Refining a region-of-interest within an available CT image

International Nuclear Information System (INIS)

Enjilela, Esmaeil; Hussein, Esam M.A.

2013-01-01

This paper describes a numerical method for refining the image of a region-of-interest (RoI) within an existing tomographic slice, provided that projection data are stored along with the image. Using the attributes of the image, projection values (ray-sums) are adjusted to compensate for the material outside the RoI. Advantage is taken of the high degree of overdetermination of common computed tomography systems to reconstruct an RoI image over smaller pixels. The smaller size of a region-of-interest enables the use of iterative methods for RoI image reconstruction, which are less prone to error propagation. Simulation results are shown for an anthropomorphic head phantom, demonstrating that the introduced approach enhances both the spatial resolution and material contrast of RoI images; without the need to acquire any additional measurements or to alter existing imaging setups and systems. - Highlights: ► A method for refining the image of a region-of-interest within an existing tomographic image. ► Refined spatial-resolution within the region-of-interest, due to high redundancy of CT data. ► Enhancement in image contrast by the use of iterative image reconstruction, made possible by the smaller problem size. ► No need for additional measurements, no alteration of existing imaging setups and systems

Finding regions of interest in pathological images: an attentional model approach

Science.gov (United States)

Gómez, Francisco; Villalón, Julio; Gutierrez, Ricardo; Romero, Eduardo

2009-02-01

This paper introduces an automated method for finding diagnostic regions-of-interest (RoIs) in histopathological images. This method is based on the cognitive process of visual selective attention that arises during a pathologist's image examination. Specifically, it emulates the first examination phase, which consists in a coarse search for tissue structures at a "low zoom" to separate the image into relevant regions.1 The pathologist's cognitive performance depends on inherent image visual cues - bottom-up information - and on acquired clinical medicine knowledge - top-down mechanisms -. Our pathologist's visual attention model integrates the latter two components. The selected bottom-up information includes local low level features such as intensity, color, orientation and texture information. Top-down information is related to the anatomical and pathological structures known by the expert. A coarse approximation to these structures is achieved by an oversegmentation algorithm, inspired by psychological grouping theories. The algorithm parameters are learned from an expert pathologist's segmentation. Top-down and bottom-up integration is achieved by calculating a unique index for each of the low level characteristics inside the region. Relevancy is estimated as a simple average of these indexes. Finally, a binary decision rule defines whether or not a region is interesting. The method was evaluated on a set of 49 images using a perceptually-weighted evaluation criterion, finding a quality gain of 3dB when comparing to a classical bottom-up model of attention.

On evaluating the robustness of spatial-proximity-based regionalization methods.

OpenAIRE

Lebecherel, L.; Andréassian, V.; Perrin, C.

2016-01-01

In absence of streamflow data to calibrate a hydrological model, its parameters are to be inferred by a regionalization method. In this technical note, we discuss a specific class of regionalization methods, those based on spatial proximity, which transfers hydrological information (typically calibrated parameter sets) from neighbor gauged stations to the target ungauged station. The efficiency of any spatialproximity-based regionalization method will depend on the density of the available st...

Sliding Window-Based Region of Interest Extraction for Finger Vein Images

Science.gov (United States)

Yang, Lu; Yang, Gongping; Yin, Yilong; Xiao, Rongyang

2013-01-01

Region of Interest (ROI) extraction is a crucial step in an automatic finger vein recognition system. The aim of ROI extraction is to decide which part of the image is suitable for finger vein feature extraction. This paper proposes a finger vein ROI extraction method which is robust to finger displacement and rotation. First, we determine the middle line of the finger, which will be used to correct the image skew. Then, a sliding window is used to detect the phalangeal joints and further to ascertain the height of ROI. Last, for the corrective image with certain height, we will obtain the ROI by using the internal tangents of finger edges as the left and right boundary. The experimental results show that the proposed method can extract ROI more accurately and effectively compared with other methods, and thus improve the performance of finger vein identification system. Besides, to acquire the high quality finger vein image during the capture process, we propose eight criteria for finger vein capture from different aspects and these criteria should be helpful to some extent for finger vein capture. PMID:23507824

On evaluating the robustness of spatial-proximity-based regionalization methods.

OpenAIRE

Lebecherel , L.; Andréassian , V.; Perrin , C.

2016-01-01

International audience; In absence of streamflow data to calibrate a hydrological model, its parameters are to be inferred by a regionalization method. In this technical note, we discuss a specific class of regionalization methods, those based on spatial proximity, which transfers hydrological information (typically calibrated parameter sets) from neighbor gauged stations to the target ungauged station. The efficiency of any spatialproximity-based regionalization method will depend on the den...

NEBNext Direct: A Novel, Rapid, Hybridization-Based Approach for the Capture and Library Conversion of Genomic Regions of Interest.

Science.gov (United States)

Emerman, Amy B; Bowman, Sarah K; Barry, Andrew; Henig, Noa; Patel, Kruti M; Gardner, Andrew F; Hendrickson, Cynthia L

2017-07-05

Next-generation sequencing (NGS) is a powerful tool for genomic studies, translational research, and clinical diagnostics that enables the detection of single nucleotide polymorphisms, insertions and deletions, copy number variations, and other genetic variations. Target enrichment technologies improve the efficiency of NGS by only sequencing regions of interest, which reduces sequencing costs while increasing coverage of the selected targets. Here we present NEBNext Direct ® , a hybridization-based, target-enrichment approach that addresses many of the shortcomings of traditional target-enrichment methods. This approach features a simple, 7-hr workflow that uses enzymatic removal of off-target sequences to achieve a high specificity for regions of interest. Additionally, unique molecular identifiers are incorporated for the identification and filtering of PCR duplicates. The same protocol can be used across a wide range of input amounts, input types, and panel sizes, enabling NEBNext Direct to be broadly applicable across a wide variety of research and diagnostic needs. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

Medical Image Compression Based on Region of Interest, With Application to Colon CT Images

National Research Council Canada - National Science Library

Gokturk, Salih

2001-01-01

...., in diagnostically important regions. This paper discusses a hybrid model of lossless compression in the region of interest, with high-rate, motion-compensated, lossy compression in other regions...

Region-of-interest imaging in cone beam computerized tomography

International Nuclear Information System (INIS)

Tam, K.C.

1996-01-01

Imaging a sectional region within an object with a detector just big enough to cover the sectional region-of-interest is analyzed. We show that with some suitable choice of scanning configuration and with an innovative method of data combination, all the Radon data can be obtained accurately. The algorithm is mathematically exact, and requires no iterations and no additional measurements. The method can be applied to inspect portions of large industrial objects in industrial imaging, as well as to image portions of human bodies in medical diagnosis

On evaluating the robustness of spatial-proximity-based regionalization methods

Science.gov (United States)

Lebecherel, Laure; Andréassian, Vazken; Perrin, Charles

2016-08-01

In absence of streamflow data to calibrate a hydrological model, its parameters are to be inferred by a regionalization method. In this technical note, we discuss a specific class of regionalization methods, those based on spatial proximity, which transfers hydrological information (typically calibrated parameter sets) from neighbor gauged stations to the target ungauged station. The efficiency of any spatial-proximity-based regionalization method will depend on the density of the available streamgauging network, and the purpose of this note is to discuss how to assess the robustness of the regionalization method (i.e., its resilience to an increasingly sparse hydrometric network). We compare two options: (i) the random hydrometrical reduction (HRand) method, which consists in sub-sampling the existing gauging network around the target ungauged station, and (ii) the hydrometrical desert method (HDes), which consists in ignoring the closest gauged stations. Our tests suggest that the HDes method should be preferred, because it provides a more realistic view on regionalization performance.

Diffusion weighted imaging for differentiating benign from malignant orbital tumors: Diagnostic performance of the apparent diffusion coefficient based on region of interest selection method

Energy Technology Data Exchange (ETDEWEB)

Xu, Xiao Quan; Hu, Hao Hu; Su, Guo Yi; Liu, Hu; Shi, Hai Bin; Wu, Fei Yun [First Affiliated Hospital of Nanjing Medical University, Nanjing (China)

2016-09-15

To evaluate the differences in the apparent diffusion coefficient (ADC) measurements based on three different region of interest (ROI) selection methods, and compare their diagnostic performance in differentiating benign from malignant orbital tumors. Diffusion-weighted imaging data of sixty-four patients with orbital tumors (33 benign and 31 malignant) were retrospectively analyzed. Two readers independently measured the ADC values using three different ROIs selection methods including whole-tumor (WT), single-slice (SS), and reader-defined small sample (RDSS). The differences of ADC values (ADC-ROI{sub WT}, ADC-ROI{sub SS}, and ADC-ROI{sub RDSS}) between benign and malignant group were compared using unpaired t test. Receiver operating characteristic curve was used to determine and compare their diagnostic ability. The ADC measurement time was compared using ANOVA analysis and the measurement reproducibility was assessed using Bland-Altman method and intra-class correlation coefficient (ICC). Malignant group showed significantly lower ADC-ROI{sub WT}, ADC-ROI{sub SS}, and ADC-ROI{sub RDSS} than benign group (all p < 0.05). The areas under the curve showed no significant difference when using ADC-ROI{sub WT}, ADC-ROI{sub SS}, and ADC-ROI{sub RDSS} as differentiating index, respectively (all p > 0.05). The ROI{sub SS} and ROI{sub RDSS} required comparable measurement time (p > 0.05), while significantly shorter than ROI{sub WT} (p < 0.05). The ROI{sub SS} showed the best reproducibility (mean difference ± limits of agreement between two readers were 0.022 [-0.080–0.123] × 10{sup -3} mm{sup 2}/s; ICC, 0.997) among three ROI method. Apparent diffusion coefficient values based on the three different ROI selection methods can help to differentiate benign from malignant orbital tumors. The results of measurement time, reproducibility and diagnostic ability suggest that the ROI{sub SS} method are potentially useful for clinical practice.

Implementation of Simulation Based-Concept Attainment Method to Increase Interest Learning of Engineering Mechanics Topic

Science.gov (United States)

Sultan, A. Z.; Hamzah, N.; Rusdi, M.

2018-01-01

The implementation of concept attainment method based on simulation was used to increase student’s interest in the subjects Engineering of Mechanics in second semester of academic year 2016/2017 in Manufacturing Engineering Program, Department of Mechanical PNUP. The result of the implementation of this learning method shows that there is an increase in the students’ learning interest towards the lecture material which is summarized in the form of interactive simulation CDs and teaching materials in the form of printed books and electronic books. From the implementation of achievement method of this simulation based concept, it is noted that the increase of student participation in the presentation and discussion as well as the deposit of individual assignment of significant student. With the implementation of this method of learning the average student participation reached 89%, which before the application of this learning method only reaches an average of 76%. And also with previous learning method, for exam achievement of A-grade under 5% and D-grade above 8%. After the implementation of the new learning method (simulation based-concept attainment method) the achievement of Agrade has reached more than 30% and D-grade below 1%.

Abnormal responses of ejection fraction to exercise, in healthy subjects, caused by region-of-interest selection

International Nuclear Information System (INIS)

Sorenson, S.G.; Caldwell, J.; Ritchie, J.; Hamilton, G.

1981-01-01

We performed serial exercise equilibrium radionuclide angiography in eight normal subjects with each subject executing three tests: control, after nitroglycerin, and after propranolol. The left-ventricular ejection fraction (EF) was calculated by two methods: (a) fixed region-of-interest (FROI) using a single end-diastolic ROI, and (b) variable region-of-interest (VROI) where an end-diastolic and end-systolic region of interest were used. Abnormal maximal EF responses occurred in five of eight subjects during control using FROI but in zero of eight employing VROI (p < 0.05). After nitroglycerin, three of eight subjects had abnormal responses by FROI, but zero of eight were abnormal by VROI (p < 0.05). After propranolol, blunted EF responses occurred in three of seven by both methods. Falsely abnormal EF responses to exercise RNA may occur due to the method of region-of-interest selection in normal subjects with normal or high ejection fractions

High-Performance Region-of-Interest Image Error Concealment with Hiding Technique

Directory of Open Access Journals (Sweden)

Shih-Chang Hsia

2010-01-01

Full Text Available Recently region-of-interest (ROI based image coding is a popular topic. Since ROI area contains much more important information for an image, it must be prevented from error decoding while suffering from channel lost or unexpected attack. This paper presents an efficient error concealment method to recover ROI information with a hiding technique. Based on the progressive transformation, the low-frequency components of ROI are encoded to disperse its information into the high-frequency bank of original image. The capability of protection is carried out with extracting the ROI coefficients from the damaged image without increasing extra information. Simulation results show that the proposed method can efficiently reconstruct the ROI image when ROI bit-stream occurs errors, and the measurement of PSNR result outperforms the conventional error concealment techniques by 2 to 5 dB.

Cloud solution for histopathological image analysis using region of interest based compression.

Science.gov (United States)

Kanakatte, Aparna; Subramanya, Rakshith; Delampady, Ashik; Nayak, Rajarama; Purushothaman, Balamuralidhar; Gubbi, Jayavardhana

2017-07-01

Recent technological gains have led to the adoption of innovative cloud based solutions in medical imaging field. Once the medical image is acquired, it can be viewed, modified, annotated and shared on many devices. This advancement is mainly due to the introduction of Cloud computing in medical domain. Tissue pathology images are complex and are normally collected at different focal lengths using a microscope. The single whole slide image contains many multi resolution images stored in a pyramidal structure with the highest resolution image at the base and the smallest thumbnail image at the top of the pyramid. Highest resolution image will be used for tissue pathology diagnosis and analysis. Transferring and storing such huge images is a big challenge. Compression is a very useful and effective technique to reduce the size of these images. As pathology images are used for diagnosis, no information can be lost during compression (lossless compression). A novel method of extracting the tissue region and applying lossless compression on this region and lossy compression on the empty regions has been proposed in this paper. The resulting compression ratio along with lossless compression on tissue region is in acceptable range allowing efficient storage and transmission to and from the Cloud.

Lightweight Object Tracking in Compressed Video Streams Demonstrated in Region-of-Interest Coding

Directory of Open Access Journals (Sweden)

Lerouge Sam

2007-01-01

Full Text Available Video scalability is a recent video coding technology that allows content providers to offer multiple quality versions from a single encoded video file in order to target different kinds of end-user devices and networks. One form of scalability utilizes the region-of-interest concept, that is, the possibility to mark objects or zones within the video as more important than the surrounding area. The scalable video coder ensures that these regions-of-interest are received by an end-user device before the surrounding area and preferably in higher quality. In this paper, novel algorithms are presented making it possible to automatically track the marked objects in the regions of interest. Our methods detect the overall motion of a designated object by retrieving the motion vectors calculated during the motion estimation step of the video encoder. Using this knowledge, the region-of-interest is translated, thus following the objects within. Furthermore, the proposed algorithms allow adequate resizing of the region-of-interest. By using the available information from the video encoder, object tracking can be done in the compressed domain and is suitable for real-time and streaming applications. A time-complexity analysis is given for the algorithms proving the low complexity thereof and the usability for real-time applications. The proposed object tracking methods are generic and can be applied to any codec that calculates the motion vector field. In this paper, the algorithms are implemented within MPEG-4 fine-granularity scalability codec. Different tests on different video sequences are performed to evaluate the accuracy of the methods. Our novel algorithms achieve a precision up to 96.4 .

Lightweight Object Tracking in Compressed Video Streams Demonstrated in Region-of-Interest Coding

Directory of Open Access Journals (Sweden)

Rik Van de Walle

2007-01-01

Full Text Available Video scalability is a recent video coding technology that allows content providers to offer multiple quality versions from a single encoded video file in order to target different kinds of end-user devices and networks. One form of scalability utilizes the region-of-interest concept, that is, the possibility to mark objects or zones within the video as more important than the surrounding area. The scalable video coder ensures that these regions-of-interest are received by an end-user device before the surrounding area and preferably in higher quality. In this paper, novel algorithms are presented making it possible to automatically track the marked objects in the regions of interest. Our methods detect the overall motion of a designated object by retrieving the motion vectors calculated during the motion estimation step of the video encoder. Using this knowledge, the region-of-interest is translated, thus following the objects within. Furthermore, the proposed algorithms allow adequate resizing of the region-of-interest. By using the available information from the video encoder, object tracking can be done in the compressed domain and is suitable for real-time and streaming applications. A time-complexity analysis is given for the algorithms proving the low complexity thereof and the usability for real-time applications. The proposed object tracking methods are generic and can be applied to any codec that calculates the motion vector field. In this paper, the algorithms are implemented within MPEG-4 fine-granularity scalability codec. Different tests on different video sequences are performed to evaluate the accuracy of the methods. Our novel algorithms achieve a precision up to 96.4%.

Automated Region of Interest Retrieval of Metallographic Images for Quality Classification in Industry

Directory of Open Access Journals (Sweden)

Petr Kotas

2012-01-01

Full Text Available The aim of the research is development and testing of new methods to classify the quality of metallographic samples of steels with high added value (for example grades X70 according API. In this paper, we address the development of methods to classify the quality of slab samples images with the main emphasis on the quality of the image center called as segregation area. For this reason, we introduce an alternative method for automated retrieval of region of interest. In the first step, the metallographic image is segmented using both spectral method and thresholding. Then, the extracted macrostructure of the metallographic image is automatically analyzed by statistical methods. Finally, automatically extracted region of interests are compared with results of human experts.  Practical experience with retrieval of non-homogeneous noised digital images in industrial environment is discussed as well.

Diffuse intrinsic pontine glioma: is MRI surveillance improved by region of interest volumetry?

Science.gov (United States)

Riley, Garan T; Armitage, Paul A; Batty, Ruth; Griffiths, Paul D; Lee, Vicki; McMullan, John; Connolly, Daniel J A

2015-02-01

Paediatric diffuse intrinsic pontine glioma (DIPG) is noteworthy for its fibrillary infiltration through neuroparenchyma and its resultant irregular shape. Conventional volumetry methods aim to approximate such irregular tumours to a regular ellipse, which could be less accurate when assessing treatment response on surveillance MRI. Region-of-interest (ROI) volumetry methods, using manually traced tumour profiles on contiguous imaging slices and subsequent computer-aided calculations, may prove more reliable. To evaluate whether the reliability of MRI surveillance of DIPGs can be improved by the use of ROI-based volumetry. We investigated the use of ROI- and ellipsoid-based methods of volumetry for paediatric DIPGs in a retrospective review of 22 MRI examinations. We assessed the inter- and intraobserver variability of the two methods when performed by four observers. ROI- and ellipsoid-based methods strongly correlated for all four observers. The ROI-based volumes showed slightly better agreement both between and within observers than the ellipsoid-based volumes (inter-[intra-]observer agreement 89.8% [92.3%] and 83.1% [88.2%], respectively). Bland-Altman plots show tighter limits of agreement for the ROI-based method. Both methods are reproducible and transferrable among observers. ROI-based volumetry appears to perform better with greater intra- and interobserver agreement for complex-shaped DIPG.

