical coherence tomography (SD-OCT) volumes in order to segment the optic disc and cup boundaries. The problem is formulated as an optimization problem where the optimal solution is obtained using a machine-learning theoretical graph-based method. In particular, first the fundus photograph is registered to the 2D projection of the SD-OCT volume. Three in-region cost functions are designed using a random forest classifier corresponding to three regions of cup, rim, and background. Next, the volumes are resampled to create radial scans in which the Bruch’s Membrane Opening (BMO) endpoints are easier to detect. Similar to in-region cost function design, the disc-boundary cost function is designed using a random forest classifier for which the features are created by applying the Haar Stationary Wavelet Transform (SWT) to the radial projection image. A multisurface graph-based approach utilizes the in-region and disc-boundary cost images to segment the boundaries of optic disc and cup under feasibility constraints. The approach is evaluated on 25 multimodal image pairs from 25 subjects in a leave-one-out fashion (by subject). The performances of the graph-theoretic approach using three sets of cost functions are compared: 1) using unimodal (OCT only) in-region costs, 2) using multimodal in-region costs, and 3) using multimodal in-region and disc-boundary costs. Results show that the multimodal approaches outperform the unimodal approach in segmenting the optic disc and cup. PMID:25781623

  13. 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...

  14. Segmental neurofibromatosis

    OpenAIRE

    Galhotra, Virat; Sheikh, Soheyl; Jindal, Sanjeev; Singla, Anshu

    2014-01-01

    Segmental neurofibromatosis is a rare disorder, characterized by neurofibromas or cafι-au-lait macules limited to one region of the body. Its occurrence on the face is extremely rare and only few cases of segmental neurofibromatosis over the face have been described so far. We present a case of segmental neurofibromatosis involving the buccal mucosa, tongue, cheek, ear, and neck on the right side of the face.

  15. A study of reactor vessel integrity assessment

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jae Hoon [Korea Institute of Nuclear Safety, Taejon (Korea, Republic of); Kim, Jong Kyung; Shin, Chang Ho; Seo, Bo Kyun [Hanyang Univ., Seoul (Korea, Republic of)

    1999-02-15

    The fast neutron fluence at the Reactor Pressure Vessel(RPV) of KNGR designed for 60 years lifetime was calculated by full-scope Monte Carlo simulation for reactor vessel integrity assessment. KNGR core geometry was modeled on a three-dimensional representation of the one-sixteenth of the reactor in-vessel component. Each fuel assemblies were modeled explicitly, and each fuel pins were axially divided into 5 segments. The maximum flux of 4.3 x 10{sup 10} neutrons/cm{sup 2}. sec at the RPV was obtained by tallying neutrons crossing the beltline of inner surface of the RPV.

  16. Vessel Operator System

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Operator cards are required for any operator of a charter/party boat and or a commercial vessel (including carrier and processor vessels) issued a vessel permit from...

  17. Multiscale FEM modeling of vascular tone: from membrane currents to vessel mechanics.

    Science.gov (United States)

    Kapela, Adam; Tsoukias, Nikolaos Michael

    2011-12-01

    Regulation of vascular tone is a complex process that remains poorly understood. Here, we present our recent efforts for the development of physiologically realistic models of arterial segments for the analysis of vasoreactivity in health and disease. Multiscale modeling integrates intracellular and cell membrane components into whole-cell models of calcium and membrane potential dynamics. Single-cell models of vascular cells are combined into a multicellular model of the vascular wall, and vessel wall biomechanics are integrated with calcium dynamics in the smooth muscle layer. At each scale, continuum models using finite element method can account for spatial heterogeneity in calcium signaling and for nonuniform deformations of a vessel segment. The outlined approach can be used to investigate cellular mechanisms underlying altered vasoreactivity in hypertension.

  18. Segmental Neurofibromatosis

    Directory of Open Access Journals (Sweden)

    Yesudian Devakar

    1997-01-01

    Full Text Available Segmental neurofibromatosis is a rare variant of neurofibromatosis in which the lesions are confined to one segment or dermatome of the body. They resemble classical neurofibromas in their morphology, histopathology and electron microscopy. However, systemic associations are usually absent. We report one such case with these classical features.

  19. 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.

  20. Analysis of the master curve approach on the fracture toughness properties of SA508 Gr.4N Ni-Mo-Cr low alloy steels for reactor pressure vessels

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Ki-Hyoung, E-mail: shirimp@kaist.ac.kr [Department of Materials Science and Engineering, KAIST, Daejeon 305-701 (Korea, Republic of); Kim, Min-Chul; Lee, Bong-Sang [Nuclear Materials Research Division, KAERI, Daejeon 305-353 (Korea, Republic of); Wee, Dang-Moon [Department of Materials Science and Engineering, KAIST, Daejeon 305-701 (Korea, Republic of)

    2010-06-15

    This study aims at assessing the fracture toughness behavior of tempered martensitic Ni-Mo-Cr low alloy steels for reactor pressure vessels in a transition temperature region using a master curve approach. The fracture toughness tests for model alloys with various chemical compositions were carried out following ASTM E1921-08. The microstructures, tensile properties, and Charpy impact toughness were also evaluated. Alloying elements such as Ni, Cr, and Mo affected the mechanical properties of alloys from changes in the phase fraction and precipitation behavior. In the fracture toughness test results, the data sets showed a deviation from the median curve and a smaller scatter than that of the prediction of the ASTM standard, especially in the lower transition region. The exponential parameter of the master curve equation was adjusted by an exponential fitting to data sets for expressing well the temperature dependency of the fracture toughness. The adjusted parameter provided good agreement for data distribution and the independence of T{sub 0} from test temperatures through an overall temperature range in contrast with the results from the standard master curve.

  1. Degloving Injuries of the Oral Cavity Change the Operative Approach to Fractures of the Anterior Segment of the Mandible

    OpenAIRE

    Pollock, Richard A.; Huber, Katherine M.; Van Sickels, Joseph E.

    2011-01-01

    No report to date describes the added risk traumatic, degloving injuries of the oral cavity may pose when treating fractures of the mandible. The authors describe the oral degloving injury, characterized by separation of periosteum and soft tissue of the anterior floor of the mouth from the inner cortex of the anterior segment. Vascular anatomy of the floor of the mouth is reviewed as a prelude to a description of pathomechanics of the injury and a case report. The higher incidence of oral de...

  2. Approach for selecting boundary value to retrieve Mie-scattering lidar data based on segmentation and two-component fitting methods.

    Science.gov (United States)

    Mao, Feiyue; Wang, Wei; Min, Qilong; Gong, Wei

    2015-06-01

    Fernald method is regarded as the standard method for retrieving lidar data, but the retrieval can be performed only when a boundary value is given. Generally, we can select clear atmosphere above the tropopause as a reference to determine the boundary value, but we need to use the slope method to fit the boundary value when the detecting range is lower than the tropopause. The slope method involves significant uncertainty because this algorithm is based on two hypotheses: one is that aerosol vertical distribution is homogeneous, and the other is that either molecule or aerosol components exist in the atmosphere. To reduce the uncertainty, we proposed a new approach, which segments a signal into "uniform" sub-signals to avoid the first hypothesis, and then uses nonlinear two-component fitting to avoid the second one. Compared with the approach based on the slope method, the new approach obtained more accurate boundary values and retrieving results for both of the simulated and real signals. Thus the automatic segmentation algorithm and the two-component fitting method are useful for determining the reference bin and boundary values when the effective detecting range of lidar is lower than the tropopause.

  3. Can masses of non-experts train highly accurate image classifiers? A crowdsourcing approach to instrument segmentation in laparoscopic images.

    Science.gov (United States)

    Maier-Hein, Lena; Mersmann, Sven; Kondermann, Daniel; Bodenstedt, Sebastian; Sanchez, Alexandro; Stock, Christian; Kenngott, Hannes Gotz; Eisenmann, Mathias; Speidel, Stefanie

    2014-01-01

    Machine learning algorithms are gaining increasing interest in the context of computer-assisted interventions. One of the bottlenecks so far, however, has been the availability of training data, typically generated by medical experts with very limited resources. Crowdsourcing is a new trend that is based on outsourcing cognitive tasks to many anonymous untrained individuals from an online community. In this work, we investigate the potential of crowdsourcing for segmenting medical instruments in endoscopic image data. Our study suggests that (1) segmentations computed from annotations of multiple anonymous non-experts are comparable to those made by medical experts and (2) training data generated by the crowd is of the same quality as that annotated by medical experts. Given the speed of annotation, scalability and low costs, this implies that the scientific community might no longer need to rely on experts to generate reference or training data for certain applications. To trigger further research in endoscopic image processing, the data used in this study will be made publicly available.

  4. Computer aided solution for segmenting the neuron line in hippocampal microscope images

    Science.gov (United States)

    Albaidhani, Tahseen; Jassim, Sabah; Al-Assam, Hisham

    2017-05-01

    The brain Hippocampus component is known to be responsible for memory and spatial navigation. Its functionality depends on the status of different blood vessels within the Hippocampus and is severely impaired by Alzheimer's disease as a result blockage of increasing number of blood vessels by accumulation of amyloid-beta (Aβ) protein. Accurate counting of blood vessels within the Hippocampus of mice brain, from microscopic images, is an active research area for the understanding of Alzheimer's disease. Here, we report our work on automatic detection of the Region of Interest, i.e. the region in which blood vessels are located. This area typically falls between the hippocampus edge and the line of neurons within the Hippocampus. This paper proposes a new method to detect and exclude the neuron line to improve the accuracy of blood vessel counting because some neurons on it might lead to false positive cases as they look like blood vessels. Our proposed solution is based on using trainable segmentation approach with morphological operations, taking into account variation in colour, intensity values, and image texture. Experiments on a sufficient number of microscopy images of mouse brain demonstrate the effectiveness of the developed solution in preparation for blood vessels counting.

  5. [Application of the expanding forming under the plate through cervical spatium intermusculare approach in treating multi-segmental myelopathic cervical spondylosis].

    Science.gov (United States)

    Zhan, Bei-lei; Ye, Zhou

    2015-09-01

    To investigate the application of the expanding forming under the plate through cervical spatium intermusculare approach to treat multi-segmental myelopathic cervical spondylosis. From July 2005 to June 2013, 25 patients with multi-segmental myelopathic cervical spondylosis were treated by the expanding forming under the plate through cervical spatium intermusculare approach including 16 males and 9 females with an average age of 56.5 years old ranging from 35 to 78 years old. Among them, 10 cases were onset without causes slowly, 7 cases were onset without causes suddenly, 8 cases were onset after mild trauma or tired. JOA scoring, incidence of postoperative axial symptoms and imaging studies were used to evaluate the effect. Twenty-five cases were followed up for 6 months to 7 years and 6 months with an average of 2 years and 9 months. There were no infection, cerebrospinal fluid leakage after the operation, and complications such as nerve damage were occurred. The operation time was 120 to 150 min, the bleeding was 300 to 500 ml. Imaging examination showed vertebral canal sagittal diameter increased, the vertebral canal increased significantly in the cross sectional area of the spinal cord, cervical curvature was straighten in 4 cases (2 cases of them became normal sequence). There were no more cases of cervical protruding and segmental instability increased. Postoperative walking ability enhanced, the finger activity of majority of patients improved on flexibility, grip strength, and accuracy of using chopsticks improved, numbness and chest waist band feeling had different degree of reduce, preoperative urine impairment were improved to varying degrees. Preoperative JOA scores were 3 to 13 points with an average of (8.86 ± 4.25) points; Postoperative 12 months' JOA scores were 7 to 17 points with an average of (13.76 ± 3.56) points, period was 60.19% in average, JOA score had statistically difference between before and after operation (P < 0.05). The result

  6. ADA access to passenger vessels : finding safety equivalence solutions for weathertight doors with coamings : Phase 2 : a risk management approach to reconfiguration design solutions

    Science.gov (United States)

    2005-03-01

    This report examines a risk management methodology to provide for both marine safety and disability access at weathertight doors into passenger accommodation spaces on U.S. passenger vessels. The Architectural and Transportation Barriers Compliance B...

  7. 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.

  8. Image segmentation by graph partitioning

    Science.gov (United States)

    Torres, Ana Sofia; Monteiro, Fernando C.

    2012-09-01

    In this paper we propose an hybrid method for the image segmentation which combines the edge-based, region-based and the morphological techniques in conjunction through the spectral based clustering approach. An initial partitioning of the image into atomic regions is set by applying a watershed method to the image gradient magnitude. This initial partition is the input to a computationally efficient region segmentation process which produces the final segmentation. We have applied our approach on several images of the Berkeley Segmentation Dataset. The results reveal the accuracy of the propose method.

  9. BIOASSAY VESSEL FAILURE ANALYSIS

    Energy Technology Data Exchange (ETDEWEB)

    Vormelker, P

    2008-09-22

    Two high-pressure bioassay vessels failed at the Savannah River Site during a microwave heating process for biosample testing. Improper installation of the thermal shield in the first failure caused the vessel to burst during microwave heating. The second vessel failure is attributed to overpressurization during a test run. Vessel failure appeared to initiate in the mold parting line, the thinnest cross-section of the octagonal vessel. No material flaws were found in the vessel that would impair its structural performance. Content weight should be minimized to reduce operating temperature and pressure. Outer vessel life is dependent on actual temperature exposure. Since thermal aging of the vessels can be detrimental to their performance, it was recommended that the vessels be used for a limited number of cycles to be determined by additional testing.

  10. Liver segmentation: indications, techniques and future directions.

    Science.gov (United States)

    Gotra, Akshat; Sivakumaran, Lojan; Chartrand, Gabriel; Vu, Kim-Nhien; Vandenbroucke-Menu, Franck; Kauffmann, Claude; Kadoury, Samuel; Gallix, Benoît; de Guise, Jacques A; Tang, An

    2017-08-01

    Liver volumetry has emerged as an important tool in clinical practice. Liver volume is assessed primarily via organ segmentation of computed tomography (CT) and magnetic resonance imaging (MRI) images. The goal of this paper is to provide an accessible overview of liver segmentation targeted at radiologists and other healthcare professionals. Using images from CT and MRI, this paper reviews the indications for liver segmentation, technical approaches used in segmentation software and the developing roles of liver segmentation in clinical practice. Liver segmentation for volumetric assessment is indicated prior to major hepatectomy, portal vein embolisation, associating liver partition and portal vein ligation for staged hepatectomy (ALPPS) and transplant. Segmentation software can be categorised according to amount of user input involved: manual, semi-automated and fully automated. Manual segmentation is considered the "gold standard" in clinical practice and research, but is tedious and time-consuming. Increasingly automated segmentation approaches are more robust, but may suffer from certain segmentation pitfalls. Emerging applications of segmentation include surgical planning and integration with MRI-based biomarkers. Liver segmentation has multiple clinical applications and is expanding in scope. Clinicians can employ semi-automated or fully automated segmentation options to more efficiently integrate volumetry into clinical practice. • Liver volume is assessed via organ segmentation on CT and MRI examinations. • Liver segmentation is used for volume assessment prior to major hepatic procedures. • Segmentation approaches may be categorised according to the amount of user input involved. • Emerging applications include surgical planning and integration with MRI-based biomarkers.

  11. Region of interest-based versus whole-lung segmentation-based approach for MR lung perfusion quantification in 2-year-old children after congenital diaphragmatic hernia repair

    Energy Technology Data Exchange (ETDEWEB)

    Weis, M.; Sommer, V.; Hagelstein, C.; Schoenberg, S.O.; Neff, K.W. [Heidelberg University, Institute of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Mannheim (Germany); Zoellner, F.G. [Heidelberg University, Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Mannheim (Germany); Zahn, K. [University of Heidelberg, Department of Paediatric Surgery, University Medical Center Mannheim, Medical Faculty Mannheim, Mannheim (Germany); Schaible, T. [Heidelberg University, Department of Paediatrics, University Medical Center Mannheim, Medical Faculty Mannheim, Mannheim (Germany)

    2016-12-15

    With a region of interest (ROI)-based approach 2-year-old children after congenital diaphragmatic hernia (CDH) show reduced MR lung perfusion values on the ipsilateral side compared to the contralateral. This study evaluates whether results can be reproduced by segmentation of whole-lung and whether there are differences between the ROI-based and whole-lung measurements. Using dynamic contrast-enhanced (DCE) MRI, pulmonary blood flow (PBF), pulmonary blood volume (PBV) and mean transit time (MTT) were quantified in 30 children after CDH repair. Quantification results of an ROI-based (six cylindrical ROIs generated of five adjacent slices per lung-side) and a whole-lung segmentation approach were compared. In both approaches PBF and PBV were significantly reduced on the ipsilateral side (p always <0.0001). In ipsilateral lungs, PBF of the ROI-based and the whole-lung segmentation-based approach was equal (p=0.50). In contralateral lungs, the ROI-based approach significantly overestimated PBF in comparison to the whole-lung segmentation approach by approximately 9.5 % (p=0.0013). MR lung perfusion in 2-year-old children after CDH is significantly reduced ipsilaterally. In the contralateral lung, the ROI-based approach significantly overestimates perfusion, which can be explained by exclusion of the most ventral parts of the lung. Therefore whole-lung segmentation should be preferred. (orig.)

  12. 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.

  13. 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.

  14. MoMAR observatory: A Geophysical, Geological and Oceanographical Approach to the Monitoring of the Lucky Strike Segment (GRAVILUCK Cruise)

    Science.gov (United States)

    Ballu, V.; Cannat, M.; Graviluck Scientific Party, A.

    2006-12-01

    The GRAVILUCK expedition, conducted in August 2006 on the R/V ATALANTE, was mainly dedicated to the installation of a seafloor geodetic network in the framework of the MoMAR ("Monitoring the Mid-Atlantic Ridge") project, to study active mid-ocean ridge processes along a slow-spreading ridge segment. The chosen site for this integrated "observatory" effort is the Lucky Strike segment (37°N) along the Mid-Atlantic Ridge, South of the Azores Archipelago; it combines both logistic and scientific interests, and has been studied in depth by geologists, geophysicists and biologists for many years. It also presents an intense hydrothermal activity and hosts an axial magma chamber under its center discovered last year during the SISMOMAR cruise. The installation of 9 permanent geodetic benchmarks and the time-zero pressure and gravity measurements were conducting during 19 Nautile dives. Pressure changes measured at a benchmark can be due to environmental variability, to a change in the elevation of the point, or to both. To quantify environmental variations, we monitored water column with full depth CTD prior to each dive, and shallow CTD yoyos down to 500 m during the dives. These oceanographic measurements will allow us to directly model and remove part of the environmental variability and thus increase our capability to detect small vertical motions over several years. Three additional Nautile dives were dedicated to geology and gravity cartography of the central volcano. In addition to the day program, 10 nights were devoted to a geological survey using the TowCam (camera, magnetometer, wax coring, CTD) to characterize tectonic and magmatic features of the Lucky Strike volcano, their relationship to the magma chamber location, and identification of areas of most recent apparent volcanic activity; 10 other nights were dedicated to studying ocean circulation and induced mixing around the Lucky Strike site. GRAVILUCK cruise Scientific Party: CNRS/IPGP: J. Ammann, V

  15. Intracoronary Compared to Intravenous Bolus Abciximab during Primary Percutaneous Coronary Intervention in ST-segment Elevation Myocardial Infarction (STEMI) Patients Reduces 30-day Mortality and Target Vessel Revascularization: A Randomized Trial

    DEFF Research Database (Denmark)

    Iversen, Allan; Abildgaard, Ulrik; Galloe, Anders

    2011-01-01

    patients who underwent pPCI and had indication for abciximab to either IV or IC bolus followed by a 12-hour IV infusion. Primary end-points at 30 days were target vessel revascularization (TVR), recurrent myocardial infarction (MI) or death, and the composite of the three. Secondary end-points were...... bleeding complications. Results: The two groups (IV n = 170;IC n = 185) were similar with respect to baseline characteristics. Mortality at 30 days was 5.3% in the IV group compared to only 1.1% in the IC group (P = 0.02). TVR was performed in 9.4% in the IV group compared to 3.8% in the IC group (P = 0...... bleedings (IV 14.1% vs. IC 9.7%; P = 0.20). Conclusion: IC administration of bolus abciximab in STEMI patients undergoing pPCI reduces 30-day mortality and TVR and tends to reduce MI, compared to IV-bolus. (J Interven Cardiol 2011;24:105-111)....