Diffuse intrinsic pontine glioma: is MRI surveillance improved by region of interest volumetry?

International Nuclear Information System (INIS)

Riley, Garan T.; Armitage, Paul A.; Griffiths, Paul D.; Batty, Ruth; Connolly, Daniel J.A.; Lee, Vicki; McMullan, John

2015-01-01

Paediatric diffuse intrinsic pontine glioma (DIPG) is noteworthy for its fibrillary infiltration through neuroparenchyma and its resultant irregular shape. Conventional volumetry methods aim to approximate such irregular tumours to a regular ellipse, which could be less accurate when assessing treatment response on surveillance MRI. Region-of-interest (ROI) volumetry methods, using manually traced tumour profiles on contiguous imaging slices and subsequent computer-aided calculations, may prove more reliable. To evaluate whether the reliability of MRI surveillance of DIPGs can be improved by the use of ROI-based volumetry. We investigated the use of ROI- and ellipsoid-based methods of volumetry for paediatric DIPGs in a retrospective review of 22 MRI examinations. We assessed the inter- and intraobserver variability of the two methods when performed by four observers. ROI- and ellipsoid-based methods strongly correlated for all four observers. The ROI-based volumes showed slightly better agreement both between and within observers than the ellipsoid-based volumes (inter-[intra-]observer agreement 89.8% [92.3%] and 83.1% [88.2%], respectively). Bland-Altman plots show tighter limits of agreement for the ROI-based method. Both methods are reproducible and transferrable among observers. ROI-based volumetry appears to perform better with greater intra- and interobserver agreement for complex-shaped DIPG. (orig.)

Diffuse intrinsic pontine glioma: is MRI surveillance improved by region of interest volumetry?

Energy Technology Data Exchange (ETDEWEB)

Riley, Garan T. [University Hospital of North Tees, Department of General Radiology, North Tees and Hartlepool NHS Foundation Trust, Stockton-on-Tees, Cleveland (United Kingdom); Armitage, Paul A.; Griffiths, Paul D. [University of Sheffield, Academic Unit of Radiology, Sheffield (United Kingdom); Batty, Ruth; Connolly, Daniel J.A. [Sheffield Children' s NHS Foundation Trust, Department of Radiology, Sheffield (United Kingdom); Lee, Vicki [Sheffield Children' s NHS Foundation Trust, Department of Oncology, Sheffield (United Kingdom); McMullan, John [Sheffield Children' s NHS Foundation Trust, Department of Neurosurgery, Sheffield (United Kingdom)

2014-08-21

Paediatric diffuse intrinsic pontine glioma (DIPG) is noteworthy for its fibrillary infiltration through neuroparenchyma and its resultant irregular shape. Conventional volumetry methods aim to approximate such irregular tumours to a regular ellipse, which could be less accurate when assessing treatment response on surveillance MRI. Region-of-interest (ROI) volumetry methods, using manually traced tumour profiles on contiguous imaging slices and subsequent computer-aided calculations, may prove more reliable. To evaluate whether the reliability of MRI surveillance of DIPGs can be improved by the use of ROI-based volumetry. We investigated the use of ROI- and ellipsoid-based methods of volumetry for paediatric DIPGs in a retrospective review of 22 MRI examinations. We assessed the inter- and intraobserver variability of the two methods when performed by four observers. ROI- and ellipsoid-based methods strongly correlated for all four observers. The ROI-based volumes showed slightly better agreement both between and within observers than the ellipsoid-based volumes (inter-[intra-]observer agreement 89.8% [92.3%] and 83.1% [88.2%], respectively). Bland-Altman plots show tighter limits of agreement for the ROI-based method. Both methods are reproducible and transferrable among observers. ROI-based volumetry appears to perform better with greater intra- and interobserver agreement for complex-shaped DIPG. (orig.)

Functional connectivity analysis of fMRI data using parameterized regions-of-interest.

NARCIS (Netherlands)

Weeda, W.D.; Waldorp, L.J.; Grasman, R.P.P.P.; van Gaal, S.; Huizenga, H.M.

2011-01-01

Connectivity analysis of fMRI data requires correct specification of regions-of-interest (ROIs). Selection of ROIs based on outcomes of a GLM analysis may be hindered by conservativeness of the multiple comparison correction, while selection based on brain anatomy may be biased due to inconsistent

A robust automated left ventricle region of interest localization technique using a cardiac cine MRI atlas

Science.gov (United States)

Ben-Zikri, Yehuda Kfir; Linte, Cristian A.

2016-03-01

Region of interest detection is a precursor to many medical image processing and analysis applications, including segmentation, registration and other image manipulation techniques. The optimal region of interest is often selected manually, based on empirical knowledge and features of the image dataset. However, if inconsistently identified, the selected region of interest may greatly affect the subsequent image analysis or interpretation steps, in turn leading to incomplete assessment during computer-aided diagnosis or incomplete visualization or identification of the surgical targets, if employed in the context of pre-procedural planning or image-guided interventions. Therefore, the need for robust, accurate and computationally efficient region of interest localization techniques is prevalent in many modern computer-assisted diagnosis and therapy applications. Here we propose a fully automated, robust, a priori learning-based approach that provides reliable estimates of the left and right ventricle features from cine cardiac MR images. The proposed approach leverages the temporal frame-to-frame motion extracted across a range of short axis left ventricle slice images with small training set generated from les than 10% of the population. This approach is based on histogram of oriented gradients features weighted by local intensities to first identify an initial region of interest depicting the left and right ventricles that exhibits the greatest extent of cardiac motion. This region is correlated with the homologous region that belongs to the training dataset that best matches the test image using feature vector correlation techniques. Lastly, the optimal left ventricle region of interest of the test image is identified based on the correlation of known ground truth segmentations associated with the training dataset deemed closest to the test image. The proposed approach was tested on a population of 100 patient datasets and was validated against the ground truth

Exploring HIV-AIDS interests in the MENA region using Internet based searches

NARCIS (Netherlands)

A.K. Al-Rawi (Ahmed)

2017-01-01

textabstractDue to the scarcity of official data on sexually transmitted diseases in the Middle East and North Africa region (MENA), it becomes important to seek alternative indications on the online information interests and possible spread of such diseases. This paper uses news stories from 10

Multi-Task Vehicle Detection with Region-of-Interest Voting.

Science.gov (United States)

Chu, Wenqing; Liu, Yao; Shen, Chen; Cai, Deng; Hua, Xian-Sheng

2017-10-12

Vehicle detection is a challenging problem in autonomous driving systems, due to its large structural and appearance variations. In this paper, we propose a novel vehicle detection scheme based on multi-task deep convolutional neural networks (CNN) and region-of-interest (RoI) voting. In the design of CNN architecture, we enrich the supervised information with subcategory, region overlap, bounding-box regression and category of each training RoI as a multi-task learning framework. This design allows the CNN model to share visual knowledge among different vehicle attributes simultaneously, thus detection robustness can be effectively improved. In addition, most existing methods consider each RoI independently, ignoring the clues from its neighboring RoIs. In our approach, we utilize the CNN model to predict the offset direction of each RoI boundary towards the corresponding ground truth. Then each RoI can vote those suitable adjacent bounding boxes which are consistent with this additional information. The voting results are combined with the score of each RoI itself to find a more accurate location from a large number of candidates. Experimental results on the real-world computer vision benchmarks KITTI and the PASCAL2007 vehicle dataset show that our approach achieves superior performance in vehicle detection compared with other existing published works.

Multi-Electrode Impedance Method for Detection of Regional Ventilation

International Nuclear Information System (INIS)

Furuya, Norio; Sakamoto, Katsuyuki

2013-01-01

By means of computer simulation and experiment, we investigated the feasibility of simultaneously measuring the transfer impedance changes in the right apex, left apex, right base and left base of the lungs using the multi-electrode impedance method. To obtain the transfer impedance in each region, while suppressing the effects of other regions, changing the amplitude and polarity of the applied current must localize the high sensitivity areas in the interest region. Twelve current and eight voltage electrodes were equidistantly arranged on the anterior and posterior chest walls. The amplitudes and polarities of the currents that were simultaneously applied to the current electrodes, and which provided the appropriate sensitivity distribution, were theoretically obtained. The effects of the localized sensitivity distribution were verified by comparing the simulation results of the investigated method with the results of the conventional four-electrode method. From the results of the computer simulation, we developed a multi-electrode impedance pneumography and applied it to healthy adult volunteers who were both in sitting position and in left decubitus. We found that the measurement results were physiologically reasonable.

Band selection method based on spectrum difference in targets of interest in hyperspectral imagery

Science.gov (United States)

Zhang, Xiaohan; Yang, Guang; Yang, Yongbo; Huang, Junhua

2016-10-01

While hyperspectral data shares rich spectrum information, it has numbers of bands with high correlation coefficients, causing great data redundancy. A reasonable band selection is important for subsequent processing. Bands with large amount of information and low correlation should be selected. On this basis, according to the needs of target detection applications, the spectral characteristics of the objects of interest are taken into consideration in this paper, and a new method based on spectrum difference is proposed. Firstly, according to the spectrum differences of targets of interest, a difference matrix which represents the different spectral reflectance of different targets in different bands is structured. By setting a threshold, the bands satisfying the conditions would be left, constituting a subset of bands. Then, the correlation coefficients between bands are calculated and correlation matrix is given. According to the size of the correlation coefficient, the bands can be set into several groups. At last, the conception of normalized variance is used on behalf of the information content of each band. The bands are sorted by the value of its normalized variance. Set needing number of bands, and the optimum band combination solution can be get by these three steps. This method retains the greatest degree of difference between the target of interest and is easy to achieve by computer automatically. Besides, false color image synthesis experiment is carried out using the bands selected by this method as well as other 3 methods to show the performance of method in this paper.

A Divide and Conquer Strategy for Scaling Weather Simulations with Multiple Regions of Interest

Directory of Open Access Journals (Sweden)

Preeti Malakar

2013-01-01

Full Text Available Accurate and timely prediction of weather phenomena, such as hurricanes and flash floods, require high-fidelity compute intensive simulations of multiple finer regions of interest within a coarse simulation domain. Current weather applications execute these nested simulations sequentially using all the available processors, which is sub-optimal due to their sub-linear scalability. In this work, we present a strategy for parallel execution of multiple nested domain simulations based on partitioning the 2-D processor grid into disjoint rectangular regions associated with each domain. We propose a novel combination of performance prediction, processor allocation methods and topology-aware mapping of the regions on torus interconnects. Experiments on IBM Blue Gene systems using WRF show that the proposed strategies result in performance improvement of up to 33% with topology-oblivious mapping and up to additional 7% with topology-aware mapping over the default sequential strategy.

Student Youth: Dynamics of Political Interests (Regional Aspect

Directory of Open Access Journals (Sweden)

Morozova Galina Viktorovna

2015-12-01

Full Text Available The article presents the main results of the research of interests and political orientations of student youth which was carried out in 2014 at the Kazan federal university and its branches in the territory of the Republic of Tatarstan. The choice of student youth as a reference group is caused by a number of factors, among which we should name the status of intellectual elite, social and political mobility that allows to consider students as the potential actors of socio-political transformations in the country. The data obtained during poll compared with the results of last research allow defining the dynamics of development of student youth’s political sentiment in the region. The study of political attitudes, preferences of students was based on the identification of a number of indicators (degree of interest in politics, the level of personal involvement in political life and on the study of factors that determine the motivation of political behavior of students. Empirical studies make it possible to rank the problems that dominate the political consciousness of students in the region. These include a high level of corruption in the government, inflation, rising prices, the state of health and education systems and the growing income inequality. Particular attention is accented on the problems associated with the foreign policy aspects, threats, aggression from abroad. The study showed that most young people’s interest in politics is limited primarily by informational level, rarely they have desire to express their own position or judgments in political situations. The level of real political participation, socio-political activity of students is low. Obtained results let us notice the increasing trend of demonstration of protest behavior among certain part of the students.

Risk-based prioritization method for the classification of groundwater pesticide pollution from agricultural regions.

Science.gov (United States)

Yang, Yu; Lian, Xin-Ying; Jiang, Yong-Hai; Xi, Bei-Dou; He, Xiao-Song

2017-11-01

Agricultural regions are a significant source of groundwater pesticide pollution. To ensure that agricultural regions with a significantly high risk of groundwater pesticide contamination are properly managed, a risk-based ranking method related to groundwater pesticide contamination is needed. In the present paper, a risk-based prioritization method for the classification of groundwater pesticide pollution from agricultural regions was established. The method encompasses 3 phases, including indicator selection, characterization, and classification. In the risk ranking index system employed here, 17 indicators involving the physicochemical properties, environmental behavior characteristics, pesticide application methods, and inherent vulnerability of groundwater in the agricultural region were selected. The boundary of each indicator was determined using K-means cluster analysis based on a survey of a typical agricultural region and the physical and chemical properties of 300 typical pesticides. The total risk characterization was calculated by multiplying the risk value of each indicator, which could effectively avoid the subjectivity of index weight calculation and identify the main factors associated with the risk. The results indicated that the risk for groundwater pesticide contamination from agriculture in a region could be ranked into 4 classes from low to high risk. This method was applied to an agricultural region in Jiangsu Province, China, and it showed that this region had a relatively high risk for groundwater contamination from pesticides, and that the pesticide application method was the primary factor contributing to the relatively high risk. The risk ranking method was determined to be feasible, valid, and able to provide reference data related to the risk management of groundwater pesticide pollution from agricultural regions. Integr Environ Assess Manag 2017;13:1052-1059. © 2017 SETAC. © 2017 SETAC.

CubeIndexer: Indexer for regions of interest in data cubes

Science.gov (United States)

Chilean Virtual Observatory; Araya, Mauricio; Candia, Gabriel; Gregorio, Rodrigo; Mendoza, Marcelo; Solar, Mauricio

2015-12-01

CubeIndexer indexes regions of interest (ROIs) in data cubes reducing the necessary storage space. The software can process data cubes containing megabytes of data in fractions of a second without human supervision, thus allowing it to be incorporated into a production line for displaying objects in a virtual observatory. The software forms part of the Chilean Virtual Observatory (ChiVO) and provides the capability of content-based searches on data cubes to the astronomical community.

The Evolution of the Region of Interest Builder for the ATLAS Experiment at CERN

CERN Document Server

AUTHOR|(INSPIRE)INSPIRE-00060668; Blair, Robert; Crone, Gordon Jeremy; Green, Barry; Love, Jeremy; Proudfoot, James; Rifki, Othmane; Panduro Vazquez, William; Vandelli, Wainer; Zhang, Jinlong

2016-01-01

ATLAS is a general purpose particle detector, at the Large Hadron Collider (LHC) at CERN, designed to measure the products of proton collisions. Given the high interaction rate (40 MHz), selective triggering in real time is required to reduce the rate to the experiment's data storage capacity (1 kHz). To meet this requirement, ATLAS employs a hardware trigger that reduces the rate to 100 kHz and software based triggers to select interesting interactions for physics analysis. The Region of Interest Builder (RoIB) is an essential part of the ATLAS detector Trigger and Data Acquisition (TDAQ) chain where the coordinates of the regions of interest (RoIs) identified by the first level trigger (L1) are collected and passed to the High Level Trigger (HLT) to make a decision. While the current custom VME based RoIB operated reliably during the first run of the LHC, it is desirable to have a more flexible RoIB and more operationally maintainable in the future, as the LHC reaches higher luminosity and ATLAS increases t...

Based on user interest level of modeling scenarios and browse content

Science.gov (United States)

Zhao, Yang

2017-08-01

User interest modeling is the core of personalized service, taking into account the impact of situational information on user preferences, the user behavior days of financial information. This paper proposes a method of user interest modeling based on scenario information, which is obtained by calculating the similarity of the situation. The user's current scene of the approximate scenario set; on the "user - interest items - scenarios" three-dimensional model using the situation pre-filtering method of dimension reduction processing. View the content of the user interested in the theme, the analysis of the page content to get each topic of interest keywords, based on the level of vector space model user interest. The experimental results show that the user interest model based on the scenario information is within 9% of the user's interest prediction, which is effective.

Strategy of Commercial Real Estate Market Development and Interests of the Region: Rostov Region

Directory of Open Access Journals (Sweden)

Kosarev Roman, V.

2016-07-01

Full Text Available The author discusses the features of the development of commercial real estate market in the Rostov region on the assumption of a relationship between the vector of entrepreneurial activity and the dynamics of supply and demand of real estate in the context of the public interest. The urgency of the problem is due to the institutional nature of commercial real estate in business development, which is neglected in the practice of public exposure due to lack of methodological support and instrumentality. Based on the self-organization of these dynamic models related economic systems in the economy of the region, a logical assessment of the trends of development of business in the consumer market in the context of the real estate needs as infrastructure is given. It allows to identify the main patterns of development and its specific regional features. Statistical evaluation of the cost of renting and buying commercial real estate in Rostov-on-Don city has helped to identify new strategies for business development, requiring the transformation of commercial property types, proposed in the framework of regional program with a focus on five trends of Global Power of Retailing 2015.

A voxelwise approach to determine consensus regions-of-interest for the study of brain network plasticity

Directory of Open Access Journals (Sweden)

Sarah M. Rajtmajer

2015-07-01

Full Text Available Despite exciting advances in the functional imaging of the brain, it remains a challenge to define regions of interest (ROIs that do not require investigator supervision and permit examination of change in networks over time (or plasticity. Plasticity is most readily examined by maintaining ROIs constant via seed-based and anatomical-atlas based techniques, but these approaches are not data-driven, requiring definition based on prior experience (e.g. choice of seed-region, anatomical landmarks. These approaches are limiting especially when functional connectivity may evolve over time in areas that are finer than known anatomical landmarks or in areas outside predetermined seeded regions. An ideal method would permit investigators to study network plasticity due to learning, maturation effects, or clinical recovery via multiple time point data that can be compared to one another in the same ROI while also preserving the voxel-level data in those ROIs at each time point. Data-driven approaches (e.g., whole-brain voxelwise approaches ameliorate concerns regarding investigator bias, but the fundamental problem of comparing the results between distinct data sets remains. In this paper we propose an approach, aggregate-initialized label propagation (AILP, which allows for data at separate time points to be compared for examining developmental processes resulting in network change (plasticity. To do so, we use a whole-brain modularity approach to parcellate the brain into anatomically constrained functional modules at separate time points and then apply the AILP algorithm to form a consensus set of ROIs for examining change over time. To demonstrate its utility, we make use of a known dataset of individuals with traumatic brain injury sampled at two time points during the first year of recovery and show how the AILP procedure can be applied to select regions of interest to be used in a graph theoretical analysis of plasticity.

Interior region-of-interest reconstruction using a small, nearly piecewise constant subregion

International Nuclear Information System (INIS)

Taguchi, Katsuyuki; Xu Jingyan; Srivastava, Somesh; Tsui, Benjamin M. W.; Cammin, Jochen; Tang Qiulin

2011-01-01

Purpose: To develop a method to reconstruct an interior region-of-interest (ROI) image with sufficient accuracy that uses differentiated backprojection (DBP) projection onto convex sets (POCS) [H. Kudo et al., ''Tiny a priori knowledge solves the interior problem in computed tomography'', Phys. Med. Biol. 53, 2207-2231 (2008)] and a tiny knowledge that there exists a nearly piecewise constant subregion. Methods: The proposed method first employs filtered backprojection to reconstruct an image on which a tiny region P with a small variation in the pixel values is identified inside the ROI. Total variation minimization [H. Yu and G. Wang, ''Compressed sensing based interior tomography'', Phys. Med. Biol. 54, 2791-2805 (2009); W. Han et al., ''A general total variation minimization theorem for compressed sensing based interior tomography'', Int. J. Biomed. Imaging 2009, Article 125871 (2009)] is then employed to obtain pixel values in the subregion P, which serve as a priori knowledge in the next step. Finally, DBP-POCS is performed to reconstruct f(x,y) inside the ROI. Clinical data and the reconstructed image obtained by an x-ray computed tomography system (SOMATOM Definition; Siemens Healthcare) were used to validate the proposed method. The detector covers an object with a diameter of ∼500 mm. The projection data were truncated either moderately to limit the detector coverage to diameter 350 mm of the object or severely to cover diameter 199 mm. Images were reconstructed using the proposed method. Results: The proposed method provided ROI images with correct pixel values in all areas except near the edge of the ROI. The coefficient of variation, i.e., the root mean square error divided by the mean pixel values, was less than 2.0% or 4.5% with the moderate or severe truncation cases, respectively, except near the boundary of the ROI. Conclusions: The proposed method allows for reconstructing interior ROI images with sufficient accuracy with a tiny knowledge that

Digital assessment of distrurbances of ventilation distribution by defined regions of interest

International Nuclear Information System (INIS)

Reuter, T.D.; Kirchhuebel, H.; Dahlgruen, H.D.

1976-01-01

Pulmonary distribution of ventilation was assessed in ten patients with COPD on the basis of defined regions of interest. Areas of hypeventilation are demarcated on the basis of the trapped air scintigram corrected for lung volume. After the demarcations are transfered to the scintigram of fractional exchange of air the regional VI is computed and compared with normal values. The detectability of regional ventilation disturbances was found to be improved compared to a subdivision scheme of six regions of interest

A new fast algorithm for the evaluation of regions of interest and statistical uncertainty in computed tomography

International Nuclear Information System (INIS)

Huesman, R.H.

1984-01-01

A new algorithm for region of interest evaluation in computed tomography is described. Region of interest evaluation is a technique used to improve quantitation of the tomographic imaging process by summing (or averaging) the reconstructed quantity throughout a volume of particular significance. An important application of this procedure arises in the analysis of dynamic emission computed tomographic data, in which the uptake and clearance of radiotracers are used to determine the blood flow and/or physiologica function of tissue within the significant volume. The new algorithm replaces the conventional technique of repeated image reconstructions with one in which projected regions are convolved and then used to form multiple vector inner products with the raw tomographic data sets. Quantitation of regions of interest is made without the need for reconstruction of tomographic images. The computational advantage of the new algorithm over conventional methods is between factors of 20 and of 500 for typical applications encountered in medical science studies. The greatest benefit is the ease with which the statistical uncertainty of the result is computed. The entire covariance matrix for the evaluation of regions of interest can be calculated with relatively few operations. (author)

Automated detection of regions of interest for tissue microarray experiments: an image texture analysis

International Nuclear Information System (INIS)

Karaçali, Bilge; Tözeren, Aydin

2007-01-01

Recent research with tissue microarrays led to a rapid progress toward quantifying the expressions of large sets of biomarkers in normal and diseased tissue. However, standard procedures for sampling tissue for molecular profiling have not yet been established. This study presents a high throughput analysis of texture heterogeneity on breast tissue images for the purpose of identifying regions of interest in the tissue for molecular profiling via tissue microarray technology. Image texture of breast histology slides was described in terms of three parameters: the percentage of area occupied in an image block by chromatin (B), percentage occupied by stroma-like regions (P), and a statistical heterogeneity index H commonly used in image analysis. Texture parameters were defined and computed for each of the thousands of image blocks in our dataset using both the gray scale and color segmentation. The image blocks were then classified into three categories using the texture feature parameters in a novel statistical learning algorithm. These categories are as follows: image blocks specific to normal breast tissue, blocks specific to cancerous tissue, and those image blocks that are non-specific to normal and disease states. Gray scale and color segmentation techniques led to identification of same regions in histology slides as cancer-specific. Moreover the image blocks identified as cancer-specific belonged to those cell crowded regions in whole section image slides that were marked by two pathologists as regions of interest for further histological studies. These results indicate the high efficiency of our automated method for identifying pathologic regions of interest on histology slides. Automation of critical region identification will help minimize the inter-rater variability among different raters (pathologists) as hundreds of tumors that are used to develop an array have typically been evaluated (graded) by different pathologists. The region of interest

Risk-based decision making and risk management of European Union regional programs

Directory of Open Access Journals (Sweden)

Michalopoulos Evangelos

2008-01-01

Full Text Available This paper presents a generalized method for management decision making incorporating risk assessment techniques. The risk based decision making methodology is applied to European Union expenditure programs used to implement its regional policy, such as the community support framework, community initiatives, special initiatives and other European policies. An example is presented for the development of an audit (inspection program in the region of West Macedonia, Greece, during the implementation of the 3rd Community Structural Support Framework Operational Program. The generic nature of the method permits its use in the management of similar European regional programs in Greece and other European countries. It is also applicable to many other industries interested in applying risk-based management decisions to physical or process based systems. .

Fast region-based object detection and tracking using correlation of features

CSIR Research Space (South Africa)

Senekal, F

2010-11-01

Full Text Available and track a target object (or objects) over a series of digital images. Visual target tracking can be accomplished by feature-based or region-based approaches. In feature-based approaches, interest points are calculated in a digital image, and a local...-time performance based on the computational power that is available on a specific platform. To further reduce the computational requirements, process- ing is restricted to the region of interest (ROI). The region of interest is provided as an input parameter...

The evolution of the region of interest builder for the ATLAS experiment at CERN

International Nuclear Information System (INIS)

Abbott, B.; Rifki, O.; Blair, R.; Love, J.; Proudfoot, J.; Zhang, J.; Crone, G.; Green, B.; Vazquez, W.P.; Vandelli, W.

2016-01-01

The ATLAS detector uses a real time selective triggering system to reduce the high interaction rate from 40 MHz to its data storage capacity of 1 kHz. A hardware first level (L1) trigger limits the rate to 100 kHz and a software high level trigger (HLT) selects events for offline analysis. The HLT uses the Regions of Interest (RoIs) identified by L1 and provided by the Region of Interest Builder (RoIB). The current RoIB is a custom VMEbus based system that operated reliably since the first run of the LHC . Since the LHC will reach higher luminosity and ATLAS will increase the complexity and number of L1 triggers, it is desirable to have a more flexible and more operationally maintainable RoIB in the future. In this regard, the functionality of the multi-card VMEbus based RoIB is being migrated to a PC based RoIB with a PCI-Express card. Testing has produced a system that achieved the targeted rate of 100 kHz

Reconstruction for interior region-of-interest inverse geometry computed tomography: preliminary study

Energy Technology Data Exchange (ETDEWEB)

Kim, Dong Su; Kim, Tae Ho; Kim, Kyeong Hyeon; Yoon, Do Kun; Suh, Tae Suk [Dept. of Biomedical Engineering, Research Institute of Biomedical Engineering, College of Medicine, The Catholic University of Korea, Seoul (Korea, Republic of); Kang, Seong Hee [Dept. of Radiation Oncology, Seoul National University Hospital, Seoul (Korea, Republic of); Cho, Min Seok [Dept. of Radiation Oncology, Asan Medical Center, Seoul (Korea, Republic of); Noh, Yu Yoon [Dept. of Radiation Oncology, Eulji University Hospital, Daejeon (Korea, Republic of)

2017-04-15

The inverse geometry computed tomography (IGCT) composed of multiple source and small size detector has several merits such as reduction of scatter effect and large volumetric imaging within one rotation without cone-beam artifact, compared to conventional cone-beam computed tomography (CBCT). By using this multi-source characteristics, we intend to present a selective and multiple interior region-of-interest (ROI) imaging method by using a designed source on-off sequence of IGCT. ROI-IGCT showed comparable image quality and has the capability to provide multi ROI image within a rotation. In this regard, it seems to be useful for diagnostic or image guidance for radiotherapy. ROI-IGCT showed comparable image quality and has the capability to provide multi ROI image within a rotation. Projection of ROI-IGCT is performed by selective irradiation, hence unnecessary imaging dose to non-interest region can be reduced. In this regard, it seems to be useful for diagnostic or image guidance for radiotherapy.

Biomedical image representation approach using visualness and spatial information in a concept feature space for interactive region-of-interest-based retrieval.

Science.gov (United States)

Rahman, Md Mahmudur; Antani, Sameer K; Demner-Fushman, Dina; Thoma, George R

2015-10-01

This article presents an approach to biomedical image retrieval by mapping image regions to local concepts where images are represented in a weighted entropy-based concept feature space. The term "concept" refers to perceptually distinguishable visual patches that are identified locally in image regions and can be mapped to a glossary of imaging terms. Further, the visual significance (e.g., visualness) of concepts is measured as the Shannon entropy of pixel values in image patches and is used to refine the feature vector. Moreover, the system can assist the user in interactively selecting a region-of-interest (ROI) and searching for similar image ROIs. Further, a spatial verification step is used as a postprocessing step to improve retrieval results based on location information. The hypothesis that such approaches would improve biomedical image retrieval is validated through experiments on two different data sets, which are collected from open access biomedical literature.

Video-based respiration monitoring with automatic region of interest detection

NARCIS (Netherlands)

Janssen, R.J.M.; Wang, Wenjin; Moço, A.; de Haan, G.

2016-01-01

Vital signs monitoring is ubiquitous in clinical environments and emerging in home-based healthcare applications. Still, since current monitoring methods require uncomfortable sensors, respiration rate remains the least measured vital sign. In this paper, we propose a video-based respiration

Analysis of iterative region-of-interest image reconstruction for x-ray computed tomography.

Science.gov (United States)

Sidky, Emil Y; Kraemer, David N; Roth, Erin G; Ullberg, Christer; Reiser, Ingrid S; Pan, Xiaochuan

2014-10-03

One of the challenges for iterative image reconstruction (IIR) is that such algorithms solve an imaging model implicitly, requiring a complete representation of the scanned subject within the viewing domain of the scanner. This requirement can place a prohibitively high computational burden for IIR applied to x-ray computed tomography (CT), especially when high-resolution tomographic volumes are required. In this work, we aim to develop an IIR algorithm for direct region-of-interest (ROI) image reconstruction. The proposed class of IIR algorithms is based on an optimization problem that incorporates a data fidelity term, which compares a derivative of the estimated data with the available projection data. In order to characterize this optimization problem, we apply it to computer-simulated two-dimensional fan-beam CT data, using both ideal noiseless data and realistic data containing a level of noise comparable to that of the breast CT application. The proposed method is demonstrated for both complete field-of-view and ROI imaging. To demonstrate the potential utility of the proposed ROI imaging method, it is applied to actual CT scanner data.

Digital Sequences and a Time Reversal-Based Impact Region Imaging and Localization Method

Science.gov (United States)

Qiu, Lei; Yuan, Shenfang; Mei, Hanfei; Qian, Weifeng

2013-01-01

To reduce time and cost of damage inspection, on-line impact monitoring of aircraft composite structures is needed. A digital monitor based on an array of piezoelectric transducers (PZTs) is developed to record the impact region of impacts on-line. It is small in size, lightweight and has low power consumption, but there are two problems with the impact alarm region localization method of the digital monitor at the current stage. The first one is that the accuracy rate of the impact alarm region localization is low, especially on complex composite structures. The second problem is that the area of impact alarm region is large when a large scale structure is monitored and the number of PZTs is limited which increases the time and cost of damage inspections. To solve the two problems, an impact alarm region imaging and localization method based on digital sequences and time reversal is proposed. In this method, the frequency band of impact response signals is estimated based on the digital sequences first. Then, characteristic signals of impact response signals are constructed by sinusoidal modulation signals. Finally, the phase synthesis time reversal impact imaging method is adopted to obtain the impact region image. Depending on the image, an error ellipse is generated to give out the final impact alarm region. A validation experiment is implemented on a complex composite wing box of a real aircraft. The validation results show that the accuracy rate of impact alarm region localization is approximately 100%. The area of impact alarm region can be reduced and the number of PZTs needed to cover the same impact monitoring region is reduced by more than a half. PMID:24084123

Comparison of manual and semi-automated delineation of regions of interest for radioligand PET imaging analysis

International Nuclear Information System (INIS)

Chow, Tiffany W; Verhoeff, Nicolaas PLG; Takeshita, Shinichiro; Honjo, Kie; Pataky, Christina E; St Jacques, Peggy L; Kusano, Maggie L; Caldwell, Curtis B; Ramirez, Joel; Black, Sandra

2007-01-01

As imaging centers produce higher resolution research scans, the number of man-hours required to process regional data has become a major concern. Comparison of automated vs. manual methodology has not been reported for functional imaging. We explored validation of using automation to delineate regions of interest on positron emission tomography (PET) scans. The purpose of this study was to ascertain improvements in image processing time and reproducibility of a semi-automated brain region extraction (SABRE) method over manual delineation of regions of interest (ROIs). We compared 2 sets of partial volume corrected serotonin 1a receptor binding potentials (BPs) resulting from manual vs. semi-automated methods. BPs were obtained from subjects meeting consensus criteria for frontotemporal degeneration and from age- and gender-matched healthy controls. Two trained raters provided each set of data to conduct comparisons of inter-rater mean image processing time, rank order of BPs for 9 PET scans, intra- and inter-rater intraclass correlation coefficients (ICC), repeatability coefficients (RC), percentages of the average parameter value (RM%), and effect sizes of either method. SABRE saved approximately 3 hours of processing time per PET subject over manual delineation (p < .001). Quality of the SABRE BP results was preserved relative to the rank order of subjects by manual methods. Intra- and inter-rater ICC were high (>0.8) for both methods. RC and RM% were lower for the manual method across all ROIs, indicating less intra-rater variance across PET subjects' BPs. SABRE demonstrated significant time savings and no significant difference in reproducibility over manual methods, justifying the use of SABRE in serotonin 1a receptor radioligand PET imaging analysis. This implies that semi-automated ROI delineation is a valid methodology for future PET imaging analysis

A region-based segmentation method for ultrasound images in HIFU therapy

International Nuclear Information System (INIS)

Zhang, Dong; Liu, Yu; Yang, Yan; Xu, Menglong; Yan, Yu; Qin, Qianqing

2016-01-01

Purpose: Precisely and efficiently locating a tumor with less manual intervention in ultrasound-guided high-intensity focused ultrasound (HIFU) therapy is one of the keys to guaranteeing the therapeutic result and improving the efficiency of the treatment. The segmentation of ultrasound images has always been difficult due to the influences of speckle, acoustic shadows, and signal attenuation as well as the variety of tumor appearance. The quality of HIFU guidance images is even poorer than that of conventional diagnostic ultrasound images because the ultrasonic probe used for HIFU guidance usually obtains images without making contact with the patient’s body. Therefore, the segmentation becomes more difficult. To solve the segmentation problem of ultrasound guidance image in the treatment planning procedure for HIFU therapy, a novel region-based segmentation method for uterine fibroids in HIFU guidance images is proposed. Methods: Tumor partitioning in HIFU guidance image without manual intervention is achieved by a region-based split-and-merge framework. A new iterative multiple region growing algorithm is proposed to first split the image into homogenous regions (superpixels). The features extracted within these homogenous regions will be more stable than those extracted within the conventional neighborhood of a pixel. The split regions are then merged by a superpixel-based adaptive spectral clustering algorithm. To ensure the superpixels that belong to the same tumor can be clustered together in the merging process, a particular construction strategy for the similarity matrix is adopted for the spectral clustering, and the similarity matrix is constructed by taking advantage of a combination of specifically selected first-order and second-order texture features computed from the gray levels and the gray level co-occurrence matrixes, respectively. The tumor region is picked out automatically from the background regions by an algorithm according to a priori

A region-based segmentation method for ultrasound images in HIFU therapy

Energy Technology Data Exchange (ETDEWEB)

Zhang, Dong, E-mail: dongz@whu.edu.cn; Liu, Yu; Yang, Yan; Xu, Menglong; Yan, Yu [School of Physics and Technology, Wuhan University, Wuhan 430072 (China); Qin, Qianqing [State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072 (China)

2016-06-15

Purpose: Precisely and efficiently locating a tumor with less manual intervention in ultrasound-guided high-intensity focused ultrasound (HIFU) therapy is one of the keys to guaranteeing the therapeutic result and improving the efficiency of the treatment. The segmentation of ultrasound images has always been difficult due to the influences of speckle, acoustic shadows, and signal attenuation as well as the variety of tumor appearance. The quality of HIFU guidance images is even poorer than that of conventional diagnostic ultrasound images because the ultrasonic probe used for HIFU guidance usually obtains images without making contact with the patient’s body. Therefore, the segmentation becomes more difficult. To solve the segmentation problem of ultrasound guidance image in the treatment planning procedure for HIFU therapy, a novel region-based segmentation method for uterine fibroids in HIFU guidance images is proposed. Methods: Tumor partitioning in HIFU guidance image without manual intervention is achieved by a region-based split-and-merge framework. A new iterative multiple region growing algorithm is proposed to first split the image into homogenous regions (superpixels). The features extracted within these homogenous regions will be more stable than those extracted within the conventional neighborhood of a pixel. The split regions are then merged by a superpixel-based adaptive spectral clustering algorithm. To ensure the superpixels that belong to the same tumor can be clustered together in the merging process, a particular construction strategy for the similarity matrix is adopted for the spectral clustering, and the similarity matrix is constructed by taking advantage of a combination of specifically selected first-order and second-order texture features computed from the gray levels and the gray level co-occurrence matrixes, respectively. The tumor region is picked out automatically from the background regions by an algorithm according to a priori

M-Arctan estimator based on the trust-region method

Energy Technology Data Exchange (ETDEWEB)

Hassaine, Yacine; Delourme, Benoit; Panciatici, Patrick [Gestionnaire du Reseau de Transport d Electricite Departement Methodes et appui Immeuble Le Colbert 9, Versailles Cedex (France); Walter, Eric [Laboratoire des signaux et systemes (L2S) Supelec, Gif-sur-Yvette (France)

2006-11-15

In this paper a new approach is proposed to increase the robustness of the classical L{sub 2}-norm state estimation. To achieve this task a new formulation of the Levemberg-Marquardt algorithm based on the trust-region method is applied to a new M-estimator, which we called M-Arctan. Results obtained on IEEE networks up to 300 buses are presented. (author)

Evaluating Interest in Acids-Bases: Development of an Acid-Base Interest Scale (ABIS) and Assessment of Pre-Service Science Teachers' Interest

Science.gov (United States)

Çiçek, Ö.; Ilhan, N.