  16. SAAS-CNV: A Joint Segmentation Approach on Aggregated and Allele Specific Signals for the Identification of Somatic Copy Number Alterations with Next-Generation Sequencing Data.

    Science.gov (United States)

    Zhang, Zhongyang; Hao, Ke

    2015-11-01

    Cancer genomes exhibit profound somatic copy number alterations (SCNAs). Studying tumor SCNAs using massively parallel sequencing provides unprecedented resolution and meanwhile gives rise to new challenges in data analysis, complicated by tumor aneuploidy and heterogeneity as well as normal cell contamination. While the majority of read depth based methods utilize total sequencing depth alone for SCNA inference, the allele specific signals are undervalued. We proposed a joint segmentation and inference approach using both signals to meet some of the challenges. Our method consists of four major steps: 1) extracting read depth supporting reference and alternative alleles at each SNP/Indel locus and comparing the total read depth and alternative allele proportion between tumor and matched normal sample; 2) performing joint segmentation on the two signal dimensions; 3) correcting the copy number baseline from which the SCNA state is determined; 4) calling SCNA state for each segment based on both signal dimensions. The method is applicable to whole exome/genome sequencing (WES/WGS) as well as SNP array data in a tumor-control study. We applied the method to a dataset containing no SCNAs to test the specificity, created by pairing sequencing replicates of a single HapMap sample as normal/tumor pairs, as well as a large-scale WGS dataset consisting of 88 liver tumors along with adjacent normal tissues. Compared with representative methods, our method demonstrated improved accuracy, scalability to large cancer studies, capability in handling both sequencing and SNP array data, and the potential to improve the estimation of tumor ploidy and purity.

  17. SAAS-CNV: A Joint Segmentation Approach on Aggregated and Allele Specific Signals for the Identification of Somatic Copy Number Alterations with Next-Generation Sequencing Data.

    Directory of Open Access Journals (Sweden)

    Zhongyang Zhang

    2015-11-01

    Full Text Available Cancer genomes exhibit profound somatic copy number alterations (SCNAs. Studying tumor SCNAs using massively parallel sequencing provides unprecedented resolution and meanwhile gives rise to new challenges in data analysis, complicated by tumor aneuploidy and heterogeneity as well as normal cell contamination. While the majority of read depth based methods utilize total sequencing depth alone for SCNA inference, the allele specific signals are undervalued. We proposed a joint segmentation and inference approach using both signals to meet some of the challenges. Our method consists of four major steps: 1 extracting read depth supporting reference and alternative alleles at each SNP/Indel locus and comparing the total read depth and alternative allele proportion between tumor and matched normal sample; 2 performing joint segmentation on the two signal dimensions; 3 correcting the copy number baseline from which the SCNA state is determined; 4 calling SCNA state for each segment based on both signal dimensions. The method is applicable to whole exome/genome sequencing (WES/WGS as well as SNP array data in a tumor-control study. We applied the method to a dataset containing no SCNAs to test the specificity, created by pairing sequencing replicates of a single HapMap sample as normal/tumor pairs, as well as a large-scale WGS dataset consisting of 88 liver tumors along with adjacent normal tissues. Compared with representative methods, our method demonstrated improved accuracy, scalability to large cancer studies, capability in handling both sequencing and SNP array data, and the potential to improve the estimation of tumor ploidy and purity.

  18. 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.

  19. Guam Abandoned Vessel Inventory

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA Abandoned Vessel Project Data for Guam. Abandoned vessels pose a significant threat to the NOAA Trust resources through physical destruction of coral habitats...

  20. Florida Abandoned Vessel Inventory

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA Abandoned Vessel Project Data for Florida. Abandoned vessels pose a significant threat to the NOAA Trust resources through physical destruction of coral...

  1. Vessel Arrival Info - Legacy

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Vessel Arrival Info is a spreadsheet that gets filled out during the initial stage of the debriefing process by the debriefer. It contains vessel name, trip...

  2. 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...... 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....... The traditionalists are characterised by favouring pork, poultry and beef. Since it is difficult to change consumers' tastes, the short-term consequence may be to focus on the "fish lovers" and target the communication towards these consumers. In the long run, "traditionalists" may be persuaded to revise...

  3. ALICE HMPID Radiator Vessel

    CERN Multimedia

    2003-01-01

    View of the radiator vessels of the ALICE/HMPID mounted on the support frame. Each HMPID module is equipped with 3 indipendent radiator vessels made out of neoceram and fused silica (quartz) windows glued together. The spacers inside the vessel are needed to stand the hydrostatic pressure. http://alice-hmpid.web.cern.ch/alice-hmpid

  4. Curvature affects Doppler investigation of vessels: implications for clinical practice.

    Science.gov (United States)

    Balbis, S; Roatta, S; Guiot, C

    2005-01-01

    In clinical practice, blood velocity estimations from Doppler examination of curved vascular segments are normally different from those of nearby straight segments. The observed "accelerations," sometimes considered as a sort of stochastic disturbances, can actually be related to very specific physical effects due to vessel curvature (i.e., the development of nonaxial velocity [NAV] components) and the spreading of the axial velocity direction in the Doppler sample volume with respect to the insonation axis. The relevant phenomena and their dependence on the radius of curvature of the vessels and on the insonation angle are investigated with a beam-vessel geometry as close as possible to clinical setting, with the simplifying assumptions of steady flow, mild vessel curvature, uniform ultrasonic beam and complete vessel insonation. The insonation angles that minimize the errors are provided on the basis of the study results.

  5. Adaptive segmentation for scientific databases

    NARCIS (Netherlands)

    Ivanova, M.; Kersten, M.L.; Nes, N.

    2008-01-01

    In this paper we explore database segmentation in the context of a column-store DBMS targeted at a scientific database. We present a novel hardware- and scheme-oblivious segmentation algorithm, which learns and adapts to the workload immediately. The approach taken is to capitalize on (intermediate)

  6. 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.

  7. Single vessel air injection estimates of xylem resistance to cavitation are affected by vessel network characteristics and sample length.

    Science.gov (United States)

    Venturas, Martin D; Rodriguez-Zaccaro, F Daniela; Percolla, Marta I; Crous, Casparus J; Jacobsen, Anna L; Pratt, R Brandon

    2016-10-01

    Xylem resistance to cavitation is an important trait that is related to the ecology and survival of plant species. Vessel network characteristics, such as vessel length and connectivity, could affect the spread of emboli from gas-filled vessels to functional ones, triggering their cavitation. We hypothesized that the cavitation resistance of xylem vessels is randomly distributed throughout the vessel network. We predicted that single vessel air injection (SVAI) vulnerability curves (VCs) would thus be affected by sample length. Longer stem samples were predicted to appear more resistant than shorter samples due to the sampled path including greater numbers of vessels. We evaluated the vessel network characteristics of grapevine (Vitis vinifera L.), English oak (Quercus robur L.) and black cottonwood (Populus trichocarpa Torr. & A. Gray), and constructed SVAI VCs for 5- and 20-cm-long segments. We also constructed VCs with a standard centrifuge method and used computer modelling to estimate the curve shift expected for pathways composed of different numbers of vessels. For all three species, the SVAI VCs for 5 cm segments rose exponentially and were more vulnerable than the 20 cm segments. The 5 cm curve shapes were exponential and were consistent with centrifuge VCs. Modelling data supported the observed SVAI VC shifts, which were related to path length and vessel network characteristics. These results suggest that exponential VCs represent the most realistic curve shape for individual vessel resistance distributions for these species. At the network level, the presence of some vessels with a higher resistance to cavitation may help avoid emboli spread during tissue dehydration. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  8. Surgical Approaches to Supradiaphragmatic Segment of IVC and Right Atrium through Abdominal Cavity during Intravenous Tumor Thrombus Removal

    Directory of Open Access Journals (Sweden)

    Dmytro Shchukin

    2014-01-01

    Full Text Available Objective. The purpose of this study was to investigate safety and feasibility of some surgical approaches to the supradiaphragmatic inferior vena cava (IVC and the right atrium through the diaphragm from the abdominal cavity. Materials and Methods. The material of the anatomical study included 35 fresh cadavers. Several options of surgical access to the supradiaphragmatic IVC were successively performed. Feasibility and risk level of each of the approaches were evaluated with the use of a special scale. Results. The isolation of the supradiaphragmatic IVC and cavoatrial junction was most easily performed via T-shaped or circular diaphragmotomy (grade “easy” was registered in 74.3% and 80% of patients, resp., compared to 31.4% for transverse diaphragmotomy and 40% for isolation of the IVC in the pericardial cavity. The risk analysis has demonstrated the highest safety level for T-shaped diaphragmotomy (grade “safe” was registered in 60% of cases. The intervention via transverse diaphragmotomy, circular diaphragmotomy, and IVC isolation in the pericardial cavity was graded as “risky” in 80%, 62.9%, and 82.9% of cases, respectively. Conclusions. In our opinion, T-shaped diaphragmotomy is the most safe and easy-to-perform access for mobilization of the supradiaphragmatic IVC through the abdominal cavity.

  9. Coronary magnetic resonance angiography and vessel wall imaging in children with Kawasaki disease

    Energy Technology Data Exchange (ETDEWEB)

    Greil, Gerald F.; Hofbeck, Michael; Sieverding, Ludger [University of Tuebingen, Department of Pediatric Cardiology, Children' s Hospital, Tuebingen (Germany); Seeger, Achim; Miller, Stephan; Claussen, Claus D. [University of Tuebingen, Department of Diagnostic Radiology, Tuebingen (Germany); Botnar, Rene M. [Technical University Munich, Department of Nuclear Medicine, Cardiovascular Division, Munich (Germany)

    2007-07-15

    In patients with Kawasaki disease (KD) serial evaluation of the distribution and size of coronary artery aneurysms (CAA) is necessary for risk stratification and therapeutic management. To apply whole-heart coronary MR angiography (CMRA) and black-blood coronary vessel wall imaging in children with KD. Six children (mean age 4.6 years, range 2.5-7.8 years) with KD underwent CMRA using a free-breathing, T2-prepared, three-dimensional steady-state free-precession (3D-SSFP), whole-heart approach with navigator gating and tracking. Vessel walls were imaged with an ECG-triggered and navigator-gated double inversion recovery (DIR) black-blood segmented turbo spin-echo sequence. There was complete agreement between CMRA and conventional angiography (n=6) in the detection of CAA (n=15). Excellent agreement was found between the two techniques in determining the maximal diameter (mean difference 0.2{+-}0.7 mm), length (mean difference 0.1{+-}0.8 mm) and distance from the ostium (mean difference -0.8{+-}2.1 mm) of the CAAs. In all subjects with a CAA, abnormally thickened vessel walls were found (2.5{+-}0.5 mm). CMRA accurately defines CAA in free-breathing sedated children with KD using the whole-heart approach and detects abnormally thickened vessel walls. This technique may reduce the need for serial X-ray coronary angiography, and improve risk stratification and monitoring of therapy. (orig.)

  10. Mixed segmentation

    DEFF Research Database (Denmark)

    Bonde, Anders; Aagaard, Morten; Hansen, Allan Grutt

    content analysis and audience segmentation in a single-source perspective. The aim is to explain and understand target groups in relation to, on the one hand, emotional response to commercials or other forms of audio-visual communication and, on the other hand, living preferences and personality traits....... Innovatively, the research process is documented via an interactive data-visualization tool by which readers and fellow peers can access and, by using various filtering options, further analyze the results and, ultimately, reformulate the problem field....

  11. [Segmental neurofibromatosis].

    Science.gov (United States)

    Wagner, G; Meyer, V; Sachse, M M

    2017-11-08

    Thirteen years ago, a 48-year-old man developed numerous neurofibromas in a circumscribed area on the right chest. At the same time, a bilateral seminoma was diagnosed and treated curatively. There was no evidence for other complications of neurofibromatosis. The family history was inconspicuous. The segmental neurofibromatosis (SN) presented in this patient is the result of a mosaic formation resulting from a mutation of the NF1 gene, a tumor suppressor gene. Concomitant, typical diseases of neurofibromatosis generalisata (NFG), including malignant neoplasms, are the exception to SN.

  12. Segmental neurofibromatosis.

    Science.gov (United States)

    Sobjanek, Michał; Dobosz-Kawałko, Magdalena; Michajłowski, Igor; Pęksa, Rafał; Nowicki, Roman

    2014-12-01

    Segmental neurofibromatosis or type V neurofibromatosis is a rare genodermatosis characterized by neurofibromas, café-au-lait spots and neurofibromas limited to a circumscribed body region. The disease may be associated with systemic involvement and malignancies. The disorder has not been reported yet in the Polish medical literature. A 63-year-old Caucasian woman presented with a 20-year history of multiple, flesh colored, dome-shaped, soft to firm nodules situated in the right lumbar region. A histopathologic evaluation of three excised tumors revealed neurofibromas. No neurological and ophthalmologic symptoms of neurofibromatosis were diagnosed.

  13. SEGMENTATION OF SERIAL MRI OF TBI PATIENTS USING PERSONALIZED ATLAS CONSTRUCTION AND TOPOLOGICAL CHANGE ESTIMATION.

    Science.gov (United States)

    Wang, Bo; Prastawa, Marcel; Awate, Suyash P; Irimia, Andrei; Chambers, Micah C; Vespa, Paul M; van Horn, John D; Gerig, Guido

    2012-01-01

    Traumatic brain injury (TBI) due to falls, car accidents, and warfare affects millions of people annually. Determining personalized therapy and assessment of treatment efficacy can substantially benefit from longitudinal (4D) magnetic resonance imaging (MRI). In this paper, we propose a method for segmenting longitudinal brain MR images with TBI using personalized atlas construction. Longitudinal images with TBI typically present topological changes over time due to the effect of the impact force on tissue, skull, and blood vessels and the recovery process. We address this issue by defining a novel atlas construction scheme that explicitly models the effect of topological changes. Our method automatically estimates the probability of topological changes jointly with the personalized atlas. We demonstrate the effectiveness of this approach on MR images with TBI that also have been segmented by human raters, where our method that integrates 4D information yields improved validation measures compared to temporally independent segmentations.

  14. Metabolic network segmentation: A probabilistic graphical modeling approach to identify the sites and sequential order of metabolic regulation from non-targeted metabolomics data.

    Directory of Open Access Journals (Sweden)

    Andreas Kuehne

    2017-06-01

    Full Text Available In recent years, the number of large-scale metabolomics studies on various cellular processes in different organisms has increased drastically. However, it remains a major challenge to perform a systematic identification of mechanistic regulatory events that mediate the observed changes in metabolite levels, due to complex interdependencies within metabolic networks. We present the metabolic network segmentation (MNS algorithm, a probabilistic graphical modeling approach that enables genome-scale, automated prediction of regulated metabolic reactions from differential or serial metabolomics data. The algorithm sections the metabolic network into modules of metabolites with consistent changes. Metabolic reactions that connect different modules are the most likely sites of metabolic regulation. In contrast to most state-of-the-art methods, the MNS algorithm is independent of arbitrary pathway definitions, and its probabilistic nature facilitates assessments of noisy and incomplete measurements. With serial (i.e., time-resolved data, the MNS algorithm also indicates the sequential order of metabolic regulation. We demonstrated the power and flexibility of the MNS algorithm with three, realistic case studies with bacterial and human cells. Thus, this approach enables the identification of mechanistic regulatory events from large-scale metabolomics data, and contributes to the understanding of metabolic processes and their interplay with cellular signaling and regulation processes.

  15. Metabolic network segmentation: A probabilistic graphical modeling approach to identify the sites and sequential order of metabolic regulation from non-targeted metabolomics data.

    Science.gov (United States)

    Kuehne, Andreas; Mayr, Urs; Sévin, Daniel C; Claassen, Manfred; Zamboni, Nicola

    2017-06-01

    In recent years, the number of large-scale metabolomics studies on various cellular processes in different organisms has increased drastically. However, it remains a major challenge to perform a systematic identification of mechanistic regulatory events that mediate the observed changes in metabolite levels, due to complex interdependencies within metabolic networks. We present the metabolic network segmentation (MNS) algorithm, a probabilistic graphical modeling approach that enables genome-scale, automated prediction of regulated metabolic reactions from differential or serial metabolomics data. The algorithm sections the metabolic network into modules of metabolites with consistent changes. Metabolic reactions that connect different modules are the most likely sites of metabolic regulation. In contrast to most state-of-the-art methods, the MNS algorithm is independent of arbitrary pathway definitions, and its probabilistic nature facilitates assessments of noisy and incomplete measurements. With serial (i.e., time-resolved) data, the MNS algorithm also indicates the sequential order of metabolic regulation. We demonstrated the power and flexibility of the MNS algorithm with three, realistic case studies with bacterial and human cells. Thus, this approach enables the identification of mechanistic regulatory events from large-scale metabolomics data, and contributes to the understanding of metabolic processes and their interplay with cellular signaling and regulation processes.

  16. Pressure vessel design manual

    CERN Document Server

    Moss, Dennis R

    2013-01-01

    Pressure vessels are closed containers designed to hold gases or liquids at a pressure substantially different from the ambient pressure. They have a variety of applications in industry, including in oil refineries, nuclear reactors, vehicle airbrake reservoirs, and more. The pressure differential with such vessels is dangerous, and due to the risk of accident and fatality around their use, the design, manufacture, operation and inspection of pressure vessels is regulated by engineering authorities and guided by legal codes and standards. Pressure Vessel Design Manual is a solutions-focused guide to the many problems and technical challenges involved in the design of pressure vessels to match stringent standards and codes. It brings together otherwise scattered information and explanations into one easy-to-use resource to minimize research and take readers from problem to solution in the most direct manner possible. * Covers almost all problems that a working pressure vessel designer can expect to face, with ...

  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. A geometric flow for segmenting vasculature in proton-density weighted MRI.

    Science.gov (United States)

    Descoteaux, Maxime; Collins, D Louis; Siddiqi, Kaleem

    2008-08-01

    Modern neurosurgery takes advantage of magnetic resonance images (MRI) of a patient's cerebral anatomy and vasculature for planning before surgery and guidance during the procedure. Dual echo acquisitions are often performed that yield proton-density (PD) and T2-weighted images to evaluate edema near a tumor or lesion. In this paper we develop a novel geometric flow for segmenting vasculature in PD images, which can also be applied to the easier cases of MR angiography data or Gadolinium enhanced MRI. Obtaining vasculature from PD data is of clinical interest since the acquisition of such images is widespread, the scanning process is non-invasive, and the availability of vessel segmentation methods could obviate the need for an additional angiographic or contrast-based sequence during preoperative imaging. The key idea is to first apply Frangi's vesselness measure [Frangi, A., Niessen, W., Vincken, K.L., Viergever, M.A., 1998. Multiscale vessel enhancement filtering. In: International Conference on Medical Image Computing and Computer Assisted Intervention, vol. 1496 of Lecture Notes in Computer Science, pp. 130-137] to find putative centerlines of tubular structures along with their estimated radii. This measure is then distributed to create a vector field which allows the flux maximizing flow algorithm of Vasilevskiy and Siddiqi [Vasilevskiy, A., Siddiqi, K., 2002. Flux maximizing geometric flows. IEEE Transactions on Pattern Analysis and Machine Intelligence 24 (12), 1565-1578] to be applied to recover vessel boundaries. We carry out a qualitative validation of the approach on PD, MR angiography and Gadolinium enhanced MRI volumes and suggest a new way to visualize the segmentations in 2D with masked projections. We validate the approach quantitatively on a single-subject data set consisting of PD, phase contrast (PC) angiography and time of flight (TOF) angiography volumes, with an expert segmented version of the TOF volume viewed as the ground truth. We then

  19. ST-segment elevation myocardial infarction treated by radial or femoral approach in a multicenter randomized clinical trial: the STEMI-RADIAL trial.

    Science.gov (United States)

    Bernat, Ivo; Horak, David; Stasek, Josef; Mates, Martin; Pesek, Jan; Ostadal, Petr; Hrabos, Vlado; Dusek, Jaroslav; Koza, Jiri; Sembera, Zdenek; Brtko, Miroslav; Aschermann, Ondrej; Smid, Michal; Polansky, Pavel; Al Mawiri, Abdul; Vojacek, Jan; Bis, Josef; Costerousse, Olivier; Bertrand, Olivier F; Rokyta, Richard

    2014-03-18

    This study sought to compare radial and femoral approaches in patients presenting with ST-segment elevation myocardial infarction (STEMI) and undergoing primary percutaneous coronary intervention (PCI) by high-volume operators experienced in both access sites. The exact clinical benefit of the radial compared to the femoral approach remains controversial. STEMI-RADIAL (ST Elevation Myocardial Infarction treated by RADIAL or femoral approach) was a randomized, multicenter trial. A total of 707 patients referred for STEMI clinical events (NACE) was defined as a composite of death, myocardial infarction, stroke, and major bleeding/vascular complications. Access site crossover, contrast volume, duration of intensive care stay, and death at 6 months were secondary endpoints. The primary endpoint occurred in 1.4% of the radial group (n = 348) and 7.2% of the femoral group (n = 359; p = 0.0001). The NACE rate was 4.6% versus 11.0% (p = 0.0028), respectively. Crossover from radial to femoral approach was 3.7%. Intensive care stay (2.5 ± 1.7 days vs. 3.0 ± 2.9 days, p = 0.0038) as well as contrast utilization (170 ± 71 ml vs. 182 ± 60 ml, p = 0.01) were significantly reduced in the radial group. Mortality in the radial and femoral groups was 2.3% versus 3.1% (p = 0.64) at 30 days and 2.3% versus 3.6% (p = 0.31) at 6 months, respectively. In patients with STEMI undergoing primary PCI by operators experienced in both access sites, the radial approach was associated with significantly lower incidence of major bleeding and access site complications and superior net clinical benefit. These findings support the use of the radial approach in primary PCI as first choice after proper training. (Trial Comparing Radial and Femoral Approach in Primary Percutaneous Coronary Intervention [PCI] [STEMI-RADIAL]; NCT01136187). Copyright © 2014 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

  20. Maury Journals - German Vessels

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — German vessels observations, after the 1853 Brussels Conference that set International Maritime Standards, modeled after Maury Marine Standard Observations.

  1. Blood Vessel Extraction in Color Retinal Fundus Images with Enhancement Filtering and Unsupervised Classification

    Directory of Open Access Journals (Sweden)

    Zafer Yavuz

    2017-01-01

    Full Text Available Retinal blood vessels have a significant role in the diagnosis and treatment of various retinal diseases such as diabetic retinopathy, glaucoma, arteriosclerosis, and hypertension. For this reason, retinal vasculature extraction is important in order to help specialists for the diagnosis and treatment of systematic diseases. In this paper, a novel approach is developed to extract retinal blood vessel network. Our method comprises four stages: (1 preprocessing stage in order to prepare dataset for segmentation; (2 an enhancement procedure including Gabor, Frangi, and Gauss filters obtained separately before a top-hat transform; (3 a hard and soft clustering stage which includes K-means and Fuzzy C-means (FCM in order to get binary vessel map; and (4 a postprocessing step which removes falsely segmented isolated regions. The method is tested on color retinal images obtained from STARE and DRIVE databases which are available online. As a result, Gabor filter followed by K-means clustering method achieves 95.94% and 95.71% of accuracy for STARE and DRIVE databases, respectively, which are acceptable for diagnosis systems.

  2. 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…

  3. Labor market segmentation

    OpenAIRE

    Berndt, Christian

    2017-01-01

    Labor market segmentation theories arose as an alternative to neoclassical notions of labor and labor markets in the 1970s. After briefly revisiting the strengths and the weaknesses of this approach, the article discusses more recent developments around the question of difference and diversity in labor markets, directing attention to three key developments associated with the rise of neoliberal capitalism: (i) the formation of entrepreneurial subjectivities and the treatment of labor as a div...

  4. Pattern Recognition Of Blood Vessel Networks In Ocular Fundus Images

    Science.gov (United States)

    Akita, K.; Kuga, H.

    1982-11-01

    We propose a computer method of recognizing blood vessel networks in color ocular fundus images which are used in the mass diagnosis of adult diseases such as hypertension and diabetes. A line detection algorithm is applied to extract the blood vessels, and the skeleton patterns of them are made to analyze and describe their structures. The recognition of line segments of arteries and/or veins in the vessel networks consists of three stages. First, a few segments which satisfy a certain constraint are picked up and discriminated as arteries or veins. This is the initial labeling. Then the remaining unknown ones are labeled by utilizing the physical level knowledge. We propose two schemes for this stage : a deterministic labeling and a probabilistic relaxation labeling. Finally the label of each line segment is checked so as to minimize the total number of labeling contradictions. Some experimental results are also presented.

  5. PRESSURE-RESISTANT VESSEL

    NARCIS (Netherlands)

    Beukers, A.; De Jong, T.

    1997-01-01

    Abstract of WO 9717570 (A1) The invention is directed to a wheel-shaped pressure-resistant vessel for gaseous, liquid or liquefied material having a substantially rigid shape, said vessel comprising a substantially continuous shell of a fiber-reinforced resin having a central opening, an inner

  6. Containment vessel drain system

    Energy Technology Data Exchange (ETDEWEB)

    Harris, Scott G.

    2018-01-30

    A system for draining a containment vessel may include a drain inlet located in a lower portion of the containment vessel. The containment vessel may be at least partially filled with a liquid, and the drain inlet may be located below a surface of the liquid. The system may further comprise an inlet located in an upper portion of the containment vessel. The inlet may be configured to insert pressurized gas into the containment vessel to form a pressurized region above the surface of the liquid, and the pressurized region may operate to apply a surface pressure that forces the liquid into the drain inlet. Additionally, a fluid separation device may be operatively connected to the drain inlet. The fluid separation device may be configured to separate the liquid from the pressurized gas that enters the drain inlet after the surface of the liquid falls below the drain inlet.

  7. Satellite Image Classification and Segmentation by Using JSEG Segmentation Algorithm

    OpenAIRE

    Khamael Abbas; Mustafa Rydh

    2012-01-01

    In this paper, a adopted approach to fully automatic satellite image segmentation, called JSEG, "JPEG image segmentation" is presented. First colors in the image are quantized to represent differentiate regions in the image. Then image pixel colors are replaced by their corresponding color class labels, thus forming a class-map of the image. A criterion for “good” segmentation using this class-map is proposed. Applying the criterion to local windows in the class-map results in the “J-image”...

  8. Simultaneous tomographic reconstruction and segmentation with class priors

    DEFF Research Database (Denmark)

    Romanov, Mikhail; Dahl, Anders Bjorholm; Dong, Yiqiu

    2015-01-01

    We consider tomographic imaging problems where the goal is to obtain both a reconstructed image and a corresponding segmentation. A classical approach is to first reconstruct and then segment the image; more recent approaches use a discrete tomography approach where reconstruction and segmentatio...... approach can produce better results than the classical two-step approach.......We consider tomographic imaging problems where the goal is to obtain both a reconstructed image and a corresponding segmentation. A classical approach is to first reconstruct and then segment the image; more recent approaches use a discrete tomography approach where reconstruction and segmentation...... are combined to produce a reconstruction that is identical to the segmentation. We consider instead a hybrid approach that simultaneously produces both a reconstructed image and segmentation. We incorporate priors about the desired classes of the segmentation through a Hidden Markov Measure Field Model, and we...

  9. Image Segmentation Algorithms Overview

    OpenAIRE

    Yuheng, Song; Hao, Yan

    2017-01-01

    The technology of image segmentation is widely used in medical image processing, face recognition pedestrian detection, etc. The current image segmentation techniques include region-based segmentation, edge detection segmentation, segmentation based on clustering, segmentation based on weakly-supervised learning in CNN, etc. This paper analyzes and summarizes these algorithms of image segmentation, and compares the advantages and disadvantages of different algorithms. Finally, we make a predi...

  10. Automatic segmentation of blood vessels from retinal fundus images ...

    Indian Academy of Sciences (India)

    The proposed methodology was evaluated on a publicly available database, STARE. The results reported ... This methodology can help ophthalmologists in better and faster analysis and hence early treatment to the patients. ... Department of Information Science and Technology, Anna University, Chennai 600025, India ...

  11. HyMaP: A hybrid magnitude-phase approach to unsupervised segmentation of tumor areas in breast cancer histology images.

    Science.gov (United States)

    Khan, Adnan M; El-Daly, Hesham; Simmons, Emma; Rajpoot, Nasir M

    2013-01-01

    Segmentation of areas containing tumor cells in standard H&E histopathology images of breast (and several other tissues) is a key task for computer-assisted assessment and grading of histopathology slides. Good segmentation of tumor regions is also vital for automated scoring of immunohistochemical stained slides to restrict the scoring or analysis to areas containing tumor cells only and avoid potentially misleading results from analysis of stromal regions. Furthermore, detection of mitotic cells is critical for calculating key measures such as mitotic index; a key criteria for grading several types of cancers including breast cancer. We show that tumor segmentation can allow detection and quantification of mitotic cells from the standard H&E slides with a high degree of accuracy without need for special stains, in turn making the whole process more cost-effective. BASED ON THE TISSUE MORPHOLOGY, BREAST HISTOLOGY IMAGE CONTENTS CAN BE DIVIDED INTO FOUR REGIONS: Tumor, Hypocellular Stroma (HypoCS), Hypercellular Stroma (HyperCS), and tissue fat (Background). Background is removed during the preprocessing stage on the basis of color thresholding, while HypoCS and HyperCS regions are segmented by calculating features using magnitude and phase spectra in the frequency domain, respectively, and performing unsupervised segmentation on these features. All images in the database were hand segmented by two expert pathologists. The algorithms considered here are evaluated on three pixel-wise accuracy measures: precision, recall, and F1-Score. The segmentation results obtained by combining HypoCS and HyperCS yield high F1-Score of 0.86 and 0.89 with re-spect to the ground truth. In this paper, we show that segmentation of breast histopathology image into hypocellular stroma and hypercellular stroma can be achieved using magnitude and phase spectra in the frequency domain. The segmentation leads to demarcation of tumor margins leading to improved accuracy of mitotic cell

  12. HyMaP: A hybrid magnitude-phase approach to unsupervised segmentation of tumor areas in breast cancer histology images

    Directory of Open Access Journals (Sweden)

    Adnan M Khan

    2013-01-01

    Full Text Available Background: Segmentation of areas containing tumor cells in standard H&E histopathology images of breast (and several other tissues is a key task for computer-assisted assessment and grading of histopathology slides. Good segmentation of tumor regions is also vital for automated scoring of immunohistochemical stained slides to restrict the scoring or analysis to areas containing tumor cells only and avoid potentially misleading results from analysis of stromal regions. Furthermore, detection of mitotic cells is critical for calculating key measures such as mitotic index; a key criteria for grading several types of cancers including breast cancer. We show that tumor segmentation can allow detection and quantification of mitotic cells from the standard H&E slides with a high degree of accuracy without need for special stains, in turn making the whole process more cost-effective. Method: Based on the tissue morphology, breast histology image contents can be divided into four regions: Tumor, Hypocellular Stroma (HypoCS, Hypercellular Stroma (HyperCS, and tissue fat (Background. Background is removed during the preprocessing stage on the basis of color thresholding, while HypoCS and HyperCS regions are segmented by calculating features using magnitude and phase spectra in the frequency domain, respectively, and performing unsupervised segmentation on these features. Results: All images in the database were hand segmented by two expert pathologists. The algorithms considered here are evaluated on three pixel-wise accuracy measures: precision, recall, and F1-Score. The segmentation results obtained by combining HypoCS and HyperCS yield high F1-Score of 0.86 and 0.89 with re-spect to the ground truth. Conclusions: In this paper, we show that segmentation of breast histopathology image into hypocellular stroma and hypercellular stroma can be achieved using magnitude and phase spectra in the frequency domain. The segmentation leads to demarcation of tumor

  13. A Multiatlas Segmentation Using Graph Cuts with Applications to Liver Segmentation in CT Scans

    Science.gov (United States)

    2014-01-01

    An atlas-based segmentation approach is presented that combines low-level operations, an affine probabilistic atlas, and a multiatlas-based segmentation. The proposed combination provides highly accurate segmentation due to registrations and atlas selections based on the regions of interest (ROIs) and coarse segmentations. Our approach shares the following common elements between the probabilistic atlas and multiatlas segmentation: (a) the spatial normalisation and (b) the segmentation method, which is based on minimising a discrete energy function using graph cuts. The method is evaluated for the segmentation of the liver in computed tomography (CT) images. Low-level operations define a ROI around the liver from an abdominal CT. We generate a probabilistic atlas using an affine registration based on geometry moments from manually labelled data. Next, a coarse segmentation of the liver is obtained from the probabilistic atlas with low computational effort. Then, a multiatlas segmentation approach improves the accuracy of the segmentation. Both the atlas selections and the nonrigid registrations of the multiatlas approach use a binary mask defined by coarse segmentation. We experimentally demonstrate that this approach performs better than atlas selections and nonrigid registrations in the entire ROI. The segmentation results are comparable to those obtained by human experts and to other recently published results. PMID:25276219

  14. Atlas-based method for segmentation of cerebral vascular trees from phase-contrast magnetic resonance angiography

    Science.gov (United States)

    Passat, Nicolas; Ronse, Christian; Baruthio, Joseph; Armspach, Jean-Paul; Maillot, Claude; Jahn, Christine

    2004-05-01

    Phase-contrast magnetic resonance angiography (PC-MRA) can produce phase images which are 3-dimensional pictures of vascular structures. However, it also provides magnitude images, containing anatomical - but no vascular - data. Classically, algorithms dedicated to PC-MRA segmentation detect the cerebral vascular tree by only working on phase images. We propose here a new approach for segmentation of cerebral blood vessels in PC-MRA using both types of images. This approach is based on the hypothesis that a magnitude image contains anatomical information useful for vascular structures detection. That information can then be transposed from a normal case to any patient image by image registration. An atlas of the whole head has been developed in order to store such anatomical knowledge. It divides a magnitude image into several "vascular areas", each one having specific vessel properties. The atlas can be applied on any magnitude image of an entire or nearly entire head by deformable matching, thus helping to segment blood vessels from the associated phase image. The segmentation method used afterwards is composed of a topology-conserving region growing algorithm using adaptative threshold values depending on the current region of the atlas. This algorithm builds the arterial and venous trees by iteratively adding voxels which are selected according to their greyscale value and the variation of values in their neighborhood. The topology conservation is guaranteed by only selecting simple points during the growing process. The method has been performed on 15 PC-MRA's of the brain. The results have been validated using MIP and 3D surface rendering visualization; a comparison to other results obtained without an atlas proves that atlas-based methods are an effective way to optimize vascular segmentation strategies.

  15. 2013 Vessel Density

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Automatic Identification Systems (AIS) are a navigation safety device that transmits and monitors the location and characteristics of many vessels in U.S. and...

  16. 2011 Passenger Vessel Density

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Automatic Identification Systems (AIS) are a navigation safety device that transmits and monitors the location and characteristics of many vessels in U.S. and...

  17. 2011 Vessel Density

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Automatic Identification Systems (AIS) are a navigation safety device that transmits and monitors the location and characteristics of many vessels in U.S. and...

  18. 2013 Passenger Vessel Density

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Automatic Identification Systems (AIS) are a navigation safety device that transmits and monitors the location and characteristics of many vessels in U.S. and...

  19. 2013 Tanker Vessel Density

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Automatic Identification Systems (AIS) are a navigation safety device that transmits and monitors the location and characteristics of many vessels in U.S. and...

  20. 2013 Cargo Vessel Density

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Automatic Identification Systems (AIS) are a navigation safety device that transmits and monitors the location and characteristics of many vessels in U.S. and...

  1. High Performance Marine Vessels

    CERN Document Server

    Yun, Liang

    2012-01-01

    High Performance Marine Vessels (HPMVs) range from the Fast Ferries to the latest high speed Navy Craft, including competition power boats and hydroplanes, hydrofoils, hovercraft, catamarans and other multi-hull craft. High Performance Marine Vessels covers the main concepts of HPMVs and discusses historical background, design features, services that have been successful and not so successful, and some sample data of the range of HPMVs to date. Included is a comparison of all HPMVs craft and the differences between them and descriptions of performance (hydrodynamics and aerodynamics). Readers will find a comprehensive overview of the design, development and building of HPMVs. In summary, this book: Focuses on technology at the aero-marine interface Covers the full range of high performance marine vessel concepts Explains the historical development of various HPMVs Discusses ferries, racing and pleasure craft, as well as utility and military missions High Performance Marine Vessels is an ideal book for student...

  2. Cheboygan Vessel Base

    Data.gov (United States)

    Federal Laboratory Consortium — Cheboygan Vessel Base (CVB), located in Cheboygan, Michigan, is a field station of the USGS Great Lakes Science Center (GLSC). CVB was established by congressional...

  3. Maury Journals - US Vessels

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — U.S. vessels observations, after the 1853 Brussels Conference that set International Maritime Standards, modeled after Maury Marine Standard Observations.

  4. 2011 Cargo Vessel Density

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Automatic Identification Systems (AIS) are a navigation safety device that transmits and monitors the location and characteristics of many vessels in U.S. and...

  5. 2011 Tanker Vessel Density

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Automatic Identification Systems (AIS) are a navigation safety device that transmits and monitors the location and characteristics of many vessels in U.S. and...

  6. 2013 Fishing Vessel Density

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Automatic Identification Systems (AIS) are a navigation safety device that transmits and monitors the location and characteristics of many vessels in U.S. and...

  7. Coastal Logbook Survey (Vessels)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains catch (landed catch) and effort for fishing trips made by vessels that have been issued a Federal permit for the Gulf of Mexico reef fish,...

  8. MORPHOMETRIC STUDY OF THE AREOLAR SPACE BETWEEN THE GREAT VESSELS AND THE LUMBAR SPINE

    Directory of Open Access Journals (Sweden)

    Luis Marchi

    2015-12-01

    Full Text Available Objective : This work aims to study the areolar space anterior to the lumbar spine, and also the positioning of the large vessels focusing a lateral approach. Methods :This is a morphometric study of 108 cases based on T2 weighted-MRI images in the supine position. The following measurements were performed: lumbar and segmental lordosis; anteroposterior disc diameter; space between the disc/vertebral body and the vessels; bifurcation between the abdominal aorta and the common iliac veins confluence in relation to the lumbar level. Results :The areolar space with respect to the iliac veins, and with the vena cava increased cranially (p<0.001, starting from average 0.6mm at L4-L5 and reaching 8.4mm at L2, while the abdominal aorta showed no increase or decrease pattern across the different levels (p=0.135 ranging from 1.8 to 4.6mm. The diameter of the discs increased distally (p<0.01 as well as the lordosis (p<0.001. The disc diameter was 11% larger when compared to the adjacent vertebral bodies (p<0.001 and that resulted in a smaller distance of the vessels in the disc level than in the level of the adjacent vertebral bodies (p<0.001. The aortic bifurcation was generally ahead of L4 (52% and less frequently at L3-L4 (28% and L4-L5 (18%. The confluence of the veins was usually at the L4-L5 level (38% and at L5 (37%, and less frequently at L4 (26%. Conclusions : There is an identifiable plane between the great vessels and the lumbar spine which is particularly narrow in its distal portion. It is theoretically feasible to reach this plan, handle the anterior complex disc/ALL and protect the great vessels by lateral approach, however, it is challenging.

  9. Mixed segmentation

    DEFF Research Database (Denmark)

    Hansen, Allan Grutt; Bonde, Anders; Aagaard, Morten

    This book is about using recent developments in the fields of data analytics and data visualization to frame new ways of identifying target groups in media communication. Based on a mixed-methods approach, the authors combine psychophysiological monitoring (galvanic skin response) with textual...