2017-01-01

Students are more likely to be successful in topics they are interested in than others. This study aims to develop an Acid-Base Interest Scale (ABIS) and subsequently evaluate the interest of pre-service science teachers in acids-bases according to gender, years at the university, type of high school the pre-service science teachers attended, and…

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.

Analysis of iterative region-of-interest image reconstruction for x-ray computed tomography

Science.gov (United States)

Sidky, Emil Y.; Kraemer, David N.; Roth, Erin G.; Ullberg, Christer; Reiser, Ingrid S.; Pan, Xiaochuan

2014-01-01

Abstract. One of the challenges for iterative image reconstruction (IIR) is that such algorithms solve an imaging model implicitly, requiring a complete representation of the scanned subject within the viewing domain of the scanner. This requirement can place a prohibitively high computational burden for IIR applied to x-ray computed tomography (CT), especially when high-resolution tomographic volumes are required. In this work, we aim to develop an IIR algorithm for direct region-of-interest (ROI) image reconstruction. The proposed class of IIR algorithms is based on an optimization problem that incorporates a data fidelity term, which compares a derivative of the estimated data with the available projection data. In order to characterize this optimization problem, we apply it to computer-simulated two-dimensional fan-beam CT data, using both ideal noiseless data and realistic data containing a level of noise comparable to that of the breast CT application. The proposed method is demonstrated for both complete field-of-view and ROI imaging. To demonstrate the potential utility of the proposed ROI imaging method, it is applied to actual CT scanner data. PMID:25685824

Optimization of Bayesian Emission tomographic reconstruction for region of interest quantitation

International Nuclear Information System (INIS)

Qi, Jinyi

2003-01-01

Region of interest (ROI) quantitation is an important task in emission tomography (e.g., positron emission tomography and single photon emission computed tomography). It is essential for exploring clinical factors such as tumor activity, growth rate, and the efficacy of therapeutic interventions. Bayesian methods based on the maximum a posteriori principle (or called penalized maximum likelihood methods) have been developed for emission image reconstructions to deal with the low signal to noise ratio of the emission data. Similar to the filter cut-off frequency in the filtered backprojection method, the smoothing parameter of the image prior in Bayesian reconstruction controls the resolution and noise trade-off and hence affects ROI quantitation. In this paper we present an approach for choosing the optimum smoothing parameter in Bayesian reconstruction for ROI quantitation. Bayesian reconstructions are difficult to analyze because the resolution and noise properties are nonlinear and object-dependent. Building on the recent progress on deriving the approximate expressions for the local impulse response function and the covariance matrix, we derived simplied theoretical expressions for the bias, the variance, and the ensemble mean squared error (EMSE) of the ROI quantitation. One problem in evaluating ROI quantitation is that the truth is often required for calculating the bias. This is overcome by using ensemble distribution of the activity inside the ROI and computing the average EMSE. The resulting expressions allow fast evaluation of the image quality for different smoothing parameters. The optimum smoothing parameter of the image prior can then be selected to minimize the EMSE

The Persian Gulf Region as a Field of China’s Geopolitical Interests

Directory of Open Access Journals (Sweden)

M F Ilminskaya

2015-12-01

Full Text Available The article analyzes the political situation in the Gulf region in the light of China’s vital interests. Particular attention is paid to Chinese energy diplomacy, mechanisms for bilateral and multilateral cooperation, the Chinese project that is expected to revive the «Great Silk Road» and the priority areas of Chinese energy security. The author considers China as the largest world energy consumer whose economy is directly dependent on oil supplies, primarily from the Persian Gulf region. The article also analyzes the reasons of acute energy shortages in China and its growing interest in the Gulf region. The author reveals strategic significance of such important water transport arteries, as Straits of Hormuz and Malacca, touches on the issue of global players’ competition over ownership and control of hydrocarbons. The article focuses on flexibility of Chinese diplomacy and foreign policy maneuvering techniques in the region, successfully applied by Beijing to maximize the benefits for the implementation of its own national interests.

A watershed-based method for environmental vulnerability assessment with a case study of the Mid-Atlantic region

Energy Technology Data Exchange (ETDEWEB)

Tran, Liem T., E-mail: ltran1@utk.edu [Department of Geography, University of Tennessee, Knoxville, TN (United States); O& #x27; Neill, Robert V. [OTIE and Associates, Oak Ridge, TN (United States); Smith, Elizabeth R. [U.S. Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, Research Triangle Park, NC (United States)

2012-04-15

The paper presents a method for environmental vulnerability assessment with a case study of the Mid-Atlantic region. The method is based on the concept of 'self-/peer-appraisal' of a watershed in term of vulnerability. The self-/peer-appraisal process is facilitated by two separate linear optimization programs. The analysis provided insights on the environmental conditions, in general, and the relative vulnerability pattern, in particular, of the Mid-Atlantic region. The suggested method offers a simple but effective and objective way to perform a regional environmental vulnerability assessment. Consequently the method can be used in various steps in environmental assessment and planning. - Highlights: Black-Right-Pointing-Pointer We present a method for regional environmental vulnerability assessment. Black-Right-Pointing-Pointer It is based on the self-/peer-appraisal concept in term of vulnerability. Black-Right-Pointing-Pointer The analysis is facilitated by two separate linear optimization programs. Black-Right-Pointing-Pointer The method provides insights on the regional relative vulnerability pattern.

75 FR 20810 - Proposed Information Collection; Comment Request; Statement of Financial Interests, Regional...

Science.gov (United States)

2010-04-21

... Collection; Comment Request; Statement of Financial Interests, Regional Fishery Management Councils AGENCY... must provide an update of their statements at any time any such financial interest is acquired, or... financial interest in any Council fishery. These interests include harvesting, processing, lobbying...

MRI-determined liver proton density fat fraction, with MRS validation: Comparison of regions of interest sampling methods in patients with type 2 diabetes.

Science.gov (United States)

Vu, Kim-Nhien; Gilbert, Guillaume; Chalut, Marianne; Chagnon, Miguel; Chartrand, Gabriel; Tang, An

2016-05-01

To assess the agreement between published magnetic resonance imaging (MRI)-based regions of interest (ROI) sampling methods using liver mean proton density fat fraction (PDFF) as the reference standard. This retrospective, internal review board-approved study was conducted in 35 patients with type 2 diabetes. Liver PDFF was measured by magnetic resonance spectroscopy (MRS) using a stimulated-echo acquisition mode sequence and MRI using a multiecho spoiled gradient-recalled echo sequence at 3.0T. ROI sampling methods reported in the literature were reproduced and liver mean PDFF obtained by whole-liver segmentation was used as the reference standard. Intraclass correlation coefficients (ICCs), Bland-Altman analysis, repeated-measures analysis of variance (ANOVA), and paired t-tests were performed. ICC between MRS and MRI-PDFF was 0.916. Bland-Altman analysis showed excellent intermethod agreement with a bias of -1.5 ± 2.8%. The repeated-measures ANOVA found no systematic variation of PDFF among the nine liver segments. The correlation between liver mean PDFF and ROI sampling methods was very good to excellent (0.873 to 0.975). Paired t-tests revealed significant differences (P sampling methods that exclusively or predominantly sampled the right lobe. Significant correlations with mean PDFF were found with sampling methods that included higher number of segments, total area equal or larger than 5 cm(2) , or sampled both lobes (P = 0.001, 0.023, and 0.002, respectively). MRI-PDFF quantification methods should sample each liver segment in both lobes and include a total surface area equal or larger than 5 cm(2) to provide a close estimate of the liver mean PDFF. © 2015 Wiley Periodicals, Inc.

MR-based automatic delineation of volumes of interest in human brain PET images using probability maps

DEFF Research Database (Denmark)

Svarer, Claus; Madsen, Karina; Hasselbalch, Steen G.

2005-01-01

The purpose of this study was to develop and validate an observer-independent approach for automatic generation of volume-of-interest (VOI) brain templates to be used in emission tomography studies of the brain. The method utilizes a VOI probability map created on the basis of a database of several...... delineation of the VOI set. The approach was also shown to work equally well in individuals with pronounced cerebral atrophy. Probability-map-based automatic delineation of VOIs is a fast, objective, reproducible, and safe way to assess regional brain values from PET or SPECT scans. In addition, the method...

AN ALGORITHM TO DETECT THE RETINAL REGION OF INTEREST

Directory of Open Access Journals (Sweden)

E. Şehirli

2017-11-01

Full Text Available Retina is one of the important layers of the eyes, which includes sensitive cells to colour and light and nerve fibers. Retina can be displayed by using some medical devices such as fundus camera, ophthalmoscope. Hence, some lesions like microaneurysm, haemorrhage, exudate with many diseases of the eye can be detected by looking at the images taken by devices. In computer vision and biomedical areas, studies to detect lesions of the eyes automatically have been done for a long time. In order to make automated detections, the concept of ROI may be utilized. ROI which stands for region of interest generally serves the purpose of focusing on particular targets. The main concentration of this paper is the algorithm to automatically detect retinal region of interest belonging to different retinal images on a software application. The algorithm consists of three stages such as pre-processing stage, detecting ROI on processed images and overlapping between input image and obtained ROI of the image.

An Algorithm to Detect the Retinal Region of Interest

Science.gov (United States)

Şehirli, E.; Turan, M. K.; Demiral, E.

2017-11-01

Retina is one of the important layers of the eyes, which includes sensitive cells to colour and light and nerve fibers. Retina can be displayed by using some medical devices such as fundus camera, ophthalmoscope. Hence, some lesions like microaneurysm, haemorrhage, exudate with many diseases of the eye can be detected by looking at the images taken by devices. In computer vision and biomedical areas, studies to detect lesions of the eyes automatically have been done for a long time. In order to make automated detections, the concept of ROI may be utilized. ROI which stands for region of interest generally serves the purpose of focusing on particular targets. The main concentration of this paper is the algorithm to automatically detect retinal region of interest belonging to different retinal images on a software application. The algorithm consists of three stages such as pre-processing stage, detecting ROI on processed images and overlapping between input image and obtained ROI of the image.

Half-Fan-Based Intensity-Weighted Region-of-Interest Imaging for Low-Dose Cone-Beam CT in Image-Guided Radiation Therapy.

Science.gov (United States)

Yoo, Boyeol; Son, Kihong; Pua, Rizza; Kim, Jinsung; Solodov, Alexander; Cho, Seungryong

2016-10-01

With the increased use of computed tomography (CT) in clinics, dose reduction is the most important feature people seek when considering new CT techniques or applications. We developed an intensity-weighted region-of-interest (IWROI) imaging method in an exact half-fan geometry to reduce the imaging radiation dose to patients in cone-beam CT (CBCT) for image-guided radiation therapy (IGRT). While dose reduction is highly desirable, preserving the high-quality images of the ROI is also important for target localization in IGRT. An intensity-weighting (IW) filter made of copper was mounted in place of a bowtie filter on the X-ray tube unit of an on-board imager (OBI) system such that the filter can substantially reduce radiation exposure to the outer ROI. In addition to mounting the IW filter, the lead-blade collimation of the OBI was adjusted to produce an exact half-fan scanning geometry for a further reduction of the radiation dose. The chord-based rebinned backprojection-filtration (BPF) algorithm in circular CBCT was implemented for image reconstruction, and a humanoid pelvis phantom was used for the IWROI imaging experiment. The IWROI image of the phantom was successfully reconstructed after beam-quality correction, and it was registered to the reference image within an acceptable level of tolerance. Dosimetric measurements revealed that the dose is reduced by approximately 61% in the inner ROI and by 73% in the outer ROI compared to the conventional bowtie filter-based half-fan scan. The IWROI method substantially reduces the imaging radiation dose and provides reconstructed images with an acceptable level of quality for patient setup and target localization. The proposed half-fan-based IWROI imaging technique can add a valuable option to CBCT in IGRT applications.

First clinical experience with a multiple region of interest registration and correction method in radiotherapy of head-and-neck cancer patients

International Nuclear Information System (INIS)

Beek, Suzanne van; Kranen, Simon van; Mencarelli, Angelo; Remeijer, Peter; Rasch, Coen; Herk, Marcel van; Sonke, Jan-Jakob

2010-01-01

Purpose: To discuss the first clinical experience with a multiple region of interest (mROI) registration and correction method for high-precision radiotherapy of head-and-neck cancer patients. Materials and methods: 12-13 3D rectangular-shaped ROIs were automatically placed around bony structures on the planning CT scans (n = 50 patients) which were individually registered to subsequent CBCT scans. mROI registration was used to quantify global and local setup errors. The time required to perform the mROI registration was compared with that of a previously used single-ROI method. The number of scans with residual local setup error exceeding 5 mm/5 deg. (warnings) was scored together with the frequency ROIs exceeding these limits for three or more consecutive imaging fractions (systematic errors). Results: In 40% of the CBCT scans, one or more ROI-registrations exceeded the 5 mm/5 deg.. Most warnings were seen in ROI 'hyoid', 31% of the rotation warnings and 14% of the translation warnings. Systematic errors lead to 52 consults of the treating physician. The preparation and registration time was similar for both registration methods. Conclusions: The mROI registration method is easy to use with little extra workload, provides additional information on local setup errors, and helps to select patients for re-planning.

Novel region of interest interrogation technique for diffusion tensor imaging analysis in the canine brain.

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Li, Jonathan Y; Middleton, Dana M; Chen, Steven; White, Leonard; Ellinwood, N Matthew; Dickson, Patricia; Vite, Charles; Bradbury, Allison; Provenzale, James M

2017-08-01

Purpose We describe a novel technique for measuring diffusion tensor imaging metrics in the canine brain. We hypothesized that a standard method for region of interest placement could be developed that is highly reproducible, with less than 10% difference in measurements between raters. Methods Two sets of canine brains (three seven-week-old full-brains and two 17-week-old single hemispheres) were scanned ex-vivo on a 7T small-animal magnetic resonance imaging system. Strict region of interest placement criteria were developed and then used by two raters to independently measure diffusion tensor imaging metrics within four different white-matter regions within each specimen. Average values of fractional anisotropy, radial diffusivity, and the three eigenvalues (λ1, λ2, and λ3) within each region in each specimen overall and within each individual image slice were compared between raters by calculating the percentage difference between raters for each metric. Results The mean percentage difference between raters for all diffusion tensor imaging metrics when pooled by each region and specimen was 1.44% (range: 0.01-5.17%). The mean percentage difference between raters for all diffusion tensor imaging metrics when compared by individual image slice was 2.23% (range: 0.75-4.58%) per hemisphere. Conclusion Our results indicate that the technique described is highly reproducible, even when applied to canine specimens of differing age, morphology, and image resolution. We propose this technique for future studies of diffusion tensor imaging analysis in canine brains and for cross-sectional and longitudinal studies of canine brain models of human central nervous system disease.

The ATLAS high level trigger region of interest builder

International Nuclear Information System (INIS)

Blair, R.; Dawson, J.; Drake, G.; Haberichter, W.; Schlereth, J.; Zhang, J.; Ermoline, Y.; Pope, B.; Aboline, M.; High Energy Physics; Michigan State Univ.

2008-01-01

This article describes the design, testing and production of the ATLAS Region of Interest Builder (RoIB). This device acts as an interface between the Level 1 trigger and the high level trigger (HLT) farm for the ATLAS LHC detector. It distributes all of the Level 1 data for a subset of events to a small number of (16 or less) individual commodity processors. These processors in turn provide this information to the HLT. This allows the HLT to use the Level 1 information to narrow data requests to areas of the detector where Level 1 has identified interesting objects

Quantification of carotid artery plaque stability with multiple region of interest based ultrasound strain indices and relationship with cognition

Science.gov (United States)

Meshram, N. H.; Varghese, T.; Mitchell, C. C.; Jackson, D. C.; Wilbrand, S. M.; Hermann, B. P.; Dempsey, R. J.