  10. LANL Robotic Vessel Scanning

    Energy Technology Data Exchange (ETDEWEB)

    Webber, Nels W. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2015-11-25

    Los Alamos National Laboratory in J-1 DARHT Operations Group uses 6ft spherical vessels to contain hazardous materials produced in a hydrodynamic experiment. These contaminated vessels must be analyzed by means of a worker entering the vessel to locate, measure, and document every penetration mark on the vessel. If the worker can be replaced by a highly automated robotic system with a high precision scanner, it will eliminate the risks to the worker and provide management with an accurate 3D model of the vessel presenting the existing damage with the flexibility to manipulate the model for better and more in-depth assessment.The project was successful in meeting the primary goal of installing an automated system which scanned a 6ft vessel with an elapsed time of 45 minutes. This robotic system reduces the total time for the original scope of work by 75 minutes and results in excellent data accumulation and transmission to the 3D model imaging program.

  11. Brain vascular image segmentation based on fuzzy local information C-means clustering

    Science.gov (United States)

    Hu, Chaoen; Liu, Xia; Liang, Xiao; Hui, Hui; Yang, Xin; Tian, Jie

    2017-02-01

    Light sheet fluorescence microscopy (LSFM) is a powerful optical resolution fluorescence microscopy technique which enables to observe the mouse brain vascular network in cellular resolution. However, micro-vessel structures are intensity inhomogeneity in LSFM images, which make an inconvenience for extracting line structures. In this work, we developed a vascular image segmentation method by enhancing vessel details which should be useful for estimating statistics like micro-vessel density. Since the eigenvalues of hessian matrix and its sign describes different geometric structure in images, which enable to construct vascular similarity function and enhance line signals, the main idea of our method is to cluster the pixel values of the enhanced image. Our method contained three steps: 1) calculate the multiscale gradients and the differences between eigenvalues of Hessian matrix. 2) In order to generate the enhanced microvessels structures, a feed forward neural network was trained by 2.26 million pixels for dealing with the correlations between multi-scale gradients and the differences between eigenvalues. 3) The fuzzy local information c-means clustering (FLICM) was used to cluster the pixel values in enhance line signals. To verify the feasibility and effectiveness of this method, mouse brain vascular images have been acquired by a commercial light-sheet microscope in our lab. The experiment of the segmentation method showed that dice similarity coefficient can reach up to 85%. The results illustrated that our approach extracting line structures of blood vessels dramatically improves the vascular image and enable to accurately extract blood vessels in LSFM images.

  12. Heat transfer and fluid flow of blood with nanoparticles through porous vessels in a magnetic field: A quasi-one dimensional analytical approach.

    Science.gov (United States)

    Rahbari, A; Fakour, M; Hamzehnezhad, A; Vakilabadi, M Akbari; Ganji, D D

    2017-01-01

    In the present study, the analytical study on blood flow containing nanoparticles through porous blood vessels is done in presence of magnetic field using Homotopy Perturbation Method (HPM). Blood is considered as the third grade non- Newtonian fluid containing nanoparticles. Viscosity of nanofluid is determined by Constant, Reynolds' and Vogel's models. Some efforts have been made to show the reliability and performance of the present method compared with the numerical method, Runge-Kutta fourth-order. The results reveal that the HPM can achieve suitable results in predicting the solution of these problems. Moreover, the influence of some physical parameters such as pressure gradient, Brownian motion parameter, thermophoresis parameter, magnetic filed intensity and Grashof number on temperature, velocity and nanoparticles concentration profiles is declared in this research. The results reveal that the increase in the pressure gradient and Thermophoresis parameter as well as decrease in the Brownian motion parameter cause the rise in the velocity profile. Furthermore, either increase in Thermophoresis or decrease in Brownian motion parameters results in enhancement in nanoparticle concentration. The highest value of velocity is observed when the Vogel's Model is used for viscosity. Copyright © 2016 Elsevier Inc. All rights reserved.

  13. Near-Tubular Fiber Bundle Segmentation for Diffusion Weighted Imaging: Segmentation Through Frame Reorientation

    Science.gov (United States)

    2010-03-01

    Near-Tubular Fiber Bundle Segmentation for Diffusion Weighted Imaging: Segmentation Through Frame Reorientation Marc Niethammera,b, Christopher Zacha...John Melonakosc, and Allen Tannenbaumc Marc Niethammer: mn@cs.unc.edu; Christopher Zach: cmzach@cs.unc.edu; John Melonakos: jmelonak@ece.gatech.edu...modification of a recent segmentation approach by Bresson et al. allows for a convex optimization formulation of the segmentation problem, combining

  14. Segmentation of the foveal microvasculature using deep learning networks

    Science.gov (United States)

    Prentašić, Pavle; Heisler, Morgan; Mammo, Zaid; Lee, Sieun; Merkur, Andrew; Navajas, Eduardo; Beg, Mirza Faisal; Šarunić, Marinko; Lončarić, Sven

    2016-07-01

    Accurate segmentation of the retinal microvasculature is a critical step in the quantitative analysis of the retinal circulation, which can be an important marker in evaluating the severity of retinal diseases. As manual segmentation remains the gold standard for segmentation of optical coherence tomography angiography (OCT-A) images, we present a method for automating the segmentation of OCT-A images using deep neural networks (DNNs). Eighty OCT-A images of the foveal region in 12 eyes from 6 healthy volunteers were acquired using a prototype OCT-A system and subsequently manually segmented. The automated segmentation of the blood vessels in the OCT-A images was then performed by classifying each pixel into vessel or nonvessel class using deep convolutional neural networks. When the automated results were compared against the manual segmentation results, a maximum mean accuracy of 0.83 was obtained. When the automated results were compared with inter and intrarater accuracies, the automated results were shown to be comparable to the human raters suggesting that segmentation using DNNs is comparable to a second manual rater. As manually segmenting the retinal microvasculature is a tedious task, having a reliable automated output such as automated segmentation by DNNs, is an important step in creating an automated output.

  15. Accurate and reliable segmentation of the optic disc in digital fundus images.

    Science.gov (United States)

    Giachetti, Andrea; Ballerini, Lucia; Trucco, Emanuele

    2014-07-01

    We describe a complete pipeline for the detection and accurate automatic segmentation of the optic disc in digital fundus images. This procedure provides separation of vascular information and accurate inpainting of vessel-removed images, symmetry-based optic disc localization, and fitting of incrementally complex contour models at increasing resolutions using information related to inpainted images and vessel masks. Validation experiments, performed on a large dataset of images of healthy and pathological eyes, annotated by experts and partially graded with a quality label, demonstrate the good performances of the proposed approach. The method is able to detect the optic disc and trace its contours better than the other systems presented in the literature and tested on the same data. The average error in the obtained contour masks is reasonably close to the interoperator errors and suitable for practical applications. The optic disc segmentation pipeline is currently integrated in a complete software suite for the semiautomatic quantification of retinal vessel properties from fundus camera images (VAMPIRE).

  16. Optimally segmented permanent magnet structures

    DEFF Research Database (Denmark)

    Insinga, Andrea Roberto; Bjørk, Rasmus; Smith, Anders

    2016-01-01

    We present an optimization approach which can be employed to calculate the globally optimal segmentation of a two-dimensional magnetic system into uniformly magnetized pieces. For each segment the algorithm calculates the optimal shape and the optimal direction of the remanent flux density vector......, with respect to a linear objective functional. We illustrate the approach with results for magnet design problems from different areas, such as a permanent magnet electric motor, a beam focusing quadrupole magnet for particle accelerators and a rotary device for magnetic refrigeration....

  17. Polarimetric Segmentation Using Wishart Test Statistic

    DEFF Research Database (Denmark)

    Skriver, Henning; Schou, Jesper; Nielsen, Allan Aasbjerg

    2002-01-01

    ) approach, which is a merging algorithm for single channel SAR images. The polarimetric version described in this paper uses the above-mentioned test statistic for merging. The segmentation algorithm has been applied to polarimetric SAR data from the Danish dual-frequency, airborne polarimetric SAR, EMISAR......A newly developed test statistic for equality of two complex covariance matrices following the complex Wishart distribution and an associated asymptotic probability for the test statistic has been used in a segmentation algorithm. The segmentation algorithm is based on the MUM (merge using moments....... The results show clearly an improved segmentation performance for the full polarimetric algorithm compared to single channel approaches....

  18. Watertight modeling and segmentation of bifurcated Coronary arteries for blood flow simulation using CT imaging.

    Science.gov (United States)

    Zhou, Haoyin; Sun, Peng; Ha, Seongmin; Lundine, Devon; Xiong, Guanglei

    2016-10-01

    Image-based simulation of blood flow using computational fluid dynamics has been shown to play an important role in the diagnosis of ischemic coronary artery disease. Accurate extraction of complex coronary artery structures in a watertight geometry is a prerequisite, but manual segmentation is both tedious and subjective. Several semi- and fully automated coronary artery extraction approaches have been developed but have faced several challenges. Conventional voxel-based methods allow for watertight segmentation but are slow and difficult to incorporate expert knowledge. Machine learning based methods are relatively fast and capture rich information embedded in manual annotations. Although sufficient for visualization and analysis of coronary anatomy, these methods cannot be used directly for blood flow simulation if the coronary vasculature is represented as a loose combination of tubular structures and the bifurcation geometry is improperly modeled. In this paper, we propose a novel method to extract branching coronary arteries from CT imaging with a focus on explicit bifurcation modeling and application of machine learning. A bifurcation lumen is firstly modeled by generating the convex hull to join tubular vessel branches. Guided by the pre-determined centerline, machine learning based segmentation is performed to adapt the bifurcation lumen model to target vessel boundaries and smoothed by subdivision surfaces. Our experiments show the constructed coronary artery geometry from CT imaging is accurate by comparing results against the manually annotated ground-truths, and can be directly applied to coronary blood flow simulation. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Breast Contrast Enhanced MR Imaging: Semi-Automatic Detection of Vascular Map and Predominant Feeding Vessel.

    Science.gov (United States)

    Petrillo, Antonella; Fusco, Roberta; Filice, Salvatore; Granata, Vincenza; Catalano, Orlando; Vallone, Paolo; Di Bonito, Maurizio; D'Aiuto, Massimiliano; Rinaldo, Massimo; Capasso, Immacolata; Sansone, Mario

    2016-01-01

    To obtain breast vascular map and to assess correlation between predominant feeding vessel and tumor location with a semi-automatic method compared to conventional radiologic reading. 148 malignant and 75 benign breast lesions were included. All patients underwent bilateral MR imaging. Written informed consent was obtained from the patients before MRI. The local ethics committee granted approval for this study. Semi-automatic breast vascular map and predominant vessel detection was performed on MRI, for each patient. Semi-automatic detection (depending on grey levels threshold manually chosen by radiologist) was compared with results of two expert radiologists; inter-observer variability and reliability of semi-automatic approach were assessed. Anatomic analysis of breast lesions revealed that 20% of patients had masses in internal half, 50% in external half and the 30% in subareolar/central area. As regards the 44 tumors in internal half, based on radiologic consensus, 40 demonstrated a predominant feeding vessel (61% were supplied by internal thoracic vessels, 14% by lateral thoracic vessels, 16% by both thoracic vessels and 9% had no predominant feeding vessel-pfeeding vessel (66% were supplied by internal thoracic vessels, 11% by lateral thoracic vessels, 9% by both thoracic vessels and 14% had no predominant feeding vessel-pfeeding vessel (25% were supplied by internal thoracic vessels, 39% by lateral thoracic vessels, 18% by both thoracic vessels and 18% had no predominant feeding vessel-pfeeding vessel (27% were supplied by internal thoracic vessels, 45% by lateral thoracic vessels, 4% by both thoracic vessels and 24% had no predominant feeding vessel-pfeeding vessel. An excellent reliability for semi-automatic assessment (Cronbach's alpha = 0.96) was reported. Predominant feeding vessel location was correlated with breast lesion location: internal thoracic artery supplied the highest proportion of breasts with tumor in internal half and lateral thoracic

  20. 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.

  1. What are the residual stresses doing in our blood vessels?

    Science.gov (United States)

    Fung, Y C

    1991-01-01

    We show that the residual strain and stress in the blood vessels are not zero, and that the zero-stress state of a blood vessel consists of open-sector segments whose opening angles vary along the longitudinal axis of the vessel. When the homeostatic state of the blood vessel is changed, e.g., by a sudden hypertension, the opening angle will change. The time constant of the opening angle change is a few hours (e.g., in the pulmonary artery) or a few days (e.g., in the aorta). From a kinematic point of view, a change of opening angle is a bending of the blood vessel wall, which is caused by a nonuniformly distributed residual strain. From a mechanics point of view, changes of blood pressure and residual strain cause change of stress in the blood vessel wall. Correlating the stress with the change of residual strain yields a fundamental biological law relating the rate of growth or resorption of tissue with the stress in the tissue. Thus, residual stresses are related to the remodeling of the blood vessel wall. Our blood vessel remodels itself when stress changes. The stress-growth law provides a biomechanical foundation for tissue engineering.

  2. Enhancing supply vessel safety

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2002-07-01

    A supply-vessel bridge installation consists of a navigating bridge and a control position aft, from which operators control the ship when close to rigs or platforms, and operate winches and other loading equipment. The international Convention for Safety of I Ale at Sea (SOLAS) does not regulate the layout, so design varies to a large degree, often causing an imperfect working environment. As for other types of ships, more than half the offshore service vessel accidents at sea are caused by bridge system failures. A majority can be traced back to technical design, and operational errors. The research and development project NAUT-OSV is a response to the offshore industry's safety concerns. Analysis of 24 incidents involving contact or collision between supply vessels and offshore installations owned or operated by Norwegian companies indicated that failures in the bridge system were often the cause.

  3. CDIS: Circle Density Based Iris Segmentation

    Science.gov (United States)

    Gupta, Anand; Kumari, Anita; Kundu, Boris; Agarwal, Isha

    Biometrics is an automated approach of measuring and analysing physical and behavioural characteristics for identity verification. The stability of the Iris texture makes it a robust biometric tool for security and authentication purposes. Reliable Segmentation of Iris is a necessary precondition as an error at this stage will propagate into later stages and requires proper segmentation of non-ideal images having noises like eyelashes, etc. Iris Segmentation work has been done earlier but we feel it lacks in detecting iris in low contrast images, removal of specular reflections, eyelids and eyelashes. Hence, it motivates us to enhance the said parameters. Thus, we advocate a new approach CDIS for Iris segmentation along with new algorithms for removal of eyelashes, eyelids and specular reflections and pupil segmentation. The results obtained have been presented using GAR vs. FAR graphs at the end and have been compared with prior works related to segmentation of iris.

  4. GOLD PRESSURE VESSEL SEAL

    Science.gov (United States)

    Smith, A.E.

    1963-11-26

    An improved seal between the piston and die member of a piston-cylinder type pressure vessel is presented. A layer of gold, of sufficient thickness to provide an interference fit between the piston and die member, is plated on the contacting surface of at least one of the members. (AEC)

  5. Network of endocardial vessels.

    Science.gov (United States)

    Lee, Byung-Cheon; Kim, Hong Bae; Sung, Baeckkyoung; Kim, Ki Woo; Sohn, Jamin; Son, Boram; Chang, Byung-Joon; Soh, Kwang-Sup

    2011-01-01

    Although there have been reports on threadlike structures inside the heart, they have received little attention. We aimed to develop a method for observing such structures and to reveal their ultrastructures. An in situ staining method, which uses a series of procedures of 0.2-0.4% trypan blue spraying and washing, was applied to observe threadlike structures on the surfaces of endocardia. The threadlike structures were isolated and observed by using confocal laser scanning microscopy (CLSM) and transmission electron microscopy (TEM). Networks of endocardial vessels (20 μm in thickness) with expansions (40-100 μm in diameter) were visualized; they were movable on the endocardium of the bovine atrium and ventricle. CLSM showed that (1) rod-shaped nuclei were aligned along the longitudinal direction of the endocardial vessel and (2) there were many cells inside the expansion. TEM on the endocardial vessel revealed that (1) there existed multiple lumens (1-7 μm in diameter) and (2) the extracellular matrices mostly consisted of collagen fibers, which were aligned along the longitudinal direction of the endocardial vessel or were locally organized in reticular structures. We investigated the endocardial circulatory system in bovine cardiac chambers and its ultrastructures, such as nucleic distributions, microlumens, and collagenous extracellular matrices. Copyright © 2011 S. Karger AG, Basel.

  6. Pressurized Vessel Slurry Pumping

    Energy Technology Data Exchange (ETDEWEB)

    Pound, C.R.

    2001-09-17

    This report summarizes testing of an alternate ''pressurized vessel slurry pumping'' apparatus. The principle is similar to rural domestic water systems and ''acid eggs'' used in chemical laboratories in that material is extruded by displacement with compressed air.

  7. 3D deeply supervised network for automated segmentation of volumetric medical images.

    Science.gov (United States)

    Dou, Qi; Yu, Lequan; Chen, Hao; Jin, Yueming; Yang, Xin; Qin, Jing; Heng, Pheng-Ann

    2017-10-01

    While deep convolutional neural networks (CNNs) have achieved remarkable success in 2D medical image segmentation, it is still a difficult task for CNNs to segment important organs or structures from 3D medical images owing to several mutually affected challenges, including the complicated anatomical environments in volumetric images, optimization difficulties of 3D networks and inadequacy of training samples. In this paper, we present a novel and efficient 3D fully convolutional network equipped with a 3D deep supervision mechanism to comprehensively address these challenges; we call it 3D DSN. Our proposed 3D DSN is capable of conducting volume-to-volume learning and inference, which can eliminate redundant computations and alleviate the risk of over-fitting on limited training data. More importantly, the 3D deep supervision mechanism can effectively cope with the optimization problem of gradients vanishing or exploding when training a 3D deep model, accelerating the convergence speed and simultaneously improving the discrimination capability. Such a mechanism is developed by deriving an objective function that directly guides the training of both lower and upper layers in the network, so that the adverse effects of unstable gradient changes can be counteracted during the training procedure. We also employ a fully connected conditional random field model as a post-processing step to refine the segmentation results. We have extensively validated the proposed 3D DSN on two typical yet challenging volumetric medical image segmentation tasks: (i) liver segmentation from 3D CT scans and (ii) whole heart and great vessels segmentation from 3D MR images, by participating two grand challenges held in conjunction with MICCAI. We have achieved competitive segmentation results to state-of-the-art approaches in both challenges with a much faster speed, corroborating the effectiveness of our proposed 3D DSN. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. A Novel Antegrade Approach for Simultaneous Carotid Endarterectomy and Angioplasty of Proximal Lesions in Patients with Tandem Stenosis of Supraaortic Arch Vessels.

    Science.gov (United States)

    Radak, Djordje; Tanaskovic, Slobodan; Sagic, Dragan; Antonic, Zelimir; Gajin, Predrag; Babic, Srdjan; Neskovic, Mihailo; Matic, Predrag; Kovacevic, Vladimir; Nenezic, Dragoslav; Ilijevski, Nenad

    2017-10-01

    To date, all published studies analyzing simultaneous treatment of carotid and proximal atherosclerotic lesions are describing retrograde approach and several technical variations. In the presented study, for the first time, antegrade approach is described for simultaneous carotid endarterectomy (CEA) and associated brachiocephalic trunk (BCT) or common carotid artery (CCA) angioplasty in the hybrid operating room. From January 2012 till January 2016, antegrade hybrid procedures were performed in 18 patients. All patients were admitted to our institute for elective supraaortic arch multidetector computed tomography angiography when significant simultaneous proximal and distal supraaortic arch lesions were revealed. After surgical exposure of carotid arteries, proximal lesions were crossed by antegrade approach. Prior to stent placement, internal carotid artery (ICA) is clamped at its origin with the guidewire placed in the external carotid artery (ECA). After primary stenting and control arteriography, CCA and ECA are clamped and the ICA clamp moved more distally. An arteriotomy is performed in the CCA, with flushing of possible debris and thrombus before performance of the eversion CEA, once again flushing before completion of the anastomosis. Follow-up ranged from 6 to 36 months with average follow-up of 22.15 ± 11.31 months. All procedures went uneventfully. Out of 18 patients, 11 were males and 7 females, mean age 66.6 ± 3.82 years. In 10 patients (55.5%), simultaneous CEA and CCA angioplasty was performed, in 7 patients (38.9%) CEA and BCT angioplasty, and in 1 patient (5.5%) tubular graft interposition between the CCA and the ICA and CCA angioplasty. In 6 patients (33.3%), CCA/BCT balloon angioplasty alone was performed simultaneously with CEA. None of the patient had postoperative transient ischemic attack, stroke, hematoma, dissection, myocardial infarction, or ischemia in the early postoperative period and during the follow-up. There were no

  9. Non-uniform object counting method in large-format pyramid images applied to CD31 vessel counting in whole-mount digital pathology sections

    Science.gov (United States)

    Murray, Mayan; Hill, Melissa L.; Liu, Kela; Mainprize, James G.; Yaffe, Martin J.

    2016-03-01

    Whole-mount pathology imaging has the potential to revolutionize clinical practice by preserving context lost when tissue is cut to fit onto conventional slides. Whole-mount digital images are very large, ranging from 4GB to greater than 50GB, making concurrent processing infeasible. Block-processing is a method commonly used to divide the image into smaller blocks and process them individually. This approach is useful for certain tasks, but leads to over-counting objects located on the seams between blocks. This issue is exaggerated as the block size decreases. In this work we apply a novel technique to enumerate vessels, a clinical task that would benefit from automation in whole-mount images. Whole-mount sections of rabbit VX2 tumors were digitized. Color thresholding was used to segment the brown CD31- DAB stained vessels. This vessel enumeration was applied to the entire whole-mount image in two distinct phases of block-processing. The first (whole-processing) phase used a basic grid and only counted objects that did not intersect the block's borders. The second (seam-processing) phase used a shifted grid to ensure all blocks captured the block-seam regions from the original grid. Only objects touching this seam-intersection were counted. For validation, segmented vessels were randomly embedded into a whole-mount image. The technique was tested on the image using 24 different block-widths. Results indicated that the error reaches a minimum at a block-width equal to the maximum vessel length, with no improvement as the block-width increases further. Object-density maps showed very good correlation between the vessel-dense regions and the pathologist outlined tumor regions.

  10. Precise segmentation of 3-D magnetic resonance angiography.

    Science.gov (United States)

    El-Baz, Ayman; Elnakib, Ahmed; Khalifa, Fahmi; El-Ghar, Mohamed Abou; McClure, Patrick; Soliman, Ahmed; Gimel'farb, Georgy

    2012-07-01

    Accurate automatic extraction of a 3-D cerebrovascular system from images obtained by time-of-flight (TOF) or phase contrast (PC) magnetic resonance angiography (MRA) is a challenging segmentation problem due to the small size objects of interest (blood vessels) in each 2-D MRA slice and complex surrounding anatomical structures (e.g., fat, bones, or gray and white brain matter). We show that due to the multimodal nature of MRA data, blood vessels can be accurately separated from the background in each slice using a voxel-wise classification based on precisely identified probability models of voxel intensities. To identify the models, an empirical marginal probability distribution of intensities is closely approximated with a linear combination of discrete Gaussians (LCDG) with alternate signs, using our previous EM-based techniques for precise linear combination of Gaussian-approximation adapted to deal with the LCDGs. The high accuracy of the proposed approach is experimentally validated on 85 real MRA datasets (50 TOF and 35 PC) as well as on synthetic MRA data for special 3-D geometrical phantoms of known shapes.

  11. Blood vessel modeling for interactive simulation of interventional neuroradiology procedures.

    Science.gov (United States)

    Kerrien, E; Yureidini, A; Dequidt, J; Duriez, C; Anxionnat, R; Cotin, S

    2017-01-01

    Endovascular interventions can benefit from interactive simulation in their training phase but also during pre-operative and intra-operative phases if simulation scenarios are based on patient data. A key feature in this context is the ability to extract, from patient images, models of blood vessels that impede neither the realism nor the performance of simulation. This paper addresses both the segmentation and reconstruction of the vasculature from 3D Rotational Angiography data, and adapted to simulation: An original tracking algorithm is proposed to segment the vessel tree while filtering points extracted at the vessel surface in the vicinity of each point on the centerline; then an automatic procedure is described to reconstruct each local unstructured point set as a skeleton-based implicit surface (blobby model). The output of successively applying both algorithms is a new model of vasculature as a tree of local implicit models. The segmentation algorithm is compared with Multiple Hypothesis Testing (MHT) algorithm (Friman et al., 2010) on patient data, showing its greater ability to track blood vessels. The reconstruction algorithm is evaluated on both synthetic and patient data and demonstrate its ability to fit points with a subvoxel precision. Various tests are also reported where our model is used to simulate catheter navigation in interventional neuroradiology. An excellent realism, and much lower computational costs are reported when compared to triangular mesh surface models. Copyright © 2016 Elsevier B.V. All rights reserved.

  12. Analysing the Methods of Dzongkha Word Segmentation

    Directory of Open Access Journals (Sweden)

    Dhungyel Parshu Ram

    2017-05-01

    Full Text Available In both Chinese and Dzongkha languages, the greatest challenge is to identify the word boundaries because there are no word delimiters as it is in English and other Western languages. Therefore, preprocessing and word segmentation is the first step in Dzongkha language processing, such as translation, spell-checking, and information retrieval. Research on Chinese word segmentation was conducted long time ago. Therefore, it is relatively mature, but the Dzongkha word segmentation has been less studied by researchers. In the paper, we have investigated this major problem in Dzongkha language processing using a probabilistic approach for selecting valid segments with probability being computed on the basis of the corpus.

  13. Thermal destruction of vessels with liquid upon heating

    Science.gov (United States)

    Zverev, V. G.; Goldin, V. D.; Svetashkov, A. A.

    2016-04-01

    A new engineering technique of calculating the heating and thermal destruction of vessels containing liquid under extreme thermal loading conditions is offered. The heating of the shell and the internal vessel volume is described on the basis of the thermodynamic approach. The pressure growth in a vessel is a result of gas heating and liquid evaporation. Stresses within the shell and its destruction conditions are determined, which allows predicting the critical time of destruction upon heating. The calculation and experimental data for pressure growth inside the vessel are in good agreement.

  14. Hawaii Abandoned Vessel Inventory, Kauai

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA Abandoned Vessel Project Data for Kauai. Abandoned vessels pose a significant threat to the NOAA Trust resources through physical destruction of coral habitats...

  15. CNMI Abandoned Vessel Inventory, Tinian

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA Abandoned Vessel Project Data for Tinian. Abandoned vessels pose a significant threat to the NOAA Trust resources through physical destruction of coral habitats...

  16. Puerto Rico Abandoned Vessel Inventory

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA Abandoned Vessel Project Data for Puerto Rico. Abandoned vessels pose a significant threat to the NOAA Trust resources through physical destruction of coral...

  17. American Samoa Abandoned Vessel Inventory

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA Abandoned Vessel Project Data for American Samoa. Abandoned vessels pose a significant threat to the NOAA Trust resources through physical destruction of coral...

  18. Hawaii Abandoned Vessel Inventory, Oahu

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA Abandoned Vessel Project Data for Oahu, Hawaii. Abandoned vessels pose a significant threat to the NOAA Trust resources through physical destruction of coral...

  19. Hawaii Abandoned Vessel Inventory, Molokai

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA Abandoned Vessel Project Data for Molokai, Hawaii. Abandoned vessels pose a significant threat to the NOAA Trust resources through physical destruction of coral...

  20. CNMI Abandoned Vessel Inventory, Rota

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA Abandoned Vessel Project Data for Rota. Abandoned vessels pose a significant threat to the NOAA Trust resources through physical destruction of coral habitats...

  1. Hawaii Abandoned Vessel Inventory, Lanai

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA Abandoned Vessel Project Data for Lanai. Abandoned vessels pose a significant threat to the NOAA Trust resources through physical destruction of coral habitats...

  2. For-Hire Vessel Directory

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Vessel Directory is maintained as the sample frame for the For-Hire Survey. I contains data on for-hire vessels on the Atlantic and Gulf coasts. Data include...

  3. CNMI Abandoned Vessel Inventory, Saipan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA Abandoned Vessel Project Data for Saipan. Abandoned vessels pose a significant threat to the NOAA Trust resources through physical destruction of coral habitats...

  4. Hawaii Abandoned Vessel Inventory, Maui

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA Abandoned Vessel Project Data for Maui. Abandoned vessels pose a significant threat to the NOAA Trust resources through physical destruction of coral habitats...

  5. Vessels in Transit - Web Tool

    Data.gov (United States)

    Department of Transportation — A web tool that provides real-time information on vessels transiting the Saint Lawrence Seaway. Visitors may sort by order of turn, vessel name, or last location in...

  6. Computer-aided detection of human cone photoreceptor inner segments using multi-scale circular voting

    Science.gov (United States)

    Liu, Jianfei; Dubra, Alfredo; Tam, Johnny

    2016-03-01

    Cone photoreceptors are highly specialized cells responsible for the origin of vision in the human eye. Their inner segments can be noninvasively visualized using adaptive optics scanning light ophthalmoscopes (AOSLOs) with nonconfocal split detection capabilities. Monitoring the number of cones can lead to more precise metrics for real-time diagnosis and assessment of disease progression. Cell identification in split detection AOSLO images is hindered by cell regions with heterogeneous intensity arising from shadowing effects and low contrast boundaries due to overlying blood vessels. Here, we present a multi-scale circular voting approach to overcome these challenges through the novel combination of: 1) iterative circular voting to identify candidate cells based on their circular structures, 2) a multi-scale strategy to identify the optimal circular voting response, and 3) clustering to improve robustness while removing false positives. We acquired images from three healthy subjects at various locations on the retina and manually labeled cell locations to create ground-truth for evaluating the detection accuracy. The images span a large range of cell densities. The overall recall, precision, and F1 score were 91±4%, 84±10%, and 87±7% (Mean±SD). Results showed that our method for the identification of cone photoreceptor inner segments performs well even with low contrast cell boundaries and vessel obscuration. These encouraging results demonstrate that the proposed approach can robustly and accurately identify cells in split detection AOSLO images.

  7. Pressure vessel design manual

    Energy Technology Data Exchange (ETDEWEB)

    Moss, D.R.

    1987-01-01

    The first section of the book covers types of loadings, failures, and stress theories, and how they apply to pressure vessels. The book delineates the procedures for designing typical components as well as those for designing large openings in cylindrical shells, ring girders, davits, platforms, bins and elevated tanks. The techniques for designing conical transitions, cone-cylinder intersections, intermediate heads, flat heads, and spherically dished covers are also described. The book covers the design of vessel supports subject to wind and seismic loads and one section is devoted to the five major ways of analyzing loads on shells and heads. Each procedure is detailed enough to size all welds, bolts, and plate thicknesses and to determine actual stresses.

  8. New research vessels

    Science.gov (United States)

    1984-04-01

    Two “new” ocean-going research vessels operated by the Scripps Institution of Oceanography and the National Science Foundation (NSF) will soon begin full-time scientific duties off the coast of California and in the Antarctic, respectively. The 37.5-m Scripps vessel, named Robert Gordon Sprout in honor of the ex-president of the University of California, replaces the smaller ship Ellen B. Scripps, which had served the institution since 1965. The new ship is a slightly modified Gulf Coast workboat. Under the name of Midnight Alaskan, it had been used for high-resolution geophysical surveys in American and Latin American waters by such firms as Arco Oil & Gas, Exxon, Pennzoil, and Racal-Decca before its purchase by Scripps from a Lousiana chartering firm last summer.

  9. Large vessel vasculitides

    OpenAIRE

    Morović-Vergles, Jadranka; Pukšić, Silva; Gudelj Gračanin, Ana

    2013-01-01

    Large vessel vasculitis includes Giant cell arteritis and Takayasu arteritis. Giant cell arteritis is the most common form of vasculitis affect patients aged 50 years or over. The diagnosis should be considered in older patients who present with new onset of headache, visual disturbance, polymyalgia rheumatica and/or fever unknown cause. Glucocorticoides remain the cornerstone of therapy. Takayasu arteritis is a chronic panarteritis of the aorta ant its major branches presenting commonly in y...

  10. Very Versatile Vessel

    Science.gov (United States)

    2009-09-01

    data. This source provides information on aluminum hydrofoil vessels without the added weight of foil structures. The composite armor around the...seating compartment. The sides should also limit wave splash on the deck. The freeboard should contribute reserve buoyancy , increasing large-angle and...Resistance, Powering, and Propulsion Savitsky’s Method Since model testing data or other reliable performance data was unavailable for the proposed

  11. 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.

  12. 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.

  13. Discriminative parameter estimation for random walks segmentation.

    Science.gov (United States)

    Baudin, Pierre-Yves; Goodman, Danny; Kumrnar, Puneet; Azzabou, Noura; Carlier, Pierre G; Paragios, Nikos; Kumar, M Pawan

    2013-01-01

    The Random Walks (RW) algorithm is one of the most efficient and easy-to-use probabilistic segmentation methods. By combining contrast terms with prior terms, it provides accurate segmentations of medical images in a fully automated manner. However, one of the main drawbacks of using the RW algorithm is that its parameters have to be hand-tuned. we propose a novel discriminative learning framework that estimates the parameters using a training dataset. The main challenge we face is that the training samples are not fully supervised. Specifically, they provide a hard segmentation of the images, instead of a probabilistic segmentation. We overcome this challenge by treating the optimal probabilistic segmentation that is compatible with the given hard segmentation as a latent variable. This allows us to employ the latent support vector machine formulation for parameter estimation. We show that our approach significantly outperforms the baseline methods on a challenging dataset consisting of real clinical 3D MRI volumes of skeletal muscles.

  14. 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.

  15. Hierarchical photo stream segmentation using context

    Science.gov (United States)

    Gong, Bo; Jain, Ramesh

    2008-01-01

    Photo stream segmentation is to segment photo streams into groups, each of which corresponds to an event. Photo stream segmentation can be done with or without prior knowledge of event structure. In this paper, we study the problem by assuming that there is no a priori event model available. Although both context and content information are important for photo stream segmentation, we focus on investigating the usage of context information in this work. We consider different information components of context such as time, location, and optical setting for inexpensive segmentation of photo streams from common users of modern digital camera. As events are hierarchical, we propose to segment photo stream using hierarchical mixture model. We compare the generated hierarchy with that created by users to see how well results can be obtained without knowing the prior event model. We experimented with about 3000 photos from amateur photographers to study the efficacy of the approach for these context information components.

  16. Boosted learned kernels for data-driven vesselness measure

    Science.gov (United States)

    Grisan, E.

    2017-03-01

    Common vessel centerline extraction methods rely on the computation of a measure providing the likeness of the local appearance of the data to a curvilinear tube-like structure. The most popular techniques rely on empirically designed (hand crafted) measurements as the widely used Hessian vesselness, the recent oriented flux tubeness or filters (e.g. the Gaussian matched filter) that are developed to respond to local features, without exploiting any context information nor the rich structural information embedded in the data. At variance with the previously proposed methods, we propose a completely data-driven approach for learning a vesselness measure from expert-annotated dataset. For each data point (voxel or pixel), we extract the intensity values in a neighborhood region, and estimate the discriminative convolutional kernel yielding a positive response for vessel data and negative response for non-vessel data. The process is iterated within a boosting framework, providing a set of linear filters, whose combined response is the learned vesselness measure. We show the results of the general-use proposed method on the DRIVE retinal images dataset, comparing its performance against the hessian-based vesselness, oriented flux antisymmetry tubeness, and vesselness learned with a probabilistic boosting tree or with a regression tree. We demonstrate the superiority of our approach that yields a vessel detection accuracy of 0.95, with respect to 0.92 (hessian), 0.90 (oriented flux) and 0.85 (boosting tree).

  17. Evaluation of segmentation methods on head and neck CT: Auto-segmentation challenge 2015.

    Science.gov (United States)

    Raudaschl, Patrik F; Zaffino, Paolo; Sharp, Gregory C; Spadea, Maria Francesca; Chen, Antong; Dawant, Benoit M; Albrecht, Thomas; Gass, Tobias; Langguth, Christoph; Lüthi, Marcel; Jung, Florian; Knapp, Oliver; Wesarg, Stefan; Mannion-Haworth, Richard; Bowes, Mike; Ashman, Annaliese; Guillard, Gwenael; Brett, Alan; Vincent, Graham; Orbes-Arteaga, Mauricio; Cárdenas-Peña, David; Castellanos-Dominguez, German; Aghdasi, Nava; Li, Yangming; Berens, Angelique; Moe, Kris; Hannaford, Blake; Schubert, Rainer; Fritscher, Karl D

    2017-05-01

    Automated delineation of structures and organs is a key step in medical imaging. However, due to the large number and diversity of structures and the large variety of segmentation algorithms, a consensus is lacking as to which automated segmentation method works best for certain applications. Segmentation challenges are a good approach for unbiased evaluation and comparison of segmentation algorithms. In this work, we describe and present the results of the Head and Neck Auto-Segmentation Challenge 2015, a satellite event at the Medical Image Computing and Computer Assisted Interventions (MICCAI) 2015 conference. Six teams participated in a challenge to segment nine structures in the head and neck region of CT images: brainstem, mandible, chiasm, bilateral optic nerves, bilateral parotid glands, and bilateral submandibular glands. This paper presents the quantitative results of this challenge using multiple established error metrics and a well-defined ranking system. The strengths and weaknesses of the different auto-segmentation approaches are analyzed and discussed. The Head and Neck Auto-Segmentation Challenge 2015 was a good opportunity to assess the current state-of-the-art in segmentation of organs at risk for radiotherapy treatment. Participating teams had the possibility to compare their approaches to other methods under unbiased and standardized circumstances. The results demonstrate a clear tendency toward more general purpose and fewer structure-specific segmentation algorithms. © 2017 American Association of Physicists in Medicine.

  18. Multi-segmental neurofibromatosis

    OpenAIRE

    Kumar Sudhir; Kumar Ravi

    2004-01-01

    Neurofibromatosis (NF), one of the commonest phakomatoses, is characterized by varied clinical manifestations. Segmental NF is one of the uncommon subtypes of NF. We report a young adult presenting with asymptomatic skin lesions- neurofibromas and café-au-lait macules- over localized areas of the lower back, affecting more than one segment. None of the family members were found to have features of segmental NF. Segmental NF may be misdiagnosed as a birthmark or remain undiagnosed for l...

  19. A framework for retinal vasculature segmentation based on matched filters.

    Science.gov (United States)

    Meng, Xianjing; Yin, Yilong; Yang, Gongping; Han, Zhe; Yan, Xiaowei

    2015-10-24

    Automatic fundus image processing plays a significant role in computer-assisted retinopathy diagnosis. As retinal vasculature is an important anatomical structure in ophthalmic images, recently, retinal vasculature segmentation has received considerable attention from researchers. A segmentation method usually consists of three steps: preprocessing, segmentation, post-processing. Most of the existing methods emphasize on the segmentation step. In our opinion, the vessels and background can be easily separable when suitable preprocessing exists. This paper represents a new matched filter-based vasculature segmentation method for 2-D retinal images. First of all, a raw segmentation is acquired by thresholding the images preprocessed using weighted improved circular gabor filter and multi-directional multi-scale second derivation of Gaussian. After that, the raw segmented image is fine-tuned by a set of novel elongating filters. Finally, we eliminate the speckle like regions and isolated pixels, most of which are non-vessel noises and miss-classified fovea or pathological regions. The performance of the proposed method is examined on two popularly used benchmark databases: DRIVE and STARE. The accuracy values are 95.29 and 95.69 %, respectively, without a significant degradation of specificity and sensitivity. The performance of the proposed method is significantly better than almost all unsupervised methods, in addition, comparable to most of the existing supervised vasculature segmentation methods.