2017-08-01

Vulnerability and instability in carotid artery plaque has been assessed based on strain variations using noninvasive ultrasound imaging. We previously demonstrated that carotid plaques with higher strain indices in a region of interest (ROI) correlated to patients with lower cognition, probably due to cerebrovascular emboli arising from these unstable plaques. This work attempts to characterize the strain distribution throughout the entire plaque region instead of being restricted to a single localized ROI. Multiple ROIs are selected within the entire plaque region, based on thresholds determined by the maximum and average strains in the entire plaque, enabling generation of additional relevant strain indices. Ultrasound strain imaging of carotid plaques, was performed on 60 human patients using an 18L6 transducer coupled to a Siemens Acuson S2000 system to acquire radiofrequency data over several cardiac cycles. Patients also underwent a battery of neuropsychological tests under a protocol based on National Institute of Neurological Disorders and Stroke and Canadian Stroke Network guidelines. Correlation of strain indices with composite cognitive index of executive function revealed a negative association relating high strain to poor cognition. Patients grouped into high and low cognition groups were then classified using these additional strain indices. One of our newer indices, namely the average L  -  1 norm with plaque (AL1NWP) presented with significantly improved correlation with executive function when compared to our previously reported maximum accumulated strain indices. An optimal combination of three of the new indices generated classifiers of patient cognition with an area under the curve (AUC) of 0.880, 0.921 and 0.905 for all (n  =  60), symptomatic (n  =  33) and asymptomatic patients (n  =  27) whereas classifiers using maximum accumulated strain indices alone provided AUC values of 0.817, 0.815 and 0

Data assimilation method based on the constraints of confidence region

Science.gov (United States)

Li, Yong; Li, Siming; Sheng, Yao; Wang, Luheng

2018-03-01

The ensemble Kalman filter (EnKF) is a distinguished data assimilation method that is widely used and studied in various fields including methodology and oceanography. However, due to the limited sample size or imprecise dynamics model, it is usually easy for the forecast error variance to be underestimated, which further leads to the phenomenon of filter divergence. Additionally, the assimilation results of the initial stage are poor if the initial condition settings differ greatly from the true initial state. To address these problems, the variance inflation procedure is usually adopted. In this paper, we propose a new method based on the constraints of a confidence region constructed by the observations, called EnCR, to estimate the inflation parameter of the forecast error variance of the EnKF method. In the new method, the state estimate is more robust to both the inaccurate forecast models and initial condition settings. The new method is compared with other adaptive data assimilation methods in the Lorenz-63 and Lorenz-96 models under various model parameter settings. The simulation results show that the new method performs better than the competing methods.

Interesting Interest Points

DEFF Research Database (Denmark)

Aanæs, Henrik; Dahl, Anders Lindbjerg; Pedersen, Kim Steenstrup

2012-01-01

on spatial invariance of interest points under changing acquisition parameters by measuring the spatial recall rate. The scope of this paper is to investigate the performance of a number of existing well-established interest point detection methods. Automatic performance evaluation of interest points is hard......Not all interest points are equally interesting. The most valuable interest points lead to optimal performance of the computer vision method in which they are employed. But a measure of this kind will be dependent on the chosen vision application. We propose a more general performance measure based...... position. The LED illumination provides the option for artificially relighting the scene from a range of light directions. This data set has given us the ability to systematically evaluate the performance of a number of interest point detectors. The highlights of the conclusions are that the fixed scale...

Theoretical Study of Penalized-Likelihood Image Reconstruction for Region of Interest Quantification

International Nuclear Information System (INIS)

Qi, Jinyi; Huesman, Ronald H.

2006-01-01

Region of interest (ROI) quantification is an important task in emission tomography (e.g., positron emission tomography and single photon emission computed tomography). It is essential for exploring clinical factors such as tumor activity, growth rate, and the efficacy of therapeutic interventions. Statistical image reconstruction methods based on the penalized maximum-likelihood (PML) or maximum a posteriori principle have been developed for emission tomography to deal with the low signal-to-noise ratio of the emission data. Similar to the filter cut-off frequency in the filtered backprojection method, the regularization parameter in PML reconstruction controls the resolution and noise tradeoff and, hence, affects ROI quantification. In this paper, we theoretically analyze the performance of ROI quantification in PML reconstructions. Building on previous work, we derive simplified theoretical expressions for the bias, variance, and ensemble mean-squared-error (EMSE) of the estimated total activity in an ROI that is surrounded by a uniform background. When the mean and covariance matrix of the activity inside the ROI are known, the theoretical expressions are readily computable and allow for fast evaluation of image quality for ROI quantification with different regularization parameters. The optimum regularization parameter can then be selected to minimize the EMSE. Computer simulations are conducted for small ROIs with variable uniform uptake. The results show that the theoretical predictions match the Monte Carlo results reasonably well

A Method of Vector Map Multi-scale Representation Considering User Interest on Subdivision Gird

Directory of Open Access Journals (Sweden)

YU Tong

2016-12-01

Full Text Available Compared with the traditional spatial data model and method, global subdivision grid show a great advantage in the organization and expression of massive spatial data. In view of this, a method of vector map multi-scale representation considering user interest on subdivision gird is proposed. First, the spatial interest field is built using a large number POI data to describe the spatial distribution of the user interest in geographic information. Second, spatial factor is classified and graded, and its representation scale range can be determined. Finally, different levels of subdivision surfaces are divided based on GeoSOT subdivision theory, and the corresponding relation of subdivision level and scale is established. According to the user interest of subdivision surfaces, the spatial feature can be expressed in different degree of detail. It can realize multi-scale representation of spatial data based on user interest. The experimental results show that this method can not only satisfy general-to-detail and important-to-secondary space cognitive demands of users, but also achieve better multi-scale representation effect.

Region of interest methylation analysis: a comparison of MSP with MS-HRM and direct BSP.

Science.gov (United States)

Akika, Reem; Awada, Zainab; Mogharbil, Nahed; Zgheib, Nathalie K

2017-07-01

The aim of this study was to compare and contrast three DNA methylation methods of a specific region of interest (ROI): methylation-specific PCR (MSP), methylation-sensitive high resolution melting (MS-HRM) and direct bisulfite sequencing (BSP). The methylation of a CpG area in the promoter region of Estrogen receptor alpha (ESR1) was evaluated by these three methods with samples and standards of different methylation percentages. MSP data were neither reproducible nor sensitive, and the assay was not specific due to non-specific binding of primers. MS-HRM was highly reproducible and a step forward into categorizing the methylation status of the samples as percent ranges. Direct BSP was the most informative method regarding methylation percentage of each CpG site. Though not perfect, it was reproducible and sensitive. We recommend the use of either method depending on the research question and target amplicon, and provided that the designed primers and expected amplicons are within recommendations. If the research question targets a limited number of CpG sites and simple yes/no results are enough, MSP may be attempted. For short amplicons that are crowded with CpG sites and of single melting domain, MS-HRM may be the method of choice though it only indicates the overall methylation percentage of the entire amplicon. Although the assay is highly reproducible, being semi-quantitative makes it of lesser interest to study ROI methylation of samples with little methylation differences. Direct BSP is a step forward as it gives information about the methylation percentage at each CpG site.

Region of Interest Selection Interface for Wide-Angle Arthroscope

Directory of Open Access Journals (Sweden)

Jung Kyunghwa

2015-01-01

Full Text Available We have proposed a new interface for an wide-angle endoscope for solo surgery. The wide-angle arthroscopic view and magnified region of interest (ROI within the wide view were shown simultaneously. With a camera affixed to surgical instruments, the position of the ROI could be determined by manipulating the surgical instrument. Image features acquired by the A-KAZE approach were used to estimate the change of position of the surgical instrument by tracking the features every time the camera moved. We examined the accuracy of ROI selection using three different images, which were different-sized square arrays and tested phantom experiments. When the number of ROIs was twelve, the success rate was best, and the rate diminished as the size of ROIs decreased. The experimental results showed that the method of using a camera without additional sensors satisfied the appropriate accuracy required for ROI selection, and this interface was helpful in performing surgery with fewer assistants.

Human body region enhancement method based on Kinect infrared imaging

Science.gov (United States)

Yang, Lei; Fan, Yubo; Song, Xiaowei; Cai, Wenjing

2016-10-01

To effectively improve the low contrast of human body region in the infrared images, a combing method of several enhancement methods is utilized to enhance the human body region. Firstly, for the infrared images acquired by Kinect, in order to improve the overall contrast of the infrared images, an Optimal Contrast-Tone Mapping (OCTM) method with multi-iterations is applied to balance the contrast of low-luminosity infrared images. Secondly, to enhance the human body region better, a Level Set algorithm is employed to improve the contour edges of human body region. Finally, to further improve the human body region in infrared images, Laplacian Pyramid decomposition is adopted to enhance the contour-improved human body region. Meanwhile, the background area without human body region is processed by bilateral filtering to improve the overall effect. With theoretical analysis and experimental verification, the results show that the proposed method could effectively enhance the human body region of such infrared images.

A Regions of Confidence Based Approach to Enhance Segmentation with Shape Priors.

Science.gov (United States)

Appia, Vikram V; Ganapathy, Balaji; Abufadel, Amer; Yezzi, Anthony; Faber, Tracy

2010-01-18

We propose an improved region based segmentation model with shape priors that uses labels of confidence/interest to exclude the influence of certain regions in the image that may not provide useful information for segmentation. These could be regions in the image which are expected to have weak, missing or corrupt edges or they could be regions in the image which the user is not interested in segmenting, but are part of the object being segmented. In the training datasets, along with the manual segmentations we also generate an auxiliary map indicating these regions of low confidence/interest. Since, all the training images are acquired under similar conditions, we can train our algorithm to estimate these regions as well. Based on this training we will generate a map which indicates the regions in the image that are likely to contain no useful information for segmentation. We then use a parametric model to represent the segmenting curve as a combination of shape priors obtained by representing the training data as a collection of signed distance functions. We evolve an objective energy functional to evolve the global parameters that are used to represent the curve. We vary the influence each pixel has on the evolution of these parameters based on the confidence/interest label. When we use these labels to indicate the regions with low confidence; the regions containing accurate edges will have a dominant role in the evolution of the curve and the segmentation in the low confidence regions will be approximated based on the training data. Since our model evolves global parameters, it improves the segmentation even in the regions with accurate edges. This is because we eliminate the influence of the low confidence regions which may mislead the final segmentation. Similarly when we use the labels to indicate the regions which are not of importance, we will get a better segmentation of the object in the regions we are interested in.

APPLICATION OF LOGISTICS PRINCIPLES FOR THE PURPOSES OF INTEREST INCREASE IN THE SPIŠ REGION

Directory of Open Access Journals (Sweden)

Dominika Szabóová

2015-06-01

Full Text Available This article refers to the application of logistics principles for the purposes of interest increase in the Spiš region. The object of the research is the Spiš region, its structure and range of services. On the basis of system analysis results the recommendations were listed. Practical application of recommendations may increase the interest in the Spiš region and contribute to its development. Certain paragraph contains the time schedule and recommendation implementation costs. After practical application of selected recommendations their effectiveness was. Conclusions are contained in individual paragraph.

Multi-resolution analysis for region of interest extraction in thermographic nondestructive evaluation

Science.gov (United States)

Ortiz-Jaramillo, B.; Fandiño Toro, H. A.; Benitez-Restrepo, H. D.; Orjuela-Vargas, S. A.; Castellanos-Domínguez, G.; Philips, W.

2012-03-01

Infrared Non-Destructive Testing (INDT) is known as an effective and rapid method for nondestructive inspection. It can detect a broad range of near-surface structuring flaws in metallic and composite components. Those flaws are modeled as a smooth contour centered at peaks of stored thermal energy, termed Regions of Interest (ROI). Dedicated methodologies must detect the presence of those ROIs. In this paper, we present a methodology for ROI extraction in INDT tasks. The methodology deals with the difficulties due to the non-uniform heating. The non-uniform heating affects low spatial/frequencies and hinders the detection of relevant points in the image. In this paper, a methodology for ROI extraction in INDT using multi-resolution analysis is proposed, which is robust to ROI low contrast and non-uniform heating. The former methodology includes local correlation, Gaussian scale analysis and local edge detection. In this methodology local correlation between image and Gaussian window provides interest points related to ROIs. We use a Gaussian window because thermal behavior is well modeled by Gaussian smooth contours. Also, the Gaussian scale is used to analyze details in the image using multi-resolution analysis avoiding low contrast, non-uniform heating and selection of the Gaussian window size. Finally, local edge detection is used to provide a good estimation of the boundaries in the ROI. Thus, we provide a methodology for ROI extraction based on multi-resolution analysis that is better or equal compared with the other dedicate algorithms proposed in the state of art.

Validation of Simple Quantification Methods for (18)F-FP-CIT PET Using Automatic Delineation of Volumes of Interest Based on Statistical Probabilistic Anatomical Mapping and Isocontour Margin Setting.

Science.gov (United States)

Kim, Yong-Il; Im, Hyung-Jun; Paeng, Jin Chul; Lee, Jae Sung; Eo, Jae Seon; Kim, Dong Hyun; Kim, Euishin E; Kang, Keon Wook; Chung, June-Key; Lee, Dong Soo

2012-12-01

(18)F-FP-CIT positron emission tomography (PET) is an effective imaging for dopamine transporters. In usual clinical practice, (18)F-FP-CIT PET is analyzed visually or quantified using manual delineation of a volume of interest (VOI) for the striatum. In this study, we suggested and validated two simple quantitative methods based on automatic VOI delineation using statistical probabilistic anatomical mapping (SPAM) and isocontour margin setting. Seventy-five (18)F-FP-CIT PET images acquired in routine clinical practice were used for this study. A study-specific image template was made and the subject images were normalized to the template. Afterwards, uptakes in the striatal regions and cerebellum were quantified using probabilistic VOI based on SPAM. A quantitative parameter, QSPAM, was calculated to simulate binding potential. Additionally, the functional volume of each striatal region and its uptake were measured in automatically delineated VOI using isocontour margin setting. Uptake-volume product (QUVP) was calculated for each striatal region. QSPAM and QUVP were compared with visual grading and the influence of cerebral atrophy on the measurements was tested. Image analyses were successful in all the cases. Both the QSPAM and QUVP were significantly different according to visual grading (P Simple quantitative measurements of QSPAM and QUVP showed acceptable agreement with visual grading. Although QSPAM in some group may be influenced by cerebral atrophy, these simple methods are expected to be effective in the quantitative analysis of (18)F-FP-CIT PET in usual clinical practice.

Smoke regions extraction based on two steps segmentation and motion detection in early fire

Science.gov (United States)

Jian, Wenlin; Wu, Kaizhi; Yu, Zirong; Chen, Lijuan

2018-03-01

Aiming at the early problems of video-based smoke detection in fire video, this paper proposes a method to extract smoke suspected regions by combining two steps segmentation and motion characteristics. Early smoldering smoke can be seen as gray or gray-white regions. In the first stage, regions of interests (ROIs) with smoke are obtained by using two step segmentation methods. Then, suspected smoke regions are detected by combining the two step segmentation and motion detection. Finally, morphological processing is used for smoke regions extracting. The Otsu algorithm is used as segmentation method and the ViBe algorithm is used to detect the motion of smoke. The proposed method was tested on 6 test videos with smoke. The experimental results show the effectiveness of our proposed method over visual observation.

Treatment planning for prostate brachytherapy using region of interest adjoint functions and a greedy heuristic

International Nuclear Information System (INIS)

Yoo, Sua; Kowalok, Michael E; Thomadsen, Bruce R; Henderson, Douglass L

2003-01-01

We have developed an efficient treatment-planning algorithm for prostate implants that is based on region of interest (ROI) adjoint functions and a greedy heuristic. For this work, we define the adjoint function for an ROI as the sensitivity of the average dose in the ROI to a unit-strength brachytherapy source at any seed position. The greedy heuristic uses a ratio of target and critical structure adjoint functions to rank seed positions according to their ability to irradiate the target ROI while sparing critical structure ROIs. This ratio is computed once for each seed position prior to the optimization process. Optimization is performed by a greedy heuristic that selects seed positions according to their ratio values. With this method, clinically acceptable treatment plans are obtained in less than 2 s. For comparison, a branch-and-bound method to solve a mixed integer-programming model took more than 50 min to arrive at a feasible solution. Both methods achieved good treatment plans, but the speedup provided by the greedy heuristic was a factor of approximately 1500. This attribute makes this algorithm suitable for intra-operative real-time treatment planning

Interests and needs for participation in tourism among disabled from eastern regions of Poland.

Science.gov (United States)

Bergier, Barbara; Kubińska, Zofia; Bergier, Józef

2013-01-01

The scope of problems concerning the disabled still remains a constantly up-to-date social issue, which requires current scientific analysis. In concern for the disabled, the problem of physical activity through their participation in tourism occupies an important position. The studies concern the disabled from three regions: Lublin, Białystok and Rzeszów, where there occurs the highest intensity of the phenomenon of disability. The recognition of interests and needs manifested by the disabled from the eastern regions of Poland concerning the use of forms of tourism during leisure time. The method of a diagnostic survey and questionnaire technique were applied. A total number of 750 disabled were examined. The study showed that the majority of the disabled spend their free time devoted to tourist activity according to their needs. The main forms of participation in tourism are sightseeing tours and package holidays, and the respondents would like most to participate in rehabilitation camps and sightseeing tours. A considerable variation was observed in the participation in forms of tourism among the disabled from individual regions. The disabled who do not wish to participate in sports-recreation and tourist activities, and for whom their state of health is the main barrier, require special interest. A relatively large variation of tourism forms used by the disabled in individual regions indicate the need for an exchange of experiences between specialist facilities taking care of the disabled.

An improved principal component analysis based region matching method for fringe direction estimation

Science.gov (United States)

He, A.; Quan, C.

2018-04-01

The principal component analysis (PCA) and region matching combined method is effective for fringe direction estimation. However, its mask construction algorithm for region matching fails in some circumstances, and the algorithm for conversion of orientation to direction in mask areas is computationally-heavy and non-optimized. We propose an improved PCA based region matching method for the fringe direction estimation, which includes an improved and robust mask construction scheme, and a fast and optimized orientation-direction conversion algorithm for the mask areas. Along with the estimated fringe direction map, filtered fringe pattern by automatic selective reconstruction modification and enhanced fast empirical mode decomposition (ASRm-EFEMD) is used for Hilbert spiral transform (HST) to demodulate the phase. Subsequently, windowed Fourier ridge (WFR) method is used for the refinement of the phase. The robustness and effectiveness of proposed method are demonstrated by both simulated and experimental fringe patterns.