  20. Analysis of HRCT-derived xylem network reveals reverse flow in some vessels.

    Science.gov (United States)

    Lee, Eric F; Matthews, Mark A; McElrone, Andrew J; Phillips, Ronald J; Shackel, Kenneth A; Brodersen, Craig R

    2013-09-21

    Long distance water and nutrient transport in plants is dependent on the proper functioning of xylem networks, a series of interconnected pipe-like cells that are vulnerable to hydraulic dysfunction as a result of drought-induced embolism and/or xylem-dwelling pathogens. Here, flow in xylem vessels was modeled to determine the role of vessel connectivity by using three dimensional xylem networks derived from High Resolution Computed Tomography (HRCT) images of grapevine (Vitis vinifera cv. 'Chardonnay') stems. Flow in 4-27% of the vessel segments (i.e. any section of vessel elements between connection points associated with intervessel pits) was found to be oriented in the direction opposite to the bulk flow under normal transpiration conditions. In order for the flow in a segment to be in the reverse direction, specific requirements were determined for the location of connections, distribution of vessel endings, diameters of the connected vessels, and the conductivity of the connections. Increasing connectivity and decreasing vessel length yielded increasing numbers of reverse flow segments until a maximum value was reached, after which more interconnected networks and smaller average vessel lengths yielded a decrease in the number of reverse flow segments. Xylem vessel relays also encouraged the formation of reverse flow segments. Based on the calculated flow rates in the xylem network, the downward spread of Xylella fastidiosa bacteria in grape stems was modeled, and reverse flow was shown to be an additional mechanism for the movement of bacteria to the trunk of grapevine. Copyright © 2013 Elsevier Ltd. All rights reserved.

  1. Optimally segmented magnetic structures

    DEFF Research Database (Denmark)

    Insinga, Andrea Roberto; Bahl, Christian; Bjørk, Rasmus

    We present a semi-analytical algorithm for magnet design problems, which calculates the optimal way to subdivide a given design region into uniformly magnetized segments.The availability of powerful rare-earth magnetic materials such as Nd-Fe-B has broadened the range of applications of permanent...... is not available.We will illustrate the results for magnet design problems from different areas, such as electric motors/generators (as the example in the picture), beam focusing for particle accelerators and magnetic refrigeration devices....... magnets[1][2]. However, the powerful rare-earth magnets are generally expensive, so both the scientific and industrial communities have devoted a lot of effort into developing suitable design methods. Even so, many magnet optimization algorithms either are based on heuristic approaches[3...

  2. Evaluation of multimodal segmentation based on 3D T1-, T2- and FLAIR-weighted images - the difficulty of choosing.

    Science.gov (United States)

    Lindig, Tobias; Kotikalapudi, Raviteja; Schweikardt, Daniel; Martin, Pascal; Bender, Friedemann; Klose, Uwe; Ernemann, Ulrike; Focke, Niels K; Bender, Benjamin

    2017-02-07

    Voxel-based morphometry is still mainly based on T1-weighted MRI scans. Misclassification of vessels and dura mater as gray matter has been previously reported. Goal of the present work was to evaluate the effect of multimodal segmentation methods available in SPM12, and their influence on identification of age related atrophy and lesion detection in epilepsy patients. 3D T1-, T2- and FLAIR-images of 77 healthy adults (mean age 35.8 years, 19-66 years, 45 females), 7 patients with malformation of cortical development (MCD) (mean age 28.1 years,19-40 years, 3 females), and 5 patients with left hippocampal sclerosis (LHS) (mean age 49.0 years, 25-67 years, 3 females) from a 3T scanner were evaluated. Segmentation based on T1-only, T1+T2, T1+FLAIR, T2+FLAIR, and T1+T2+FLAIR were compared in the healthy subjects. Clinical VBM results based on the different segmentation approaches for MCD and for LHS were compared. T1-only segmentation overestimated total intracranial volume by about 80ml compared to the other segmentation methods. This was due to misclassification of dura mater and vessels as GM and CSF. Significant differences were found for several anatomical regions: the occipital lobe, the basal ganglia/thalamus, the pre- and postcentral gyrus, the cerebellum, and the brainstem. None of the segmentation methods yielded completely satisfying results for the basal ganglia/thalamus and the brainstem. The best correlation with age could be found for the multimodal T1+T2+FLAIR segmentation. Highest T-scores for identification of LHS were found for T1+T2 segmentation, while highest T-scores for MCD were dependent on lesion and anatomical location. Multimodal segmentation is superior to T1-only segmentation and reduces the misclassification of dura mater and vessels as GM and CSF. Depending on the anatomical region and the pathology of interest (atrophy, lesion detection, etc.), different combinations of T1, T2 and FLAIR yield optimal results. Copyright © 2017 Elsevier

  3. 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

  4. Text Segmentation Using Exponential Models

    CERN Document Server

    Beeferman, D; Lafferty, G D; Beeferman, Doug; Berger, Adam; Lafferty, John

    1997-01-01

    This paper introduces a new statistical approach to partitioning text automatically into coherent segments. Our approach enlists both short-range and long-range language models to help it sniff out likely sites of topic changes in text. To aid its search, the system consults a set of simple lexical hints it has learned to associate with the presence of boundaries through inspection of a large corpus of annotated data. We also propose a new probabilistically motivated error metric for use by the natural language processing and information retrieval communities, intended to supersede precision and recall for appraising segmentation algorithms. Qualitative assessment of our algorithm as well as evaluation using this new metric demonstrate the effectiveness of our approach in two very different domains, Wall Street Journal articles and the TDT Corpus, a collection of newswire articles and broadcast news transcripts.

  5. On the potential of a new IVUS elasticity modulus imaging approach for detecting vulnerable atherosclerotic coronary plaques: in vitro vessel phantom study.

    Science.gov (United States)

    Le Floc'h, Simon; Cloutier, Guy; Finet, Gérard; Tracqui, Philippe; Pettigrew, Roderic I; Ohayon, Jacques

    2010-10-07

    Peak cap stress amplitude is recognized as a good indicator of vulnerable plaque (VP) rupture. However, such stress evaluation strongly relies on a precise, but still lacking, knowledge of the mechanical properties exhibited by the plaque components. As a first response to this limitation, our group recently developed, in a previous theoretical study, an original approach, called iMOD (imaging modulography), which reconstructs elasticity maps (or modulograms) of atheroma plaques from the estimation of strain fields. In the present in vitro experimental study, conducted on polyvinyl alcohol cryogel arterial phantoms, we investigate the benefit of coupling the iMOD procedure with the acquisition of intravascular ultrasound (IVUS) measurements for detection of VP. Our results show that the combined iMOD-IVUS strategy: (1) successfully detected and quantified soft inclusion contours with high positive predictive and sensitivity values of 89.7 ± 3.9% and 81.5 ± 8.8%, respectively, (2) estimated reasonably cap thicknesses larger than ∼300 µm, but underestimated thinner caps, and (3) quantified satisfactorily Young's modulus of hard medium (mean value of 109.7 ± 23.7 kPa instead of 145.4 ± 31.8 kPa), but overestimated the stiffness of soft inclusions (mean Young`s moduli of 31.4 ± 9.7 kPa instead of 17.6 ± 3.4 kPa). All together, these results demonstrate a promising benefit of the new iMOD-IVUS clinical imaging method for in vivo VP detection.

  6. On the potential of a new IVUS elasticity modulus imaging approach for detecting vulnerable atherosclerotic coronary plaques: in vitro vessel phantom study

    Energy Technology Data Exchange (ETDEWEB)

    Floc' h, Simon Le; Tracqui, Philippe; Ohayon, Jacques [Laboratory TIMC-DynaCell, UJF, CNRS UMR 5525, In3S, Grenoble (France); Cloutier, Guy [Laboratory of Biorheology and Medical Ultrasonics, Research Center, University of Montreal Hospital (CRCHUM), Montreal, Quebec (Canada); Finet, Gerard [Department of Hemodynamics and Interventional Cardiology, Hospices Civils de Lyon and Claude Bernard University Lyon 1, INSERM Unit 886, Lyon (France); Pettigrew, Roderic I, E-mail: Guy.Cloutier@umontreal.c, E-mail: Jacques.Ohayon@imag.f [Laboratory of Integrative Cardiovascular Imaging Science, National Institute of Diabetes Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD (United States)

    2010-10-07

    Peak cap stress amplitude is recognized as a good indicator of vulnerable plaque (VP) rupture. However, such stress evaluation strongly relies on a precise, but still lacking, knowledge of the mechanical properties exhibited by the plaque components. As a first response to this limitation, our group recently developed, in a previous theoretical study, an original approach, called iMOD (imaging modulography), which reconstructs elasticity maps (or modulograms) of atheroma plaques from the estimation of strain fields. In the present in vitro experimental study, conducted on polyvinyl alcohol cryogel arterial phantoms, we investigate the benefit of coupling the iMOD procedure with the acquisition of intravascular ultrasound (IVUS) measurements for detection of VP. Our results show that the combined iMOD-IVUS strategy: (1) successfully detected and quantified soft inclusion contours with high positive predictive and sensitivity values of 89.7 {+-} 3.9% and 81.5 {+-} 8.8%, respectively, (2) estimated reasonably cap thicknesses larger than {approx}300 {mu}m, but underestimated thinner caps, and (3) quantified satisfactorily Young's modulus of hard medium (mean value of 109.7 {+-} 23.7 kPa instead of 145.4 {+-} 31.8 kPa), but overestimated the stiffness of soft inclusions (mean Young's moduli of 31.4 {+-} 9.7 kPa instead of 17.6 {+-} 3.4 kPa). All together, these results demonstrate a promising benefit of the new iMOD-IVUS clinical imaging method for in vivo VP detection.

  7. Integrated active contours for texture segmentation.

    Science.gov (United States)

    Sagiv, Chen; Sochen, Nir A; Zeevi, Yehoshua Y

    2006-06-01

    We address the issue of textured image segmentation in the context of the Gabor feature space of images. Gabor filters tuned to a set of orientations, scales and frequencies are applied to the images to create the Gabor feature space. A two-dimensional Riemannian manifold of local features is extracted via the Beltrami framework. The metric of this surface provides a good indicator of texture changes and is used, therefore, in a Beltrami-based diffusion mechanism and in a geodesic active contours algorithm for texture segmentation. The performance of the proposed algorithm is compared with that of the edgeless active contours algorithm applied for texture segmentation. Moreover, an integrated approach, extending the geodesic and edgeless active contours approaches to texture segmentation, is presented. We show that combining boundary and region information yields more robust and accurate texture segmentation results.

  8. Processing of MRI images weighted in TOF for blood vessels analysis: 3-D reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Hernandez D, J.; Cordova F, T. [Universidad de Guanajuato, Campus Leon, Departamento de Ingenieria Fisica, Loma del Bosque No. 103, Lomas del Campestre, 37150 Leon, Guanajuato (Mexico); Cruz A, I., E-mail: hernandezdj.gto@gmail.com [CONACYT, Centro de Investigacion en Matematicas, A. C., Jalisco s/n, Col. Valenciana, 36000 Guanajuato, Gto. (Mexico)

    2015-10-15

    This paper presents a novel presents an approach based on differences of intensities for the identification of vascular structures in medical images from MRI studies of type time of flight method (TOF). The plating method hypothesis gave high intensities belonging to the vascular system image type TOF can be segmented by thresholding of the histogram. The enhanced vascular structures is performed using the filter Vesselness, upon completion of a decision based on fuzzy thresholding minimizes error in the selection of vascular structures. It will give a brief introduction to the vascular system problems and how the images have helped diagnosis, is summarized the physical history of the different imaging modalities and the evolution of digital images with computers. Segmentation and 3-D reconstruction became image type time of flight; these images are typically used in medical diagnosis of cerebrovascular diseases. The proposed method has less error in segmentation and reconstruction of volumes related to the vascular system, clear images and less noise compared with edge detection methods. (Author)

  9. MUSCLE MRI SEGMENTATION USING RANDOM WALKER METHOD

    Directory of Open Access Journals (Sweden)

    A. V. Shukelovich

    2013-01-01

    Full Text Available A technique of marker set construction for muscle MRI segmentation using random walker approach is introduced. The possibility of clinician’s manual labor amount reduction and random walker algorithm optimization is studied.

  10. 3D/2D Registration with superabundant vessel reconstruction for cardiac resynchronization therapy.

    Science.gov (United States)

    Toth, Daniel; Panayiotou, Maria; Brost, Alexander; Behar, Jonathan M; Rinaldi, Christopher A; Rhode, Kawal S; Mountney, Peter

    2017-12-01

    A key component of image guided interventions is the registration of preoperative and intraoperative images. Classical registration approaches rely on cross-modality information; however, in modalities such as MRI and X-ray there may not be sufficient cross-modality information. This paper proposes a fundamentally different registration approach which uses adjacent anatomical structures with superabundant vessel reconstruction and dynamic outlier rejection. In the targeted clinical scenario of cardiac resynchronization therapy (CRT) delivery, preoperative, non contrast-enhanced, MRI is registered to intraoperative, contrasted X-ray fluoroscopy. The adjacent anatomical structures are the left ventricle (LV) from MRI and the coronary veins reconstructed from two contrast-enhanced X-ray images. The novel concept of superabundant vessel reconstruction is introduced to bypass the standard reconstruction problem of establishing one-to-one correspondences. Furthermore, a new dynamic outlier rejection method is proposed, to enable globally optimal point set registration. The proposed approach has been qualitatively and quantitatively evaluated on phantom, clinical CT angiography with ground truth and clinical CRT data. A novel evaluation method is proposed for clinical CRT data based on previously implanted artificial aortic and mitral valves. The registration accuracy in 3D was 2.94 mm for the aortic and 3.86 mm for the mitral valve. The results are below the required accuracy identified by clinical partners to be the half-segment size (16.35 mm) of a standard American Heart Association (AHA) 16 segment model of the LV. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Vessel Traffic Services.

    Science.gov (United States)

    1982-12-01

    Yorker" articles titled Silent Spring by Rachel Carson in 1963 produced a unifying effect, "the sort of rallying point of the movement to protect the...6232, 92d Cong., 1st. sess., 1971, p. 2. 15. Carson , Rachel L. , The Sea Around Us, New York: Oxford Univesity Press, 195-, p. IV. 16. U.S., Congress...Government Printing Office, 1974. 63. Buhler, L. and Geiger, J., Vessel Traffic Data Extraction MethodoloqX, Silver Spring , Maryland, O6erFae-tns

  12. Vanishing corneal vessels

    Science.gov (United States)

    Nicholson, Luke; Chana, Rupinder

    2013-01-01

    We wish to highlight the importance of acknowledging the accompanying effects of topical phenylephrine drops on the eye other than its intended mydriasis. We reported a case of a 92-year-old woman with a corneal graft who was noted to have superficial corneal vascularisation which was not documented previously. After the instillation of topical tropicamide 1% and phenylephrine 2.5%, for funduscopy, the corneal vascularisation was not visible. When reassessed on another visit, tropicamide had no effect on the vessels and only phenylephrine did. We wish to highlight that when reviewing patients in cornea clinics, instilling phenylephrine prior to being seen may mask important corneal vascularisation. PMID:24121816

  13. Level-Set Based Carotid Artery Segmentation for Stenosis Grading

    NARCIS (Netherlands)

    van Bemmel, C.M.; Spreeuwers, Lieuwe Jan; Viergever, M.A.; Niessen, W.J.

    2002-01-01

    A semi-automated method is presented for the determination of the degree of stenosis of the internal carotid artery (ICA) in 3D contrast-enhanced (CE) MR angiograms. Hereto, we determined the central vessel axis (CA), which subsequently is used as an initialization for a level-set based segmentation

  14. Flattening maps for the visualization of multibranched vessels.

    Science.gov (United States)

    Zhu, Lei; Haker, Steven; Tannenbaum, Allen

    2005-02-01

    In this paper, we present two novel algorithms which produce flattened visualizations of branched physiological surfaces, such as vessels. The first approach is a conformal mapping algorithm based on the minimization of two Dirichlet functionals. From a triangulated representation of vessel surfaces, we show how the algorithm can be implemented using a finite element technique. The second method is an algorithm which adjusts the conformal mapping to produce a flattened representation of the original surface while preserving areas. This approach employs the theory of optimal mass transport. Furthermore, a new way of extracting center lines for vessel fly-throughs is provided.

  15. Dynamic Endothelial Cell Rearrangements Drive Developmental Vessel Regression

    Science.gov (United States)

    Franco, Claudio A.; Jones, Martin L.; Bernabeu, Miguel O.; Geudens, Ilse; Mathivet, Thomas; Rosa, Andre; Lopes, Felicia M.; Lima, Aida P.; Ragab, Anan; Collins, Russell T.; Phng, Li-Kun; Coveney, Peter V.; Gerhardt, Holger

    2015-01-01

    Patterning of functional blood vessel networks is achieved by pruning of superfluous connections. The cellular and molecular principles of vessel regression are poorly understood. Here we show that regression is mediated by dynamic and polarized migration of endothelial cells, representing anastomosis in reverse. Establishing and analyzing the first axial polarity map of all endothelial cells in a remodeling vascular network, we propose that balanced movement of cells maintains the primitive plexus under low shear conditions in a metastable dynamic state. We predict that flow-induced polarized migration of endothelial cells breaks symmetry and leads to stabilization of high flow/shear segments and regression of adjacent low flow/shear segments. PMID:25884288

  16. 46 CFR 289.2 - Vessels included.

    Science.gov (United States)

    2010-10-01

    ... CONSTRUCTION-DIFFERENTIAL SUBSIDY VESSELS, OPERATING-DIFFERENTIAL SUBSIDY VESSELS AND OF VESSELS SOLD OR ADJUSTED UNDER THE MERCHANT SHIP SALES ACT 1946 § 289.2 Vessels included. Vessels subject to the provisions of this part are: (a) All vessels which may in the future be constructed or sold with construction...

  17. Semi-automated segment generation for geographic novelty ...

    African Journals Online (AJOL)

    Charles

    correspondence metric (PCM), is evaluated in this approach as a fitness function for segmentation algorithm ... The results show the potential of using edge metrics, as opposed to area metrics, for evaluating segments in an ... traverses the parameter space of the segmentation algorithm, searching for results most closely.

  18. [Vascular access for haemodyalisis. Comparative analysis of the mechanical behaviour of native vessels and prosthesis].