Apparatus and method for mapping an area of interest

Science.gov (United States)

Staab, Torsten A. Cohen, Daniel L.; Feller, Samuel [Fairfax, VA

2009-12-01

An apparatus and method are provided for mapping an area of interest using polar coordinates or Cartesian coordinates. The apparatus includes a range finder, an azimuth angle measuring device to provide a heading and an inclinometer to provide an angle of inclination of the range finder as it relates to primary reference points and points of interest. A computer is provided to receive signals from the range finder, inclinometer and azimuth angle measurer to record location data and calculate relative locations between one or more points of interest and one or more primary reference points. The method includes mapping of an area of interest to locate points of interest relative to one or more primary reference points and to store the information in the desired manner. The device may optionally also include an illuminator which can be utilized to paint the area of interest to indicate both points of interest and primary points of reference during and/or after data acquisition.

26 CFR 1.446-2 - Method of accounting for interest.

Science.gov (United States)

2010-04-01

... account by a taxpayer under the taxpayer's regular method of accounting (e.g., an accrual method or the... 26 Internal Revenue 6 2010-04-01 2010-04-01 false Method of accounting for interest. 1.446-2... TAX (CONTINUED) INCOME TAXES Methods of Accounting § 1.446-2 Method of accounting for interest. (a...

Detection of the spatial accuracy of an O-arm in the region of surgical interest

Science.gov (United States)

Koivukangas, Tapani; Katisko, Jani P. A.; Koivukangsa, John P.

2013-03-01

Medical imaging is an essential component of a wide range of surgical procedures1. For image guided surgical (IGS) procedures, medical images are the main source of information2. The IGS procedures rely largely on obtained image data, so the data needs to provide differentiation between normal and abnormal tissues, especially when other surgical guidance devices are used in the procedures. The image data also needs to provide accurate spatial representation of the patient3. This research has concentrated on the concept of accuracy assessment of IGS devices to meet the needs of quality assurance in the hospital environment. For this purpose, two precision engineered accuracy assessment phantoms have been developed as advanced materials and methods for the community. The phantoms were designed to mimic the volume of a human head as the common region of surgical interest (ROSI). This paper introduces the utilization of the phantoms in spatial accuracy assessment of a commercial surgical 3D CT scanner, the O-Arm. The study presents methods and results of image quality detection of possible geometrical distortions in the region of surgical interest. The results show that in the pre-determined ROSI there are clear image distortion and artefacts using too high imaging parameters when scanning the objects. On the other hand, when using optimal parameters, the O-Arm causes minimal error in IGS accuracy. The detected spatial inaccuracy of the O-Arm with used parameters was in the range of less than 1.00 mm.

Computerized detection of multiple sclerosis candidate regions based on a level set method using an artificial neural network

International Nuclear Information System (INIS)

Kuwazuru, Junpei; Magome, Taiki; Arimura, Hidetaka; Yamashita, Yasuo; Oki, Masafumi; Toyofuku, Fukai; Kakeda, Shingo; Yamamoto, Daisuke

2010-01-01

Yamamoto et al. developed the system for computer-aided detection of multiple sclerosis (MS) candidate regions. In a level set method in their proposed method, they employed the constant threshold value for the edge indicator function related to a speed function of the level set method. However, it would be appropriate to adjust the threshold value to each MS candidate region, because the edge magnitudes in MS candidates differ from each other. Our purpose of this study was to develop a computerized detection of MS candidate regions in MR images based on a level set method using an artificial neural network (ANN). To adjust the threshold value for the edge indicator function in the level set method to each true positive (TP) and false positive (FP) region, we constructed the ANN. The ANN could provide the suitable threshold value for each candidate region in the proposed level set method so that TP regions can be segmented and FP regions can be removed. Our proposed method detected MS regions at a sensitivity of 82.1% with 0.204 FPs per slice and similarity index of MS candidate regions was 0.717 on average. (author)

The Evolution of the Region of Interest Builder in the ATLAS Experiment

CERN Document Server

Blair, Robert; The ATLAS collaboration; Green, Barry; Love, Jeremy; Proudfoot, James; Rifki, Othmane; Panduro Vazquez, Jose Guillermo; Zhang, Jinlong

2015-01-01

ATLAS is a general purpose particle detector at the Large Hadron Collider (LHC) at CERN designed to measure the products of proton collisions. Given their high interaction rate (1GHz), selective triggering in real time is required to reduce the rate to the experiment’s data storage capacity (1KHz). To meet this requirement, ATLAS employs a combination of hardware and software triggers to select interesting collisions for physics analysis. The Region of Interest Builder (RoIB) is an integral part of the ATLAS detector Trigger and Data Acquisition (TDAQ) chain where the coordinates of the regions of interest (RoIs) identified by the first level trigger (L1) are collected and passed to the High Level Trigger (HLT) to make a decision. While the current custom RoIB operated reliably during the first run of the LHC, it is desirable to have the RoIB more operationally maintainable in the new run, which will reach higher luminosities with an increased complexity of L1 triggers. We are responsible for migrating the ...

Comparison between PET template-based method and MRI-based method for cortical quantification of florbetapir (AV-45) uptake in vivo

Energy Technology Data Exchange (ETDEWEB)

Saint-Aubert, L.; Nemmi, F.; Peran, P. [Inserm, Imagerie Cerebrale et Handicaps neurologiques UMR 825, Centre Hospitalier Universitaire de Toulouse, Toulouse (France); Centre Hospitalier Universitaire de Toulouse, Universite de Toulouse, UPS, Imagerie Cerebrale et Handicaps Neurologiques UMR 825, Toulouse (France); Barbeau, E.J. [Universite de Toulouse, UPS, Centre de Recherche Cerveau et Cognition, France, CNRS, CerCo, Toulouse (France); Service de Neurologie, Pole Neurosciences, Centre Hospitalier Universitaire de Toulouse, Toulouse (France); Payoux, P. [Inserm, Imagerie Cerebrale et Handicaps neurologiques UMR 825, Centre Hospitalier Universitaire de Toulouse, Toulouse (France); Centre Hospitalier Universitaire de Toulouse, Universite de Toulouse, UPS, Imagerie Cerebrale et Handicaps Neurologiques UMR 825, Toulouse (France); Service de Medecine Nucleaire, Pole Imagerie, Centre Hospitalier Universitaire de Toulouse, Toulouse (France); Chollet, F.; Pariente, J. [Inserm, Imagerie Cerebrale et Handicaps neurologiques UMR 825, Centre Hospitalier Universitaire de Toulouse, Toulouse (France); Centre Hospitalier Universitaire de Toulouse, Universite de Toulouse, UPS, Imagerie Cerebrale et Handicaps Neurologiques UMR 825, Toulouse (France); Service de Neurologie, Pole Neurosciences, Centre Hospitalier Universitaire de Toulouse, Toulouse (France)

2014-05-15

Florbetapir (AV-45) has been shown to be a reliable tool for assessing in vivo amyloid load in patients with Alzheimer's disease from the early stages. However, nonspecific white matter binding has been reported in healthy subjects as well as in patients with Alzheimer's disease. To avoid this issue, cortical quantification might increase the reliability of AV-45 PET analyses. In this study, we compared two quantification methods for AV-45 binding, a classical method relying on PET template registration (route 1), and a MRI-based method (route 2) for cortical quantification. We recruited 22 patients at the prodromal stage of Alzheimer's disease and 17 matched controls. AV-45 binding was assessed using both methods, and target-to-cerebellum mean global standard uptake values (SUVr) were obtained for each of them, together with SUVr in specific regions of interest. Quantification using the two routes was compared between the clinical groups (intragroup comparison), and between groups for each route (intergroup comparison). Discriminant analysis was performed. In the intragroup comparison, differences in uptake values were observed between route 1 and route 2 in both groups. In the intergroup comparison, AV-45 uptake was higher in patients than controls in all regions of interest using both methods, but the effect size of this difference was larger using route 2. In the discriminant analysis, route 2 showed a higher specificity (94.1 % versus 70.6 %), despite a lower sensitivity (77.3 % versus 86.4 %), and D-prime values were higher for route 2. These findings suggest that, although both quantification methods enabled patients at early stages of Alzheimer's disease to be well discriminated from controls, PET template-based quantification seems adequate for clinical use, while the MRI-based cortical quantification method led to greater intergroup differences and may be more suitable for use in current clinical research. (orig.)

Interest of LQAS method in a survey of HTLV-I infection in Benin (West Africa).

Science.gov (United States)

Houinato, Dismand; Preux, Pierre-Marie; Charriere, Bénédicte; Massit, Bruno; Avodé, Gilbert; Denis, François; Dumas, Michel; Boutros-Toni, Fernand; Salamon, Roger

2002-02-01

HTLV-I is heterogeneously distributed in Sub-Saharan Africa. Traditional survey methods as cluster sampling could provide information for a country or region of interest. However, they cannot identify small areas with higher prevalences of infection to help in the health policy planning. Identification of such areas could be done by a Lot Quality Assurance Sampling (LQAS) method, which is currently used in industry to identify a poor performance in assembly lines. The LQAS method was used in Atacora (Northern Benin) between March and May 1998 to identify areas with a HTLV-I seroprevalence higher than 4%. Sixty-five subjects were randomly selected in each of 36 communes (lots) of this department. Lots were classified as unacceptable when the sample contained at least one positive subject. The LQAS method identified 25 (69.4 %) communes with a prevalence higher than 4%. Using stratified sampling theory, the overall HTLV-I seroprevalence was 4.5% (95% CI: 3.6-5.4%). These data show the interest of LQAS method application under field conditions to detect clusters of infection.

Automatic detection of regions of interest in mammographic images

Science.gov (United States)

Cheng, Erkang; Ling, Haibin; Bakic, Predrag R.; Maidment, Andrew D. A.; Megalooikonomou, Vasileios

2011-03-01

This work is a part of our ongoing study aimed at comparing the topology of anatomical branching structures with the underlying image texture. Detection of regions of interest (ROIs) in clinical breast images serves as the first step in development of an automated system for image analysis and breast cancer diagnosis. In this paper, we have investigated machine learning approaches for the task of identifying ROIs with visible breast ductal trees in a given galactographic image. Specifically, we have developed boosting based framework using the AdaBoost algorithm in combination with Haar wavelet features for the ROI detection. Twenty-eight clinical galactograms with expert annotated ROIs were used for training. Positive samples were generated by resampling near the annotated ROIs, and negative samples were generated randomly by image decomposition. Each detected ROI candidate was given a confidences core. Candidate ROIs with spatial overlap were merged and their confidence scores combined. We have compared three strategies for elimination of false positives. The strategies differed in their approach to combining confidence scores by summation, averaging, or selecting the maximum score.. The strategies were compared based upon the spatial overlap with annotated ROIs. Using a 4-fold cross-validation with the annotated clinical galactographic images, the summation strategy showed the best performance with 75% detection rate. When combining the top two candidates, the selection of maximum score showed the best performance with 96% detection rate.

The implementation of interest-based entrepreneurship curriculum in the Theory of Economics course

Science.gov (United States)

Surjanti, J.; Nugrohoseno, D.; Budiono; Musfidah, H.

2018-01-01

College and university are educational institutions and they should be able to design entrepreneurship program in order to strengthen creativity and innovation. Potential grown-up citizens potential is the main problem of national development solved through the role of universities by reconstructing the curriculum based on 2016 Indonesian National Curriculum Framework. The interest of building entrepreneurship becomes the work of all elements which one of them is a university. Reconstructing interest-based entrepreneurship curriculum is the first step to construct characterized economic. Economics lecturers have a responsibility to develop the curriculum. This study aimed to explore the interest in entrepreneurship used to develop the contextual learning using problem-based learning (PBL) method that refers to Universitas Negeri Surabaya’s motto “Growing with character” and integrated into 2016 Indonesian National Curriculum Framework. This study was qualitative explorative. The subjects of the study are 86 students in their first semester. The objective of the study was curriculum development interest-based entrepreneurship in the theory of economics course. The results of the study showed that the interest-based entrepreneurship curriculum was able to reach the targeted learning outcome as well as to create a product in the culinary and services project in Wonorejo mangrove forest according to students’ interests.

Profile of Pre-Service Science Teachers Based on STEM Career Interest Survey

Science.gov (United States)

Winarno, N.; Widodo, A.; Rusdiana, D.; Rochintaniawati, D.; Afifah, R. M. A.

2017-09-01

This study aims to investigate the profile of pre-service science teachers based on STEM (Science, Technology, Engineering, and Mathematics) Career Interest Survey. The study uses descriptive survey method as the research design. Samples collected from 66 preservice science teachers in a university located in Bandung, Indonesia. The results of the study are the profile of pre-service science teachers based on STEM Career Interest Survey shows that the average number of career interest in the field of technology is 4.08, in science 3.80, mathematics 3.39 and engineering 3.30. Pre-service science teachers are found to have interests in the STEM career fields. This research is necessary as there are many instances of people choosing majors or studies that are not in accordance with their interests and talents. The recommendation of this study is to develop learning in pre-service science teachers by using STEM approach.

Synthesis method based on solution regions for planar four bar straight line linkages

International Nuclear Information System (INIS)

Lai Rong, Yin; Cong, Mao; Jian you, Han; Tong, Yang; Juan, Huang

2012-01-01

An analytical method for synthesizing and selecting desired four-bar straight line mechanisms based on solution regions is presented. Given two fixed pivots, the point position and direction of the target straight line, an infinite number of mechanism solutions can be produced by employing this method, both in the general case and all three special cases. Unifying the straight line direction and the displacement from the given point to the instant center into the same form with different angles as parameters, infinite mechanism solutions can be expressed with different solution region charts. The mechanism property graphs have been computed to enable the designers to find out the involved mechanism information more intuitively and avoid aimlessness in selecting optimal mechanisms

Multiple regions-of-interest analysis of setup uncertainties for head-and-neck cancer radiotherapy

International Nuclear Information System (INIS)

Zhang Lifei; Garden, Adam S.; Lo, Justin; Ang, K. Kian; Ahamad, Anesa; Morrison, William H.; Rosenthal, David I.; Chambers, Mark S.; Zhu, X. Ronald; Mohan, Radhe; Dong Lei

2006-01-01

Purpose: To analyze three-dimensional setup uncertainties for multiple regions of interest (ROIs) in head-and-neck region. Methods and Materials: In-room computed tomography (CT) scans were acquired using a CT-on-rails system for 14 patients. Three separate bony ROIs were defined: C2 and C6 vertebral bodies and the palatine process of the maxilla. Translational shifts of 3 ROIs were calculated relative to the marked isocenter on the immobilization mask. Results: The shifts for all 3 ROIs were highly correlated. However, noticeable differences on the order of 2-6 mm existed between any 2 ROIs, indicating the flexibility and/or rotational effect in the head-and-neck region. The palatine process of the maxilla had the smallest right-left shifts because of the tight lateral fit in the face mask, but the largest superior-inferior movement because of in-plane rotation and variations in jaw positions. The neck region (C6) had the largest right-left shifts. The positioning mouthpiece was found effective in reducing variations in the superior-inferior direction. There was no statistically significant improvement for using the S-board (8 out of 14 patients) vs. the short face mask. Conclusions: We found variability in setup corrections for different regions of head-and-neck anatomy. These relative positional variations should be considered when making setup corrections or designing treatment margins

A consumption-based, regional input-output analysis of greenhouse gas emissions and the carbon regional index

DEFF Research Database (Denmark)

Boyd, Britta; Mangalagiu, Diana; Straatman, Bas

2018-01-01

This paper presents a consumption-based method accounting for greenhouse gas emissions at regional level based on a multi-region input-output model. The method is based on regional consumption and includes imports and exports of emissions, factual emission developments, green investments as well...

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

International Nuclear Information System (INIS)

Weis, M.; Sommer, V.; Hagelstein, C.; Schoenberg, S.O.; Neff, K.W.; Zoellner, F.G.; Zahn, K.; Schaible, T.

2016-01-01

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.)

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.)

Single-shot full resolution region-of-interest (ROI) reconstruction in image plane digital holographic microscopy

Science.gov (United States)

Singh, Mandeep; Khare, Kedar

2018-05-01

We describe a numerical processing technique that allows single-shot region-of-interest (ROI) reconstruction in image plane digital holographic microscopy with full pixel resolution. The ROI reconstruction is modelled as an optimization problem where the cost function to be minimized consists of an L2-norm squared data fitting term and a modified Huber penalty term that are minimized alternately in an adaptive fashion. The technique can provide full pixel resolution complex-valued images of the selected ROI which is not possible to achieve with the commonly used Fourier transform method. The technique can facilitate holographic reconstruction of individual cells of interest from a large field-of-view digital holographic microscopy data. The complementary phase information in addition to the usual absorption information already available in the form of bright field microscopy can make the methodology attractive to the biomedical user community.

A method of identifying social structures in siting regions for deep geological repositories in Switzerland

International Nuclear Information System (INIS)

Brander, Simone

2010-09-01

Acceptance is a key element in the site selection process for deep geological repositories for high-level and low and intermediate-level radioactive waste in Switzerland. Participation requirements such as comprehensive negotiation issues and adequate resources have thus been defined by the Swiss Federal Office of Energy (SFOE). In 2008, on the basis of technical criteria Nagra (National Cooperative for the Disposal of Radioactive Waste) proposed several potential areas for deep geological repositories. The number of potential areas will be narrowed down within the next few years. All municipalities within the planning perimeter (the area in which surface facilities can be realised) are affected and form the siting region. In order to ensure that the local population have their say in the forthcoming discussions, regional participation bodies including all municipalities within a siting region are being set up by the SFOE. Regional participation ensures that local interests, needs and values are taken into account in the site selection process. Assembling the regional participation bodies is therefore of great importance. Before such bodies can be formed, however, the various interests, needs and values have to be identified, and special attention has to be paid to long-term interests of future generations, as well as to non-organised and under-represented interests. According to the concept of proportional representation, the interests, needs and values that are identified and weighted by the local population are to be represented in the regional participation procedure. The aim of this study is to share a method of mapping existing social structures in a defined geographical area. This involves a combination of an analysis of socio-economic statistical data and qualitative and quantitative social research methods

Improved quantification for local regions of interest in preclinical PET imaging

Science.gov (United States)

Cal-González, J.; Moore, S. C.; Park, M.-A.; Herraiz, J. L.; Vaquero, J. J.; Desco, M.; Udias, J. M.

2015-09-01

In Positron Emission Tomography, there are several causes of quantitative inaccuracy, such as partial volume or spillover effects. The impact of these effects is greater when using radionuclides that have a large positron range, e.g. 68Ga and 124I, which have been increasingly used in the clinic. We have implemented and evaluated a local projection algorithm (LPA), originally evaluated for SPECT, to compensate for both partial-volume and spillover effects in PET. This method is based on the use of a high-resolution CT or MR image, co-registered with a PET image, which permits a high-resolution segmentation of a few tissues within a volume of interest (VOI) centered on a region within which tissue-activity values need to be estimated. The additional boundary information is used to obtain improved activity estimates for each tissue within the VOI, by solving a simple inversion problem. We implemented this algorithm for the preclinical Argus PET/CT scanner and assessed its performance using the radionuclides 18F, 68Ga and 124I. We also evaluated and compared the results obtained when it was applied during the iterative reconstruction, as well as after the reconstruction as a postprocessing procedure. In addition, we studied how LPA can help to reduce the ‘spillover contamination’, which causes inaccurate quantification of lesions in the immediate neighborhood of large, ‘hot’ sources. Quantification was significantly improved by using LPA, which provided more accurate ratios of lesion-to-background activity concentration for hot and cold regions. For 18F, the contrast was improved from 3.0 to 4.0 in hot lesions (when the true ratio was 4.0) and from 0.16 to 0.06 in cold lesions (true ratio  =  0.0), when using the LPA postprocessing. Furthermore, activity values estimated within the VOI using LPA during reconstruction were slightly more accurate than those obtained by post-processing, while also visually improving the image contrast and uniformity

Region-of-interest reconstruction for a cone-beam dental CT with a circular trajectory

International Nuclear Information System (INIS)

Hu, Zhanli; Zou, Jing; Gui, Jianbao; Zheng, Hairong; Xia, Dan

2013-01-01

Dental CT is the most appropriate and accurate device for preoperative evaluation of dental implantation. It can demonstrate the quantity of bone in three dimensions (3D), the location of important adjacent anatomic structures and the quality of available bone with minimal geometric distortion. Nevertheless, with the rapid increase of dental CT examinations, we are facing the problem of dose reduction without loss of image quality. In this work, backprojection-filtration (BPF) and Feldkamp–Davis–Kress (FDK) algorithm was applied to reconstruct the 3D full image and region-of-interest (ROI) image from complete and truncated circular cone-beam data respectively by computer-simulation. In addition, the BPF algorithm was evaluated based on the 3D ROI-image reconstruction from real data, which was acquired from our developed circular cone-beam prototype dental CT system. The results demonstrated that the ROI-image quality reconstructed from truncated data using the BPF algorithm was comparable to that reconstructed from complete data. The FDK algorithm, however, created artifacts while reconstructing ROI-image. Thus it can be seen, for circular cone-beam dental CT, reducing scanning angular range of the BPF algorithm used for ROI-image reconstruction are helpful for reducing the radiation dose and scanning time. Finally, an analytical method was developed for estimation of the ROI projection area on the detector before CT scanning, which would help doctors to roughly estimate the total radiation dose before the CT examination. -- Highlights: ► BPF algorithm was applied by using dental CT for the first time. ► A method was developed for estimation of projection region before CT scanning. ► Roughly predict the total radiation dose before CT scans. ► Potential reduce imaging radiation dose, scatter, and scanning time

Regions of micro-calcifications clusters detection based on new features from imbalance data in mammograms

Science.gov (United States)

Wang, Keju; Dong, Min; Yang, Zhen; Guo, Yanan; Ma, Yide

2017-02-01

Breast cancer is the most common cancer among women. Micro-calcification cluster on X-ray mammogram is one of the most important abnormalities, and it is effective for early cancer detection. Surrounding Region Dependence Method (SRDM), a statistical texture analysis method is applied for detecting Regions of Interest (ROIs) containing microcalcifications. Inspired by the SRDM, we present a method that extract gray and other features which are effective to predict the positive and negative regions of micro-calcifications clusters in mammogram. By constructing a set of artificial images only containing micro-calcifications, we locate the suspicious pixels of calcifications of a SRDM matrix in original image map. Features are extracted based on these pixels for imbalance date and then the repeated random subsampling method and Random Forest (RF) classifier are used for classification. True Positive (TP) rate and False Positive (FP) can reflect how the result will be. The TP rate is 90% and FP rate is 88.8% when the threshold q is 10. We draw the Receiver Operating Characteristic (ROC) curve and the Area Under the ROC Curve (AUC) value reaches 0.9224. The experiment indicates that our method is effective. A novel regions of micro-calcifications clusters detection method is developed, which is based on new features for imbalance data in mammography, and it can be considered to help improving the accuracy of computer aided diagnosis breast cancer.

Lagrangian based methods for coherent structure detection

Energy Technology Data Exchange (ETDEWEB)

Allshouse, Michael R., E-mail: mallshouse@chaos.utexas.edu [Center for Nonlinear Dynamics and Department of Physics, University of Texas at Austin, Austin, Texas 78712 (United States); Peacock, Thomas, E-mail: tomp@mit.edu [Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States)

2015-09-15

There has been a proliferation in the development of Lagrangian analytical methods for detecting coherent structures in fluid flow transport, yielding a variety of qualitatively different approaches. We present a review of four approaches and demonstrate the utility of these methods via their application to the same sample analytic model, the canonical double-gyre flow, highlighting the pros and cons of each approach. Two of the methods, the geometric and probabilistic approaches, are well established and require velocity field data over the time interval of interest to identify particularly important material lines and surfaces, and influential regions, respectively. The other two approaches, implementing tools from cluster and braid theory, seek coherent structures based on limited trajectory data, attempting to partition the flow transport into distinct regions. All four of these approaches share the common trait that they are objective methods, meaning that their results do not depend on the frame of reference used. For each method, we also present a number of example applications ranging from blood flow and chemical reactions to ocean and atmospheric flows.

A novel method to remove GPR background noise based on the similarity of non-neighboring regions

Science.gov (United States)

Montiel-Zafra, V.; Canadas-Quesada, F. J.; Vera-Candeas, P.; Ruiz-Reyes, N.; Rey, J.; Martinez, J.

2017-09-01

Ground penetrating radar (GPR) is a non-destructive technique that has been widely used in many areas of research, such as landmine detection or subsurface anomalies, where it is required to locate targets embedded within a background medium. One of the major challenges in the research of GPR data remains the improvement of the image quality of stone materials by means of detection of true anisotropies since most of the errors are caused by an incorrect interpretation by the users. However, it is complicated due to the interference of the horizontal background noise, e.g., the air-ground interface, that reduces the high-resolution quality of radargrams. Thus, weak or deep anisotropies are often masked by this type of noise. In order to remove the background noise obtained by GPR, this work proposes a novel background removal method assuming that the horizontal noise shows repetitive two-dimensional regions along the movement of the GPR antenna. Specifically, the proposed method, based on the non-local similarity of regions over the distance, computes similarities between different regions of the same depth in order to identify most repetitive regions using a criterion to avoid closer regions. Evaluations are performed using a set of synthetic and real GPR data. Experimental results show that the proposed method obtains promising results compared to the classic background removal techniques and the most recently published background removal methods.

Testing of Haar-Like Feature in Region of Interest Detection for Automated Target Recognition (ATR) System

Science.gov (United States)

Zhang, Yuhan; Lu, Dr. Thomas

2010-01-01

The objectives of this project were to develop a ROI (Region of Interest) detector using Haar-like feature similar to the face detection in Intel's OpenCV library, implement it in Matlab code, and test the performance of the new ROI detector against the existing ROI detector that uses Optimal Trade-off Maximum Average Correlation Height filter (OTMACH). The ROI detector included 3 parts: 1, Automated Haar-like feature selection in finding a small set of the most relevant Haar-like features for detecting ROIs that contained a target. 2, Having the small set of Haar-like features from the last step, a neural network needed to be trained to recognize ROIs with targets by taking the Haar-like features as inputs. 3, using the trained neural network from the last step, a filtering method needed to be developed to process the neural network responses into a small set of regions of interests. This needed to be coded in Matlab. All the 3 parts needed to be coded in Matlab. The parameters in the detector needed to be trained by machine learning and tested with specific datasets. Since OpenCV library and Haar-like feature were not available in Matlab, the Haar-like feature calculation needed to be implemented in Matlab. The codes for Adaptive Boosting and max/min filters in Matlab could to be found from the Internet but needed to be integrated to serve the purpose of this project. The performance of the new detector was tested by comparing the accuracy and the speed of the new detector against the existing OTMACH detector. The speed was referred as the average speed to find the regions of interests in an image. The accuracy was measured by the number of false positives (false alarms) at the same detection rate between the two detectors.

Coordination of Regional Structures’ Interests Concerning Investment Resources of Educational Services of Enterprises under High-Risk Conditions

Directory of Open Access Journals (Sweden)

Semchuk Zhanna V.

2016-02-01

Full Text Available The development of professional education in the context of interaction with the labor market has been analyzed and inconsistencies of professional and economic nature have been revealed. Reasons for the imbalance in the structure of the market for labor and education have been identified, and it was noted that they have a negative impact on the economic security of educational institutions and cause the accumulation of negative factors as well. Elements of foreign experience in forecasting economic development and associated with it changes in educational services with regard to high-risk conditions have been considered for the purpose of its application in Ukraine. A conceptual model of information technology for coordination of regional structures’ interests concerning investment resources of educational services of enterprises under high-risk conditions has been proposed. The information technology is based on the econometric model for optimizing enterprise Internet payment systems, criterion of hierarchical games theories, multiobjective optimization, active systems, the model for diagnosing internal and external threats to the economic security of the educational institution; means and methodology of the system-value approach; algorithms for recognition of crisis situations; the optimization model for forecasting crisis situations and managing risk as well as the decision-making system for coordination of regional structures’ interests concerning investment resources based on the model of a program-designtarget complex

Validation of simple quantification methods for 18F FP CIT PET Using Automatic Delineation of volumes of interest based on statistical probabilistic anatomical mapping and isocontour margin setting

International Nuclear Information System (INIS)

Kim, Yong Il; Im, Hyung Jun; Paeng, Jin Chul; Lee, Jae Sung; Eo, Jae Seon; Kim, Dong Hyun; Kim, Euishin E.; Kang, Keon Wook; Chung, June Key; Lee Dong Soo

2012-01-01

18 F FP CIT positron emission tomography (PET) is an effective imaging for dopamine transporters. In usual clinical practice, 18 F FP CIT PET is analyzed visually or quantified using manual delineation of a volume of interest (VOI) fir the stratum. in this study, we suggested and validated two simple quantitative methods based on automatic VOI delineation using statistical probabilistic anatomical mapping (SPAM) and isocontour margin setting. Seventy five 18 F FP CIT images acquired in routine clinical practice were used for this study. A study-specific image template was made and the subject images were normalized to the template. afterwards, uptakes in the striatal regions and cerebellum were quantified using probabilistic VOI based on SPAM. A quantitative parameter, Q SPAM, was calculated to simulate binding potential. additionally, the functional volume of each striatal region and its uptake were measured in automatically delineated VOI using isocontour margin setting. Uptake volume product(Q UVP) was calculated for each striatal region. Q SPAMa nd Q UVPw as calculated for each visual grading and the influence of cerebral atrophy on the measurements was tested. Image analyses were successful in all the cases. Both the Q SPAMa nd Q UVPw ere significantly different according to visual grading (0.001). The agreements of Q UVPa nd Q SPAMw ith visual grading were slight to fair for the caudate nucleus (K= 0.421 and 0.291, respectively) and good to prefect to the putamen (K=0.663 and 0.607, respectively). Also, Q SPAMa nd Q UVPh ad a significant correlation with each other (0.001). Cerebral atrophy made a significant difference in Q SPAMa nd Q UVPo f the caudate nuclei regions with decreased 18 F FP CIT uptake. Simple quantitative measurements of Q SPAMa nd Q UVPs howed acceptable agreement with visual grad-ing. although Q SPAMi n some group may be influenced by cerebral atrophy, these simple methods are expected to be effective in the quantitative analysis of F FP

Apparent diffusion coefficient measurement in glioma: Influence of region-of-interest determination methods on apparent diffusion coefficient values, interobserver variability, time efficiency, and diagnostic ability.

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Han, Xu; Suo, Shiteng; Sun, Yawen; Zu, Jinyan; Qu, Jianxun; Zhou, Yan; Chen, Zengai; Xu, Jianrong

2017-03-01

To compare four methods of region-of-interest (ROI) placement for apparent diffusion coefficient (ADC) measurements in distinguishing low-grade gliomas (LGGs) from high-grade gliomas (HGGs). Two independent readers measured ADC parameters using four ROI methods (single-slice [single-round, five-round and freehand] and whole-volume) on 43 patients (20 LGGs, 23 HGGs) who had undergone 3.0 Tesla diffusion-weighted imaging and time required for each method of ADC measurements was recorded. Intraclass correlation coefficients (ICCs) were used to assess interobserver variability of ADC measurements. Mean and minimum ADC values and time required were compared using paired Student's t-tests. All ADC parameters (mean/minimum ADC values of three single-slice methods, mean/minimum/standard deviation/skewness/kurtosis/the10 th and 25 th percentiles/median/maximum of whole-volume method) were correlated with tumor grade (low versus high) by unpaired Student's t-tests. Discriminative ability was determined by receiver operating characteristic curves. All ADC measurements except minimum, skewness, and kurtosis of whole-volume ROI differed significantly between LGGs and HGGs (all P determination methods. Whole-volume histogram analysis did not yield better results than single-slice methods and took longer. Mean ADC value derived from single-round ROI is the most optimal parameter for differentiating LGGs from HGGs. 3 J. Magn. Reson. Imaging 2017;45:722-730. © 2016 International Society for Magnetic Resonance in Medicine.

The Special Interest Tourism Development and the Small Regions

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Drita Kruja

2011-04-01

Full Text Available It is easy to attract visitors when you have plenty of resources, nice accommodations, powerful selling techniques, many supporting sectors and of course reliable government support. The challenge starts when you lack most of the above and what you have is only a handful of beautiful natural resources, breathtaking sceneries, goodwill and a great desire and pride to show those visitors what your country is made of. How can we generate income using what we have? The answer is simple. You target that group of customers whom are specifically interested in what you have, beautiful views, heartfelt welcome, home like accommodations and very warm people. These customers do not look for fancy, expensive, overcrowded hotels; they are in search of real beauty and nature. They have special interests and would like to fulfill them toward a reasonable price. Hence starts the development of what is widely known as the special interest tourism whose analysis as a potential tool for the improvement of tourism in the region of Shkodra is the main purpose of this paper.

78 FR 48149 - Proposed Information Collection; Comment Request; Statement of Financial Interests, Regional...

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2013-08-07

... Collection; Comment Request; Statement of Financial Interests, Regional Fishery Management Councils AGENCY... days of taking office and must provide updates of their statements at any time any such financial... of a State for [[Page 48150

Personal dose assessment using region of interest analysis compared with harshaw TLD WinREMS software evaluation

International Nuclear Information System (INIS)

Adjei, D.

2010-06-01

Personal dose equivalents, Hp(10), have been evaluated manually using Region of Interest (ROI) analysis and compared with the automated computerized WinREMS software for the occupationally exposed in medical, industrial and research/teaching applications for 2008 and 2009. The mean annual effective dose estimated by the WinREMS software for medical, industrial and research/teaching applications for the study period are 0.459 mSv, 0.549mSv and 0.447 mSv, respectively compared with ROI analysis are 0.424 mSv, 0.520 mSv and 0.407 mSv respectively. The mean annual collective doses evaluated by the WinREMS software for medical, industrial and research/teaching applications for the two-year study period are 0.258 man-Sv, 0.084 man-Sv and 0.032 man-Sv respectively, compared with the ROI analysis with values: 0.238 man-Sv, 0.080 man-Sv and 0.029 man-Sv respectively. The individual doses for the occupationally exposed in Ghana fall within the typical range of individual doses in the UNSCEAR 2008 report. In calibration mode, the WinREMS method overestimated the personal dose equivalent by 51.3% for doses below 1 mSv and 12.0% above 1 mSv. The corresponding values for the Region of Interest analysis method are 13.2% and 6.5%. The results from the study indicate that the ROI analysis provides a better alternative to estimating the personal doses (au).

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

International Nuclear Information System (INIS)

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

1991-01-01

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

The Evolution of the Region of Interest Builder in the ATLAS Experiment at CERN

CERN Document Server

Rifki, Othmane; The ATLAS collaboration; Crone, Gordon Jeremy; Green, Barry; Love, Jeremy; Proudfoot, James; Panduro Vazquez, William; Vandelli, Wainer; Zhang, Jinlong

2015-01-01

ATLAS is a general purpose particle detector at the Large Hadron Collider (LHC) at CERN designed to measure the products of proton collisions. Given their high interaction rate (1GHz), selective triggering in real time is required to reduce the rate to the experiment’s data storage capacity (1KHz). To meet this requirement, ATLAS employs a combination of hardware and software triggers to select interesting collisions for physics analysis. The Region of Interest Builder (RoIB) is an integral part of the ATLAS detector Trigger and Data Acquisition (TDAQ) chain where the coordinates of the regions of interest (RoIs) identified by the first level trigger (L1) are collected and passed to the High Level Trigger (HLT) to make a decision. While the current custom RoIB operated reliably during the first run of the LHC, it is desirable to have the RoIB more operationally maintainable in the new run, which will reach higher luminosities with an increased complexity of L1 triggers. We are responsible for migrating the ...