    Science.gov (United States)

    Bia, D; Zócalo, Y; Armentano, R; Pérez, H; Cabrera, E; Saldías, M; Galli, C; Alvarez, I

    2006-01-01

    The prosthesis nowadays used in the vascular access for haemodialysis have low patency rates, mainly due to the luminal obstruction, determined by the intimal hyperplasia. Several factors have been related to de development of intimal hyperplasia and graft failure. Among them are the differences in the biomechanical properties between the prosthesis and the native vessels. In the searching for vascular prosthesis that overcomes the limitations of the currently used, the cryopreserved vessels (cryografts) appear as an alternative of growing interest. However, it is unknown if the mechanical differences or mismatch between prosthesis and native vessels are lesser when using cryografts. To characterize and compare the biomechanical behaviour of native vessels used in vascular access and cryografts. Additionally, segments of expanded polytetrafluoroethylene (ePTFE) were also evaluated, so as to evaluate the potential biomechanical advantages of the cryografts respect to synthetic prosthesis used in vascular access. Segments from human humeral (n = 12), carotid (n = 12) and femoral (n = 12) arteries, and saphenous vein (n = 12), were obtained from 6 multiorgan donors. The humeral arteries were studied in fresh state. The other segments were divided into two groups, and 6 segments from each vessel were studied in fresh state, while the remaining 6 segments were evaluated after 30 days of criopreservation. For the mechanical evaluation the vascular segments and 6 segments of ePTFE were mounted in a circulation mock and submitted to haemodynamic conditions similar to those of the in vivo. Instantaneous pressure (Konigsberg) and diameter (Sonomicrometry) were measured and used to calculate the viscous and elastic indexes, the compliance, distensibility and characteristic impedance. For each mechanical parameter studied, the mismatch between the prosthesis and the native vessel was evaluated. The ePTFE was the prosthesis with the higher mechanical mismatch (p vascular

  19. Blood flow reprograms lymphatic vessels to blood vessels.

    Science.gov (United States)

    Chen, Chiu-Yu; Bertozzi, Cara; Zou, Zhiying; Yuan, Lijun; Lee, John S; Lu, MinMin; Stachelek, Stan J; Srinivasan, Sathish; Guo, Lili; Vicente, Andres; Vincente, Andres; Mericko, Patricia; Levy, Robert J; Makinen, Taija; Oliver, Guillermo; Kahn, Mark L

    2012-06-01

    Human vascular malformations cause disease as a result of changes in blood flow and vascular hemodynamic forces. Although the genetic mutations that underlie the formation of many human vascular malformations are known, the extent to which abnormal blood flow can subsequently influence the vascular genetic program and natural history is not. Loss of the SH2 domain-containing leukocyte protein of 76 kDa (SLP76) resulted in a vascular malformation that directed blood flow through mesenteric lymphatic vessels after birth in mice. Mesenteric vessels in the position of the congenital lymphatic in mature Slp76-null mice lacked lymphatic identity and expressed a marker of blood vessel identity. Genetic lineage tracing demonstrated that this change in vessel identity was the result of lymphatic endothelial cell reprogramming rather than replacement by blood endothelial cells. Exposure of lymphatic vessels to blood in the absence of significant flow did not alter vessel identity in vivo, but lymphatic endothelial cells exposed to similar levels of shear stress ex vivo rapidly lost expression of PROX1, a lymphatic fate-specifying transcription factor. These findings reveal that blood flow can convert lymphatic vessels to blood vessels, demonstrating that hemodynamic forces may reprogram endothelial and vessel identity in cardiovascular diseases associated with abnormal flow.

  20. Adaptation of mesenteric lymphatic vessels to prolonged changes in transmural pressure.

    Science.gov (United States)

    Dongaonkar, R M; Nguyen, T L; Quick, C M; Hardy, J; Laine, G A; Wilson, E; Stewart, R H

    2013-07-15

    In vitro studies have revealed that acute increases in transmural pressure increase lymphatic vessel contractile function. However, adaptive responses to prolonged changes in transmural pressure in vivo have not been reported. Therefore, we developed a novel bovine mesenteric lymphatic partial constriction model to test the hypothesis that lymphatic vessels exposed to higher transmural pressures adapt functionally to become stronger pumps than vessels exposed to lower transmural pressures. Postnodal mesenteric lymphatic vessels were partially constricted for 3 days. On postoperative day 3, constricted vessels were isolated, and divided into upstream (UP) and downstream (DN) segment groups, and instrumented in an isolated bath. Although there were no differences between the passive diameters of the two groups, both diastolic diameter and systolic diameter were significantly larger in the UP group than in the DN group. The pump index of the UP group was also higher than that in the DN group. In conclusion, this is the first work to report how lymphatic vessels adapt to prolonged changes in transmural pressure in vivo. Our results suggest that vessel segments upstream of the constriction adapt to become both better fluid conduits and lymphatic pumps than downstream segments.

  1. Semi-automatic 3D segmentation of costal cartilage in CT data from Pectus Excavatum patients

    Science.gov (United States)

    Barbosa, Daniel; Queirós, Sandro; Rodrigues, Nuno; Correia-Pinto, Jorge; Vilaça, J.

    2015-03-01

    One of the current frontiers in the clinical management of Pectus Excavatum (PE) patients is the prediction of the surgical outcome prior to the intervention. This can be done through computerized simulation of the Nuss procedure, which requires an anatomically correct representation of the costal cartilage. To this end, we take advantage of the costal cartilage tubular structure to detect it through multi-scale vesselness filtering. This information is then used in an interactive 2D initialization procedure which uses anatomical maximum intensity projections of 3D vesselness feature images to efficiently initialize the 3D segmentation process. We identify the cartilage tissue centerlines in these projected 2D images using a livewire approach. We finally refine the 3D cartilage surface through region-based sparse field level-sets. We have tested the proposed algorithm in 6 noncontrast CT datasets from PE patients. A good segmentation performance was found against reference manual contouring, with an average Dice coefficient of 0.75±0.04 and an average mean surface distance of 1.69+/-0.30mm. The proposed method requires roughly 1 minute for the interactive initialization step, which can positively contribute to an extended use of this tool in clinical practice, since current manual delineation of the costal cartilage can take up to an hour.

  2. Adaptive Kalman snake for semi-autonomous 3D vessel tracking.

    Science.gov (United States)

    Lee, Sang-Hoon; Lee, Sanghoon

    2015-10-01

    In this paper, we propose a robust semi-autonomous algorithm for 3D vessel segmentation and tracking based on an active contour model and a Kalman filter. For each computed tomography angiography (CTA) slice, we use the active contour model to segment the vessel boundary and the Kalman filter to track position and shape variations of the vessel boundary between slices. For successful segmentation via active contour, we select an adequate number of initial points from the contour of the first slice. The points are set manually by user input for the first slice. For the remaining slices, the initial contour position is estimated autonomously based on segmentation results of the previous slice. To obtain refined segmentation results, an adaptive control spacing algorithm is introduced into the active contour model. Moreover, a block search-based initial contour estimation procedure is proposed to ensure that the initial contour of each slice can be near the vessel boundary. Experiments were performed on synthetic and real chest CTA images. Compared with the well-known Chan-Vese (CV) model, the proposed algorithm exhibited better performance in segmentation and tracking. In particular, receiver operating characteristic analysis on the synthetic and real CTA images demonstrated the time efficiency and tracking robustness of the proposed model. In terms of computational time redundancy, processing time can be effectively reduced by approximately 20%. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  3. Interactive vs. automatic ultrasound image segmentation methods for staging hepatic lipidosis.

    NARCIS (Netherlands)

    Weijers, G.; Starke, A.; Haudum, A.; Thijssen, J.M.; Rehage, J.; Korte, C.L. de

    2010-01-01

    The aim of this study was to test the hypothesis that automatic segmentation of vessels in ultrasound (US) images can produce similar or better results in grading fatty livers than interactive segmentation. A study was performed in postpartum dairy cows (N=151), as an animal model of human fatty

  4. Unsupervised information extraction by text segmentation

    CERN Document Server

    Cortez, Eli

    2013-01-01

    A new unsupervised approach to the problem of Information Extraction by Text Segmentation (IETS) is proposed, implemented and evaluated herein. The authors' approach relies on information available on pre-existing data to learn how to associate segments in the input string with attributes of a given domain relying on a very effective set of content-based features. The effectiveness of the content-based features is also exploited to directly learn from test data structure-based features, with no previous human-driven training, a feature unique to the presented approach. Based on the approach, a

  5. Fast and Automatic Detection and Segmentation of Unknown Objects

    OpenAIRE

    Kootstra, Gert; Bergström, Niklas; Kragic, Danica

    2010-01-01

    This paper focuses on the fast and automatic detection and segmentation of unknown objects in unknown environments. Many existing object detection and segmentation methods assume prior knowledge about the object or human interference. However, an autonomous system operating in the real world will often be confronted with previously unseen objects. To solve this problem, we propose a segmentation approach named Automatic Detection And Segmentation (ADAS). For the detection of objects, we use s...

  6. The vessel fluence; Fluence cuve

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2001-07-01

    This book presents the proceedings of the technical meeting on the reactors vessels fluence. They are grouped in eight sessions: the industrial context and the stakes of the vessels control; the organization and the methodology for the fluence computation; the concerned physical properties; the reference computation methods; the fluence monitoring in an industrial context; vessels monitoring under irradiation; others methods in the world; the research and development programs. (A.L.B.)

  7. A Hybrid Technique for Medical Image Segmentation

    Directory of Open Access Journals (Sweden)

    Alamgir Nyma

    2012-01-01

    Full Text Available Medical image segmentation is an essential and challenging aspect in computer-aided diagnosis and also in pattern recognition research. This paper proposes a hybrid method for magnetic resonance (MR image segmentation. We first remove impulsive noise inherent in MR images by utilizing a vector median filter. Subsequently, Otsu thresholding is used as an initial coarse segmentation method that finds the homogeneous regions of the input image. Finally, an enhanced suppressed fuzzy c-means is used to partition brain MR images into multiple segments, which employs an optimal suppression factor for the perfect clustering in the given data set. To evaluate the robustness of the proposed approach in noisy environment, we add different types of noise and different amount of noise to T1-weighted brain MR images. Experimental results show that the proposed algorithm outperforms other FCM based algorithms in terms of segmentation accuracy for both noise-free and noise-inserted MR images.

  8. 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

  9. A new approach to measuring tortuosity

    Science.gov (United States)

    Wert, Amanda; Scott, Sherry E.

    2012-03-01

    The detection and measurement of the tortuosity - i.e. the bending and winding - of vessels has been shown to be potentially useful in the assessment of cancer progression and treatment response. Although several metrics for tortuosity are used, no single one measure is able to capture all types of tortuosity. This report presents a new multiscale technique for measuring vessel tortuosity. The approach is based on a method - called the ergodicity defect - which gives a scale-dependent measure of deviation from ergodicity. Ergodicity is a concept that captures the manner in which trajectories or signals sample the space; thus, ergodicity and vessel tortuosity both involve the notion of how a signal samples space. Here we begin to explore this connection. We first apply the ergodicity defect tortuosity measure to both 2D and 3D synthetic data in order to demonstrate the response of the method to three types of tortuosity observed in clinical patterns. We then implement the technique on segmented vessels extracted from brain tumor MRA images. Results indicate that the method can be effectively used to detect and measure several types of vessel tortuosity.

  10. [Large vessel vasculitides].

    Science.gov (United States)

    Morović-Vergles, Jadranka; Puksić, Silva; Gracanin, Ana Gudelj

    2013-01-01

    Large vessel vasculitis includes Giant cell arteritis and Takayasu arteritis. Giant cell arteritis is the most common form of vasculitis affect patients aged 50 years or over. The diagnosis should be considered in older patients who present with new onset of headache, visual disturbance, polymyalgia rheumatica and/or fever unknown cause. Glucocorticoides remain the cornerstone of therapy. Takayasu arteritis is a chronic panarteritis of the aorta ant its major branches presenting commonly in young ages. Although all large arteries can be affected, the aorta, subclavian and carotid arteries are most commonly involved. The most common symptoms included upper extremity claudication, hypertension, pain over the carotid arteries (carotidynia), dizziness and visual disturbances. Early diagnosis and treatment has improved the outcome in patients with TA.

  11. Americium behaviour in plastic vessels

    Energy Technology Data Exchange (ETDEWEB)

    Legarda, F.; Herranz, M. [Departamento de Ingenieria Nuclear y Mecanica de Fluidos, Escuela Tecnica Superior de Ingenieria de Bilbao, Universidad del Pais Vasco (UPV/EHU), Alameda de Urquijo s/n, 48013 Bilbao (Spain); Idoeta, R., E-mail: raquel.idoeta@ehu.e [Departamento de Ingenieria Nuclear y Mecanica de Fluidos, Escuela Tecnica Superior de Ingenieria de Bilbao, Universidad del Pais Vasco (UPV/EHU), Alameda de Urquijo s/n, 48013 Bilbao (Spain); Abelairas, A. [Departamento de Ingenieria Nuclear y Mecanica de Fluidos, Escuela Tecnica Superior de Ingenieria de Bilbao, Universidad del Pais Vasco (UPV/EHU), Alameda de Urquijo s/n, 48013 Bilbao (Spain)

    2010-07-15

    The adsorption of {sup 241}Am dissolved in water in different plastic storage vessels was determined. Three different plastics were investigated with natural and distilled waters and the retention of {sup 241}Am by these plastics was studied. The same was done by varying vessel agitation time, vessel agitation speed, surface/volume ratio of water in the vessels and water pH. Adsorptions were measured to be between 0% and 70%. The adsorption of {sup 241}Am is minimized with no water agitation, with PET or PVC plastics, and by water acidification.

  12. A Perspective On Segment Reporting Choices And Segment Reconciliations

    OpenAIRE

    Dana Hollie; Shaokun£¨Carol) Yu

    2015-01-01

    In 2014, segment reporting gained third place in SEC comment letters. This article reviews the history of segment reporting including segment reporting choices and segment reconciliations, the current concerns as the level of detail in segment disclosures varies widely across organizations, the value relevance of segment reconciliations and its market consequences, and the importance of segment reporting to management. The following are highlights of the manuscript: The third-most-common area...

  13. Novel approach to evaluation of medical care quality delivered to patients with ST-segment elevation acute coronary syndrome: course to clinical result

    Directory of Open Access Journals (Sweden)

    Posnenkova О.М.

    2014-09-01

    Full Text Available The purpose was to implement system analysis of clinical cases for development of healthcare quality indicators for STe-ACS patients, aimed at achievement of clinical result — decrease of in-hospital mortality. Mathehal and Methods. National recommendations on diagnostic and treatment of patients with myocardial infarction with ST-segment elevation on ECG (2007 were used to determine clinical result of treatment and key measures of medical care. To reveal major causes of clinical result non-achievement fishbone diagram was used. Results. Early reperfusion and optimal medical therapy were determined as the key measures of medical care delivered to patients with STe-ACS. The following indicators were developed to control these measures: «Primary reperfusion», «Thrombolysis in 30 minutes», «Primary percutaneous coronary intervention in 90 minutes», «Dual antiplatelet therapy in hospital», «Beta-blockers administration», «ACE-is/ARBs administration». The major causes of in-hospital mortality were separated. Indicators for assessment the major causes of clinical result non-achievement were proposed. Principal stages of performance measures creation were posed. Conclusion. Recommendation-based and clear definition of clinical result of treatment and key measures of the result achievement combined with methods of systems analysis allows development of evidence-based measures for assessment the quality of care delivered to patients with STe-ACS.

  14. Speech segmentation in aphasia.

    Science.gov (United States)

    Peñaloza, Claudia; Benetello, Annalisa; Tuomiranta, Leena; Heikius, Ida-Maria; Järvinen, Sonja; Majos, Maria Carmen; Cardona, Pedro; Juncadella, Montserrat; Laine, Matti; Martin, Nadine; Rodríguez-Fornells, Antoni

    2015-01-01

    Speech segmentation is one of the initial and mandatory phases of language learning. Although some people with aphasia have shown a preserved ability to learn novel words, their speech segmentation abilities have not been explored. We examined the ability of individuals with chronic aphasia to segment words from running speech via statistical learning. We also explored the relationships between speech segmentation and aphasia severity, and short-term memory capacity. We further examined the role of lesion location in speech segmentation and short-term memory performance. The experimental task was first validated with a group of young adults (n = 120). Participants with chronic aphasia (n = 14) were exposed to an artificial language and were evaluated in their ability to segment words using a speech segmentation test. Their performance was contrasted against chance level and compared to that of a group of elderly matched controls (n = 14) using group and case-by-case analyses. As a group, participants with aphasia were significantly above chance level in their ability to segment words from the novel language and did not significantly differ from the group of elderly controls. Speech segmentation ability in the aphasic participants was not associated with aphasia severity although it significantly correlated with word pointing span, a measure of verbal short-term memory. Case-by-case analyses identified four individuals with aphasia who performed above chance level on the speech segmentation task, all with predominantly posterior lesions and mild fluent aphasia. Their short-term memory capacity was also better preserved than in the rest of the group. Our findings indicate that speech segmentation via statistical learning can remain functional in people with chronic aphasia and suggest that this initial language learning mechanism is associated with the functionality of the verbal short-term memory system and the integrity of the left inferior frontal region.

  15. Deep learning for anomaly detection in maritime vessels using AIS-cued camera imagery

    Science.gov (United States)

    Zang, Yi; Mukherjee, Abir; Fei, Chuhong; Liu, Ting; Lampropoulos, George

    2017-05-01

    The presented work is an extension of previous work carried out at A.U.G. Signals Ltd. The problem is approached herein for vessel identification/verification using Deep Learning Neural Networks in a persistent surveillance scenario. Using images with vessels in the scene, Deep Learning Neural Networks were set up to detect vessels from still imagery (visible wavelength). Different neural network designs were implemented for vessel detection and compared based on learning performance (speed and demanded training sets) and estimation accuracy. Unique features from these designs were taken to create an optimized solution. This paper presents a comparison of the deep learning approaches implemented and their relative capabilities in vessel verification.

  16. Classifier Directed Data Hybridization for Geographic Sample Supervised Segment Generation

    Directory of Open Access Journals (Sweden)

    Christoff Fourie

    2014-11-01

    Full Text Available Quality segment generation is a well-known challenge and research objective within Geographic Object-based Image Analysis (GEOBIA. Although methodological avenues within GEOBIA are diverse, segmentation commonly plays a central role in most approaches, influencing and being influenced by surrounding processes. A general approach using supervised quality measures, specifically user provided reference segments, suggest casting the parameters of a given segmentation algorithm as a multidimensional search problem. In such a sample supervised segment generation approach, spatial metrics observing the user provided reference segments may drive the search process. The search is commonly performed by metaheuristics. A novel sample supervised segment generation approach is presented in this work, where the spectral content of provided reference segments is queried. A one-class classification process using spectral information from inside the provided reference segments is used to generate a probability image, which in turn is employed to direct a hybridization of the original input imagery. Segmentation is performed on such a hybrid image. These processes are adjustable, interdependent and form a part of the search problem. Results are presented detailing the performances of four method variants compared to the generic sample supervised segment generation approach, under various conditions in terms of resultant segment quality, required computing time and search process characteristics. Multiple metrics, metaheuristics and segmentation algorithms are tested with this approach. Using the spectral data contained within user provided reference segments to tailor the output generally improves the results in the investigated problem contexts, but at the expense of additional required computing time.

  17. FISICO: Fast Image SegmentatIon COrrection.

    Directory of Open Access Journals (Sweden)

    Waldo Valenzuela

    Full Text Available In clinical diagnosis, medical image segmentation plays a key role in the analysis of pathological regions. Despite advances in automatic and semi-automatic segmentation techniques, time-effective correction tools are commonly needed to improve segmentation results. Therefore, these tools must provide faster corrections with a lower number of interactions, and a user-independent solution to reduce the time frame between image acquisition and diagnosis.We present a new interactive method for correcting image segmentations. Our method provides 3D shape corrections through 2D interactions. This approach enables an intuitive and natural corrections of 3D segmentation results. The developed method has been implemented into a software tool and has been evaluated for the task of lumbar muscle and knee joint segmentations from MR images.Experimental results show that full segmentation corrections could be performed within an average correction time of 5.5±3.3 minutes and an average of 56.5±33.1 user interactions, while maintaining the quality of the final segmentation result within an average Dice coefficient of 0.92±0.02 for both anatomies. In addition, for users with different levels of expertise, our method yields a correction time and number of interaction decrease from 38±19.2 minutes to 6.4±4.3 minutes, and 339±157.1 to 67.7±39.6 interactions, respectively.

  18. Breast ultrasound image segmentation: a survey.

    Science.gov (United States)

    Huang, Qinghua; Luo, Yaozhong; Zhang, Qiangzhi

    2017-03-01

    Breast cancer is the most common form of cancer among women worldwide. Ultrasound imaging is one of the most frequently used diagnostic tools to detect and classify abnormalities of the breast. Recently, computer-aided diagnosis (CAD) systems using ultrasound images have been developed to help radiologists to increase diagnosis accuracy. However, accurate ultrasound image segmentation remains a challenging problem due to various ultrasound artifacts. In this paper, we investigate approaches developed for breast ultrasound (BUS) image segmentation. In this paper, we reviewed the literature on the segmentation of BUS images according to the techniques adopted, especially over the past 10 years. By dividing into seven classes (i.e., thresholding-based, clustering-based, watershed-based, graph-based, active contour model, Markov random field and neural network), we have introduced corresponding techniques and representative papers accordingly. We have summarized and compared many techniques on BUS image segmentation and found that all these techniques have their own pros and cons. However, BUS image segmentation is still an open and challenging problem due to various ultrasound artifacts introduced in the process of imaging, including high speckle noise, low contrast, blurry boundaries, low signal-to-noise ratio and intensity inhomogeneity CONCLUSIONS: To the best of our knowledge, this is the first comprehensive review of the approaches developed for segmentation of BUS images. With most techniques involved, this paper will be useful and helpful for researchers working on segmentation of ultrasound images, and for BUS CAD system developers.

  19. Segmented conjugated polymers

    Indian Academy of Sciences (India)

    Abstract. Segmented conjugated polymers, wherein the conjugation is randomly truncated by varying lengths of non-conjugated segments, form an interesting class of polymers as they not only represent systems of varying stiffness, but also ones where the backbone can be construed as being made up of chromophores of ...

  20. Segmentation, advertising and prices

    NARCIS (Netherlands)

    Galeotti, Andrea; Moraga-González, José Luis

    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

  1. Segmented conjugated polymers

    Indian Academy of Sciences (India)

    Segmented conjugated polymers, wherein the conjugation is randomly truncated by varying lengths of non-conjugated segments, form an interesting class of polymers as they not only represent systems of varying stiffness, but also ones where the backbone can be construed as being made up of chromophores of varying ...

  2. Mixed raster content segmentation, compression, transmission

    CERN Document Server

    Pavlidis, George

    2017-01-01

    This book presents the main concepts in handling digital images of mixed content, traditionally referenced as mixed raster content (MRC), in two main parts. The first includes introductory chapters covering the scientific and technical background aspects, whereas the second presents a set of research and development approaches to tackle key issues in MRC segmentation, compression and transmission. The book starts with a review of color theory and the mechanism of color vision in humans. In turn, the second chapter reviews data coding and compression methods so as to set the background and demonstrate the complexity involved in dealing with MRC. Chapter three addresses the segmentation of images through an extensive literature review, which highlights the various approaches used to tackle MRC segmentation. The second part of the book focuses on the segmentation of color images for optimized compression, including multi-layered decomposition and representation of MRC and the processes that can be employed to op...

  3. An efficient algorithm for color image segmentation

    Directory of Open Access Journals (Sweden)

    Shikha Yadav

    2016-09-01

    Full Text Available In field of image processing, image segmentation plays an important role that focus on splitting the whole image into segments. Representation of an image so that it can be more easily analysed and involves more information is an important segmentation goal. The process of partitioning an image can be usually realized by Region based, Boundary based or edge based method. In this work a hybrid approach is followed that combines improved bee colony optimization and Tabu search for color image segmentation. The results produced from this hybrid approach are compared with non-sorted particle swarm optimization, non-sorted genetic algorithm and improved bee colony optimization. Results show that the Hybrid algorithm has better or somewhat similar performance as compared to other algorithms that are based on population. The algorithm is successfully implemented on MATLAB.

  4. Building Roof Segmentation from Aerial Images Using a Lineand Region-Based Watershed Segmentation Technique

    Directory of Open Access Journals (Sweden)

    Youssef El Merabet

    2015-02-01

    Full Text Available In this paper, we present a novel strategy for roof segmentation from aerial images (orthophotoplans based on the cooperation of edge- and region-based segmentation methods. The proposed strategy is composed of three major steps. The first one, called the pre-processing step, consists of simplifying the acquired image with an appropriate couple of invariant and gradient, optimized for the application, in order to limit illumination changes (shadows, brightness, etc. affecting the images. The second step is composed of two main parallel treatments: on the one hand, the simplified image is segmented by watershed regions. Even if the first segmentation of this step provides good results in general, the image is often over-segmented. To alleviate this problem, an efficient region merging strategy adapted to the orthophotoplan particularities, with a 2D modeling of roof ridges technique, is applied. On the other hand, the simplified image is segmented by watershed lines. The third step consists of integrating both watershed segmentation strategies into a single cooperative segmentation scheme in order to achieve satisfactory segmentation results. Tests have been performed on orthophotoplans containing 100 roofs with varying complexity, and the results are evaluated with the VINETcriterion using ground-truth image segmentation. A comparison with five popular segmentation techniques of the literature demonstrates the effectiveness and the reliability of the proposed approach. Indeed, we obtain a good segmentation rate of 96% with the proposed method compared to 87.5% with statistical region merging (SRM, 84% with mean shift, 82% with color structure code (CSC, 80% with efficient graph-based segmentation algorithm (EGBIS and 71% with JSEG.

  5. Building roof segmentation from aerial images using a lineand region-based watershed segmentation technique.

    Science.gov (United States)

    El Merabet, Youssef; Meurie, Cyril; Ruichek, Yassine; Sbihi, Abderrahmane; Touahni, Raja

    2015-02-02

    In this paper, we present a novel strategy for roof segmentation from aerial images (orthophotoplans) based on the cooperation of edge- and region-based segmentation methods. The proposed strategy is composed of three major steps. The first one, called the pre-processing step, consists of simplifying the acquired image with an appropriate couple of invariant and gradient, optimized for the application, in order to limit illumination changes (shadows, brightness, etc.) affecting the images. The second step is composed of two main parallel treatments: on the one hand, the simplified image is segmented by watershed regions. Even if the first segmentation of this step provides good results in general, the image is often over-segmented. To alleviate this problem, an efficient region merging strategy adapted to the orthophotoplan particularities, with a 2D modeling of roof ridges technique, is applied. On the other hand, the simplified image is segmented by watershed lines. The third step consists of integrating both watershed segmentation strategies into a single cooperative segmentation scheme in order to achieve satisfactory segmentation results. Tests have been performed on orthophotoplans containing 100 roofs with varying complexity, and the results are evaluated with the VINETcriterion using ground-truth image segmentation. A comparison with five popular segmentation techniques of the literature demonstrates the effectiveness and the reliability of the proposed approach. Indeed, we obtain a good segmentation rate of 96% with the proposed method compared to 87.5% with statistical region merging (SRM), 84% with mean shift, 82% with color structure code (CSC), 80% with efficient graph-based segmentation algorithm (EGBIS) and 71% with JSEG.

  6. Unsupervised Segmentation Methods of TV Contents

    Directory of Open Access Journals (Sweden)

    Elie El-Khoury

    2010-01-01

    Full Text Available We present a generic algorithm to address various temporal segmentation topics of audiovisual contents such as speaker diarization, shot, or program segmentation. Based on a GLR approach, involving the ΔBIC criterion, this algorithm requires the value of only a few parameters to produce segmentation results at a desired scale and on most typical low-level features used in the field of content-based indexing. Results obtained on various corpora are of the same quality level than the ones obtained by other dedicated and state-of-the-art methods.

  7. Combined Surgical Approach of Pars Plana Vitrectomy, Phacoemulsification, and Intraocular Lens Implantation for the Management of Cataract and Posterior Segment Pathologies

    Directory of Open Access Journals (Sweden)

    Cem Özgönül

    2014-03-01

    Full Text Available Objectives: To evaluate the indications, intra- and post-operative complications, and visual results of combined cataract surgery and pars plana vitrectomy. Materials and Methods: Medical records of patients who underwent combined surgery between January 2008 and January 2011 were retrospectively evaluated. Indications for surgery, complications, pre-operative and post-operative visual acuities were recorded. Results: Sixty-four eyes of 64 patients were included in the study. Thirty-five (55% of the patients were men and 29 (45% were women; mean age was 53±21 (6-88 years. Mean follow-up time was 13±12 (1-51 months. The main indications for combined surgery were intravitreal hemorrhage in 19 patients (29.7%, epiretinal membrane in 12 (18.8%, intraocular foreign body in 11 (17.2%, retinal detachment in 9 (14.1%, and macular edema in 7 (11% patients. Posterior capsule rupture in 3 cases and corneal edema in 2 cases were the complications encountered during surgery. Postoperatively, hypotonia occurred in 5 cases and corneal edema in 1. Intraocular pressure elevation was observed in 1 silicon-injected case and 1 propane gas-injected case. The average preoperative visual acuity was 1.90±1.9 (0.22 to 3.10 LogMAR. The average postoperative visual acuity at the last visit was 1.1±1.0 (0.00 to 4.00 LogMAR. The visual acuity increase was statistically significant (p<0.001. Conclusion: Combined surgery is a feasible option for patients with vitreoretinal diseases and cataract. Visual results and complications depend primarily on the underlying posterior segment pathology. (Turk J Ophthalmol 2014; 44: 98-101

  8. Multi-segmental neurofibromatosis

    Directory of Open Access Journals (Sweden)

    Kumar Sudhir

    2004-01-01

    Full Text Available Neurofibromatosis (NF, one of the commonest phakomatoses, is characterized by varied clinical manifestations. Segmental NF is one of the uncommon subtypes of NF. We report a young adult presenting with asymptomatic skin lesions- neurofibromas and café-au-lait macules- over localized areas of the lower back, affecting more than one segment. None of the family members were found to have features of segmental NF. Segmental NF may be misdiagnosed as a birthmark or remain undiagnosed for long periods of time, as the patients are often asymptomatic. Moreover, the clinical features are highly variable and range from a small area of skin involvement to involvement over the entire half of the body. This variation is explained by the fact that segmental NF is thought to arise from a postzygotic NF1 gene mutation, leading to somatic mosaicism. We have also reviewed the relevant literature on this subject.

  9. Multi-segmental neurofibromatosis

    Directory of Open Access Journals (Sweden)

    Kumar Sudhir

    2004-11-01

    Full Text Available Neurofibromatosis (NF, one of the commonest phakomatoses, is characterized by varied clinical manifestations. Segmental NF is one of the uncommon subtypes of NF. We report a young adult presenting with asymptomatic skin lesions- neurofibromas and café-au-lait macules- over localized areas of the lower back, affecting more than one segment. None of the family members were found to have features of segmental NF. Segmental NF may be misdiagnosed as a birthmark or remain undiagnosed for long periods of time, as the patients are often asymptomatic. Moreover, the clinical features are highly variable and range from a small area of skin involvement to involvement over the entire half of the body. This variation is explained by the fact that segmental NF is thought to arise from a postzygotic NF1 gene mutation, leading to somatic mosaicism. We have also reviewed the relevant literature on this subject.

  10. Fast blood-flow simulation for large arterial trees containing thousands of vessels.

    Science.gov (United States)

    Muller, Alexandre; Clarke, Richard; Ho, Harvey

    2017-02-01

    Blood flow modelling has previously been successfully carried out in arterial trees to study pulse wave propagation using nonlinear or linear flow solvers. However, the number of vessels used in the simulations seldom grows over a few hundred. The aim of this work is to present a computationally efficient solver coupled with highly detailed arterial trees containing thousands of vessels. The core of the solver is based on a modified transmission line method, which exploits the analogy between electrical current in finite-length conductors and blood flow in vessels. The viscoelastic behaviour of the arterial-wall is taken into account using a complex elastic modulus. The flow is solved vessel by vessel in the frequency domain and the calculated output pressure is then used as an input boundary condition for daughter vessels. The computational results yield pulsatile blood pressure and flow rate for every segment in the tree. This solver is coupled with large arterial trees generated from a three-dimensional constrained constructive optimisation algorithm. The tree contains thousands of blood vessels with radii spanning ~1 mm in the root artery to ~30 μm in leaf vessels. The computation takes seconds to complete for a vasculature of 2048 vessels and less than 2 min for a vasculature of 4096 vessels on a desktop computer.

  11. Vessel network detection using contour evolution and color components

    Energy Technology Data Exchange (ETDEWEB)

    Ushizima, Daniela; Medeiros, Fatima; Cuadros, Jorge; Martins, Charles

    2011-06-22

    Automated retinal screening relies on vasculature segmentation before the identification of other anatomical structures of the retina. Vasculature extraction can also be input to image quality ranking, neovascularization detection and image registration, among other applications. There is an extensive literature related to this problem, often excluding the inherent heterogeneity of ophthalmic clinical images. The contribution of this paper relies on an algorithm using front propagation to segment the vessel network. The algorithm includes a penalty in the wait queue on the fast marching heap to minimize leakage of the evolving interface. The method requires no manual labeling, a minimum number of parameters and it is capable of segmenting color ocular fundus images in real scenarios, where multi-ethnicity and brightness variations are parts of the problem.

  12. Mounting and Alignment of IXO Mirror Segments

    Science.gov (United States)

    Chan, Kai-Wing; Zhang, William; Evans, Tyler; McClelland, Ryan; Hong, Melinda; Mazzarella, James; Saha, Timo; Jalota, Lalit; Olsen, Lawrence; Byron, Glenn

    2010-01-01

    A suspension-mounting scheme is developed for the IXO (International X-ray Observatory) mirror segments in which the figure of the mirror segment is preserved in each stage of mounting. The mirror, first fixed on a thermally compatible strongback, is subsequently transported, aligned and transferred onto its mirror housing. In this paper, we shall outline the requirement, approaches, and recent progress of the suspension mount processes.

  13. Automatic segmentation of the lumen region in intravascular images of the coronary artery.

    Science.gov (United States)

    Jodas, Danilo Samuel; Pereira, Aledir Silveira; Tavares, João Manuel R S

    2017-08-01

    Image assessment of the arterial system plays an important role in the diagnosis of cardiovascular diseases. The segmentation of the lumen and media-adventitia in intravascular (IVUS) images of the coronary artery is the first step towards the evaluation of the morphology of the vessel under analysis and the identification of possible atherosclerotic lesions. In this study, a fully automatic method for the segmentation of the lumen in IVUS images of the coronary artery is presented. The proposed method relies on the K-means algorithm and the mean roundness to identify the region corresponding to the potential lumen. An approach to identify and eliminate side branches on bifurcations is also proposed to delimit the area with the potential lumen regions. Additionally, an active contour model is applied to refine the contour of the lumen region. In order to evaluate the segmentation accuracy, the results of the proposed method were compared against manual delineations made by two experts in 326 IVUS images of the coronary artery. The average values of the Jaccard measure, Hausdorff distance, percentage of area difference and Dice coefficient were 0.88 ± 0.06, 0.29 ± 0.17  mm, 0.09 ± 0.07 and 0.94 ± 0.04, respectively, in 324 IVUS images successfully segmented. Additionally, a comparison with the studies found in the literature showed that the proposed method is slight better than the majority of the related methods that have been proposed. Hence, the new automatic segmentation method is shown to be effective in detecting the lumen in IVUS images without using complex solutions and user interaction. Copyright © 2017 Elsevier B.V. All rights reserved.

  14. Role of arginase in vessel wall remodeling

    Directory of Open Access Journals (Sweden)

    William eDurante

    2013-05-01

    Full Text Available Arginase metabolizes the semi-essential amino acid L-arginine to L-ornithine and urea. There are two distinct isoforms of arginase, arginase I and II, which are encoded by separate genes and display differences in tissue distribution, subcellular localization, and molecular regulation. Blood vessels express both arginase I and II but their distribution appears to be cell-, vessel-, and species-specific. Both isoforms of arginase are induced by numerous pathologic stimuli and contribute to vascular cell dysfunction and vessel wall remodeling in several diseases. Clinical and experimental studies have documented increases in the expression and/or activity of arginase I or II in blood vessels following arterial injury and in pulmonary and arterial hypertension, aging, and atherosclerosis. Significantly, pharmacological inhibition or genetic ablation of arginase in animals ameliorates abnormalities in vascular cells and normalizes blood vessel architecture and function in all of these pathological states. The detrimental effect of arginase in vascular remodeling is attributable to its ability to stimulate vascular smooth muscle cell and endothelial cell proliferation, and collagen deposition by promoting the synthesis of polyamines and L-proline, respectively. In addition, arginase adversely impacts arterial remodeling by directing macrophages towards an inflammatory phenotype. Moreover, the proliferative, fibrotic, and inflammatory actions of arginase in the vasculature are further amplified by its capacity to inhibit nitric oxide synthesis by competing with nitric oxide synthase for substrate, L-arginine. Pharmacologic or molecular approaches targeting specific isoforms of arginase represent a promising strategy in treating obstructive fibroproliferative vascular disease.

  15. 50 CFR 648.8 - Vessel identification.

    Science.gov (United States)

    2010-10-01

    ... 50 Wildlife and Fisheries 8 2010-10-01 2010-10-01 false Vessel identification. 648.8 Section 648.8... identification. (a) Vessel name and official number. Each fishing vessel subject to this part and over 25 ft (7.6... or ocean quahog vessels licensed under New Jersey law may use the appropriate vessel identification...

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

    Directory of Open Access Journals (Sweden)

    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.

  17. Unique identification code for medical fundus images using blood vessel pattern for tele-ophthalmology applications.

    Science.gov (United States)

    Singh, Anushikha; Dutta, Malay Kishore; Sharma, Dilip Kumar

    2016-10-01

    Identification of fundus images during transmission and storage in database for tele-ophthalmology applications is an important issue in modern era. The proposed work presents a novel accurate method for generation of unique identification code for identification of fundus images for tele-ophthalmology applications and storage in databases. Unlike existing methods of steganography and watermarking, this method does not tamper the medical image as nothing is embedded in this approach and there is no loss of medical information. Strategic combination of unique blood vessel pattern and patient ID is considered for generation of unique identification code for the digital fundus images. Segmented blood vessel pattern near the optic disc is strategically combined with patient ID for generation of a unique identification code for the image. The proposed method of medical image identification is tested on the publically available DRIVE and MESSIDOR database of fundus image and results are encouraging. Experimental results indicate the uniqueness of identification code and lossless recovery of patient identity from unique identification code for integrity verification of fundus images. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  18. Familial segmental neurofibromatosis.

    Science.gov (United States)

    Oguzkan, Sibel; Cinbis, Mine; Ayter, Sükriye; Anlar, Banu; Aysun, Sabiha

    2004-05-01

    Segmental neurofibromatosis is considered to be the result of postzygotic NF1 gene mutations. We present a family in which the proband has generalized neurofibromatosis 1, whereas members of previous generations manifest segmental skin lesions. All, including the clinically asymptomatic grandmother, carry the same haplotype. This is the only case in the literature in which a parent with segmental skin findings has a child with full-blown neurofibromatosis 1 disease. The genetic mechanisms underlying this association are discussed. This family can be further investigated by examination of tissue samples from affected and unaffected sites for mutations.

  19. Using SA508/533 for the HTGR Vessel Material

    Energy Technology Data Exchange (ETDEWEB)

    Larry Demick

    2012-06-01

    This paper examines the influence of High Temperature Gas-cooled Reactor (HTGR) module power rating and normal operating temperatures on the use of SA508/533 material for the HTGR vessel system with emphasis on the calculated times at elevated temperatures approaching or exceeding ASME Code Service Limits (Levels B&C) to which the reactor pressure vessel could be exposed during postulated pressurized and depressurized conduction cooldown events over its design lifetime.

  20. Retinal vessel detection and measurement for computer-aided medical diagnosis.

    Science.gov (United States)

    Li, Xiaokun; Wee, William G

    2014-02-01

    Since blood vessel detection and characteristic measurement for ocular retinal images is a fundamental problem in computer-aided medical diagnosis, automated algorithms/systems for vessel detection and measurement are always demanded. To support computer-aided diagnosis, an integrated approach/solution for vessel detection and diameter measurement is presented and validated. In the proposed approach, a Dempster-Shafer (D-S)-based edge detector is developed to obtain initial vessel edge information and an accurate vascular map for a retinal image. Then, the appropriate path and the centerline of a vessel of interest are identified automatically through graph search. Once the vessel path has been identified, the diameter of the vessel will be measured accordingly by the algorithm in real time. To achieve more accurate edge detection and diameter measurement, mixed Gaussian-matched filters are designed to refine the initial detection and measures. Other important medical indices of retinal vessels can also be calculated accordingly based on detection and measurement results. The efficiency of the proposed algorithm was validated by the retinal images obtained from different public databases. Experimental results show that the vessel detection rate of the algorithm is 100 % for large vessels and 89.9 % for small vessels, and the error rate on vessel diameter measurement is less than 5 %, which are all well within the acceptable range of deviation among the human graders.