Emotion Discrimination using spatially Compact Regions of Interest extracted from Imaging EEG Activity

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Jorge Ivan Padilla-Buritica

2016-07-01

Full Text Available Lately, research on computational models of emotion had been getting much attention due to their potential for understanding the mechanisms of emotions and their promising broad range of applications that potentially bridge the gap between human and machine interactions. We propose a new method for emotion classification that relies on features extracted from those active brain areas that are most likely related to emotions. To this end, we carry out the selection of spatially compact regions of interest that are computed using the brain neural activity reconstructed from electroencephalography data. Throughout this study, we consider three representative feature extraction methods widely applied to emotion detection tasks, including Power spectral density, Wavelet, and Hjorth parameters. Further feature selection is carried out using principal component analysis. For validation purpose, these features are used to feed a support vector machine classifier that is trained under the leave-one-out cross-validation strategy. Obtained results on real affective data show that incorporation of the proposed training method in combination with the enhanced spatial resolution provided by the source estimation allows improving the performed accuracy of discrimination in most of the considered emotions, namely: dominance, valence, and linking.

Using Symmetrical Regions of Interest to Improve Visual SLAM

NARCIS (Netherlands)

Kootstra, Geert; Schomaker, Lambertus

2009-01-01

Simultaneous Localization and Mapping (SLAM) based on visual information is a challenging problem. One of the main problems with visual SLAM is to find good quality landmarks, that can be detected despite noise and small changes in viewpoint. Many approaches use SIFT interest points as visual

Apparent diffusion coefficient measurements in diffusion-weighted magnetic resonance imaging of the anterior mediastinum: inter-observer reproducibility of five different methods of region-of-interest positioning

Energy Technology Data Exchange (ETDEWEB)

Priola, Adriano Massimiliano; Priola, Sandro Massimo; Parlatano, Daniela; Gned, Dario; Veltri, Andrea [San Luigi Gonzaga University Hospital, Department of Diagnostic Imaging, Regione Gonzole 10, Orbassano, Torino (Italy); Giraudo, Maria Teresa [University of Torino, Department of Mathematics ' ' Giuseppe Peano' ' , Torino (Italy); Giardino, Roberto; Ardissone, Francesco [San Luigi Gonzaga University Hospital, Department of Thoracic Surgery, Regione Gonzole 10, Orbassano, Torino (Italy); Ferrero, Bruno [San Luigi Gonzaga University Hospital, Department of Neurology, Regione Gonzole 10, Orbassano, Torino (Italy)

2017-04-15

To investigate inter-reader reproducibility of five different region-of-interest (ROI) protocols for apparent diffusion coefficient (ADC) measurements in the anterior mediastinum. In eighty-one subjects, on ADC mapping, two readers measured the ADC using five methods of ROI positioning that encompassed the entire tissue (whole tissue volume [WTV], three slices observer-defined [TSOD], single-slice [SS]) or the more restricted areas (one small round ROI [OSR], multiple small round ROI [MSR]). Inter-observer variability was assessed with interclass correlation coefficient (ICC), coefficient of variation (CoV), and Bland-Altman analysis. Nonparametric tests were performed to compare the ADC between ROI methods. The measurement time was recorded and compared between ROI methods. All methods showed excellent inter-reader agreement with best and worst reproducibility in WTV and OSR, respectively (ICC, 0.937/0.874; CoV, 7.3 %/16.8 %; limits of agreement, ±0.44/±0.77 x 10{sup -3} mm{sup 2}/s). ADC values of OSR and MSR were significantly lower compared to the other methods in both readers (p < 0.001). The SS and OSR methods required less measurement time (14 ± 2 s) compared to the others (p < 0.0001), while the WTV method required the longest measurement time (90 ± 56 and 77 ± 49 s for each reader) (p < 0.0001). All methods demonstrate excellent inter-observer reproducibility with the best agreement in WTV, although it requires the longest measurement time. (orig.)

An Improved Privacy-Preserving Framework for Location-Based Services Based on Double Cloaking Regions with Supplementary Information Constraints

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Li Kuang

2017-01-01

Full Text Available With the rapid development of location-based services in the field of mobile network applications, users enjoy the convenience of location-based services on one side, while being exposed to the risk of disclosure of privacy on the other side. Attacker will make a fierce attack based on the probability of inquiry, map data, point of interest (POI, and other supplementary information. The existing location privacy protection techniques seldom consider the supplementary information held by attackers and usually only generate single cloaking region according to the protected location point, and the query efficiency is relatively low. In this paper, we improve the existing LBSs system framework, in which we generate double cloaking regions by constraining the supplementary information, and then k-anonymous task is achieved by the cooperation of the double cloaking regions; specifically speaking, k dummy points of fixed dummy positions in the double cloaking regions are generated and the LBSs query is then performed. Finally, the effectiveness of the proposed method is verified by the experiments on real datasets.

Diffusion tensor imaging of nigral degeneration in Parkinson's disease: A region-of-interest and voxel-based study at 3 T and systematic review with meta-analysis☆

Science.gov (United States)

Schwarz, Stefan T.; Abaei, Maryam; Gontu, Vamsi; Morgan, Paul S.; Bajaj, Nin; Auer, Dorothee P.

2013-01-01

There is increasing interest in developing a reliable, affordable and accessible disease biomarker of Parkinson's disease (PD) to facilitate disease modifying PD-trials. Imaging biomarkers using magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) can describe parameters such as fractional anisotropy (FA), mean diffusivity (MD) or apparent diffusion coefficient (ADC). These parameters, when measured in the substantia nigra (SN), have not only shown promising but also varying and controversial results. To clarify the potential diagnostic value of nigral DTI in PD and its dependency on selection of region-of-interest, we undertook a high resolution DTI study at 3 T. 59 subjects (32 PD patients, 27 age and sex matched healthy controls) were analysed using manual outlining of SN and substructures, and voxel-based analysis (VBA). We also performed a systematic literature review and meta-analysis to estimate the effect size (DES) of disease related nigral DTI changes. We found a regional increase in nigral mean diffusivity in PD (mean ± SD, PD 0.80 ± 0.10 vs. controls 0.73 ± 0.06 · 10− 3 mm2/s, p = 0.002), but no difference using a voxel based approach. No significant disease effect was seen using meta-analysis of nigral MD changes (10 studies, DES = + 0.26, p = 0.17, I2 = 30%). None of the nigral regional or voxel based analyses of this study showed altered fractional anisotropy. Meta-analysis of 11 studies on nigral FA changes revealed a significant PD induced FA decrease. There was, however, a very large variation in results (I2 = 86%) comparing all studies. After exclusion of five studies with unusual high values of nigral FA in the control group, an acceptable heterogeneity was reached, but there was non-significant disease effect (DES = − 0.5, p = 0.22, I2 = 28%). The small PD related nigral MD changes in conjunction with the negative findings on VBA and meta-analysis limit the usefulness of nigral MD measures as

Regional interests of Russia in the concept of development of the Arctic

Directory of Open Access Journals (Sweden)

Bogachev V. F.

2015-12-01

Full Text Available The paper analyzes the current state and prospects of development of the Arctic in the context of its growing value in connection with expansion of demand for strategic types of raw materials, increased interest in the region of the concerned states and transnational consortia, as well as with the development of the international transport corridors and new technologies facilitating access to sources of raw materials

A Low-Power Wireless Image Sensor Node with Noise-Robust Moving Object Detection and a Region-of-Interest Based Rate Controller

Science.gov (United States)

2017-03-01

from both environment and hardware further reduces the transmission energy with negligible computation and memory overhead. The rate controller...detection, Region-of-interest, Rate control Introduction In wireless image sensor nodes for moving object surveillance, energy efficiency can be...noise, reliable moving object detection is required to avoid unnecessary transmission of background scenes [1]. Transmission energy can be further

Improving cluster-based methods for investigating potential for insect pest species establishment: region-specific risk factors

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Michael J. Watts

2011-09-01

Full Text Available Existing cluster-based methods for investigating insect species assemblages or profiles of a region to indicate the risk of new insect pest invasion have a major limitation in that they assign the same species risk factors to each region in a cluster. Clearly regions assigned to the same cluster have different degrees of similarity with respect to their species profile or assemblage. This study addresses this concern by applying weighting factors to the cluster elements used to calculate regional risk factors, thereby producing region-specific risk factors. Using a database of the global distribution of crop insect pest species, we found that we were able to produce highly differentiated region-specific risk factors for insect pests. We did this by weighting cluster elements by their Euclidean distance from the target region. Using this approach meant that risk weightings were derived that were more realistic, as they were specific to the pest profile or species assemblage of each region. This weighting method provides an improved tool for estimating the potential invasion risk posed by exotic species given that they have an opportunity to establish in a target region.

Identifying regions of interest in medical images using self-organizing maps.

Science.gov (United States)

Teng, Wei-Guang; Chang, Ping-Lin

2012-10-01

Advances in data acquisition, processing and visualization techniques have had a tremendous impact on medical imaging in recent years. However, the interpretation of medical images is still almost always performed by radiologists. Developments in artificial intelligence and image processing have shown the increasingly great potential of computer-aided diagnosis (CAD). Nevertheless, it has remained challenging to develop a general approach to process various commonly used types of medical images (e.g., X-ray, MRI, and ultrasound images). To facilitate diagnosis, we recommend the use of image segmentation to discover regions of interest (ROI) using self-organizing maps (SOM). We devise a two-stage SOM approach that can be used to precisely identify the dominant colors of a medical image and then segment it into several small regions. In addition, by appropriately conducting the recursive merging steps to merge smaller regions into larger ones, radiologists can usually identify one or more ROIs within a medical image.

Performance of shear-wave elastography for breast masses using different region-of-interest (ROI) settings.

Science.gov (United States)

Youk, Ji Hyun; Son, Eun Ju; Han, Kyunghwa; Gweon, Hye Mi; Kim, Jeong-Ah

2018-07-01

Background Various size and shape of region of interest (ROI) can be applied for shear-wave elastography (SWE). Purpose To investigate the diagnostic performance of SWE according to ROI settings for breast masses. Material and Methods To measure elasticity for 142 lesions, ROIs were set as follows: circular ROIs 1 mm (ROI-1), 2 mm (ROI-2), and 3 mm (ROI-3) in diameter placed over the stiffest part of the mass; freehand ROIs drawn by tracing the border of mass (ROI-M) and the area of peritumoral increased stiffness (ROI-MR); and circular ROIs placed within the mass (ROI-C) and to encompass the area of peritumoral increased stiffness (ROI-CR). Mean (E mean ), maximum (E max ), and standard deviation (E SD ) of elasticity values and their areas under the receiver operating characteristic (ROC) curve (AUCs) for diagnostic performance were compared. Results Means of E mean and E SD significantly differed between ROI-1, ROI-2, and ROI-3 ( P Shear-wave elasticity values and their diagnostic performance vary based on ROI settings and elasticity indices. E max is recommended for the ROIs over the stiffest part of mass and an ROI encompassing the peritumoral area of increased stiffness is recommended for elastic heterogeneity of mass.

Simple and efficient method for region of interest value extraction from picture archiving and communication system viewer with optical character recognition software and macro program.

Science.gov (United States)

Lee, Young Han; Park, Eun Hae; Suh, Jin-Suck

2015-01-01

The objectives are: 1) to introduce a simple and efficient method for extracting region of interest (ROI) values from a Picture Archiving and Communication System (PACS) viewer using optical character recognition (OCR) software and a macro program, and 2) to evaluate the accuracy of this method with a PACS workstation. This module was designed to extract the ROI values on the images of the PACS, and created as a development tool by using open-source OCR software and an open-source macro program. The principal processes are as follows: (1) capture a region of the ROI values as a graphic file for OCR, (2) recognize the text from the captured image by OCR software, (3) perform error-correction, (4) extract the values including area, average, standard deviation, max, and min values from the text, (5) reformat the values into temporary strings with tabs, and (6) paste the temporary strings into the spreadsheet. This principal process was repeated for the number of ROIs. The accuracy of this module was evaluated on 1040 recognitions from 280 randomly selected ROIs of the magnetic resonance images. The input times of ROIs were compared between conventional manual method and this extraction module-assisted input method. The module for extracting ROI values operated successfully using the OCR and macro programs. The values of the area, average, standard deviation, maximum, and minimum could be recognized and error-corrected with AutoHotkey-coded module. The average input times using the conventional method and the proposed module-assisted method were 34.97 seconds and 7.87 seconds, respectively. A simple and efficient method for ROI value extraction was developed with open-source OCR and a macro program. Accurate inputs of various numbers from ROIs can be extracted with this module. The proposed module could be applied to the next generation of PACS or existing PACS that have not yet been upgraded. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.

Optimal depth-based regional frequency analysis

Science.gov (United States)

Wazneh, H.; Chebana, F.; Ouarda, T. B. M. J.

2013-06-01

Classical methods of regional frequency analysis (RFA) of hydrological variables face two drawbacks: (1) the restriction to a particular region which can lead to a loss of some information and (2) the definition of a region that generates a border effect. To reduce the impact of these drawbacks on regional modeling performance, an iterative method was proposed recently, based on the statistical notion of the depth function and a weight function φ. This depth-based RFA (DBRFA) approach was shown to be superior to traditional approaches in terms of flexibility, generality and performance. The main difficulty of the DBRFA approach is the optimal choice of the weight function ϕ (e.g., φ minimizing estimation errors). In order to avoid a subjective choice and naïve selection procedures of φ, the aim of the present paper is to propose an algorithm-based procedure to optimize the DBRFA and automate the choice of ϕ according to objective performance criteria. This procedure is applied to estimate flood quantiles in three different regions in North America. One of the findings from the application is that the optimal weight function depends on the considered region and can also quantify the region's homogeneity. By comparing the DBRFA to the canonical correlation analysis (CCA) method, results show that the DBRFA approach leads to better performances both in terms of relative bias and mean square error.

Delineation of wetland areas from high resolution WorldView-2 data by object-based method

International Nuclear Information System (INIS)

Hassan, N; Hamid, J R A; Adnan, N A; Jaafar, M

2014-01-01

Various classification methods are available that can be used to delineate land cover types. Object-based is one of such methods for delineating the land cover from satellite imageries. This paper focuses on the digital image processing aspects of discriminating wetland areas via object-based method using high resolution satellite multispectral WorldView-2 image data taken over part of Penang Island region. This research is an attempt to improve the wetland area delineation in conjunction with a range of classification techniques which can be applied to satellite data with high spatial and spectral resolution such as World View 2. The intent is to determine a suitable approach to delineate and map these wetland areas more appropriately. There are common parameters to take into account that are pivotal in object-based method which are the spatial resolution and the range of spectral channels of the imaging sensor system. The preliminary results of the study showed object-based analysis is capable of delineating wetland region of interest with an accuracy that is acceptable to the required tolerance for land cover classification

A speeded-up saliency region-based contrast detection method for small targets

Science.gov (United States)

Li, Zhengjie; Zhang, Haiying; Bai, Jiaojiao; Zhou, Zhongjun; Zheng, Huihuang

2018-04-01

To cope with the rapid development of the real applications for infrared small targets, the researchers have tried their best to pursue more robust detection methods. At present, the contrast measure-based method has become a promising research branch. Following the framework, in this paper, a speeded-up contrast measure scheme is proposed based on the saliency detection and density clustering. First, the saliency region is segmented by saliency detection method, and then, the Multi-scale contrast calculation is carried out on it instead of traversing the whole image. Second, the target with a certain "integrity" property in spatial is exploited to distinguish the target from the isolated noises by density clustering. Finally, the targets are detected by a self-adaptation threshold. Compared with time-consuming MPCM (Multiscale Patch Contrast Map), the time cost of the speeded-up version is within a few seconds. Additional, due to the use of "clustering segmentation", the false alarm caused by heavy noises can be restrained to a lower level. The experiments show that our method has a satisfied FASR (False alarm suppression ratio) and real-time performance compared with the state-of-art algorithms no matter in cloudy sky or sea-sky background.

Dynamic magnetic resonance imaging of cervical lymph nodes in patients with oral cancer. Utility of the small region of interest method in evaluating the architecture of cervical lymph nodes

International Nuclear Information System (INIS)

Oomori, Miwako; Fukunari, Fumiko; Kagawa, Toyohiro; Okamura, Kazuhiko; Yuasa, Kenji

2008-01-01

Our purpose was to evaluate the utility of the small region of interest (ROI) method to detect the architecture of cervical lymph nodes and the specificity of time-intensity curves for tissue present in cervical lymph nodes. Specimens were taken from 17 lymph nodes of eight patients (ten sides of the neck) with oral squamous cell carcinoma who underwent dynamic contrast-enhanced magnetic resonance imaging (MRI) and neck dissection between 2005 and 2007 at our hospital. Two methods of constructing time-intensity curves were compared: the conventional method that uses relatively large ROIs, and a new method that uses small ROIs. Curves made with the small ROI method were then compared to histopathological findings for dissected lymph nodes. The small ROI method allowed differences in signal intensity to be discerned at the tissue level, which was not possible with the conventional large ROI method. Curves for normal lymphoid tissue tended to be type I, those for tumor cells tended to be type II, and those for keratinization/necrosis tended to be types III and IV, indicating that time-intensity curves can be specific to tissue type within lymph nodes. The small ROI method was useful for evaluation of the architecture of cervical lymph nodes. (author)

Joint Labeling Of Multiple Regions of Interest (Rois) By Enhanced Auto Context Models.

Science.gov (United States)

Kim, Minjeong; Wu, Guorong; Guo, Yanrong; Shen, Dinggang

2015-04-01

Accurate segmentation of a set of regions of interest (ROIs) in the brain images is a key step in many neuroscience studies. Due to the complexity of image patterns, many learning-based segmentation methods have been proposed, including auto context model (ACM) that can capture high-level contextual information for guiding segmentation. However, since current ACM can only handle one ROI at a time, neighboring ROIs have to be labeled separately with different ACMs that are trained independently without communicating each other. To address this, we enhance the current single-ROI learning ACM to multi-ROI learning ACM for joint labeling of multiple neighboring ROIs (called e ACM). First, we extend current independently-trained single-ROI ACMs to a set of jointly-trained cross-ROI ACMs, by simultaneous training of ACMs for all spatially-connected ROIs to let them to share their respective intermediate outputs for coordinated labeling of each image point. Then, the context features in each ACM can capture the cross-ROI dependence information from the outputs of other ACMs that are designed for neighboring ROIs. Second, we upgrade the output labeling map of each ACM with the multi-scale representation, thus both local and global context information can be effectively used to increase the robustness in characterizing geometric relationship among neighboring ROIs. Third, we integrate ACM into a multi-atlases segmentation paradigm, for encompassing high variations among subjects. Experiments on LONI LPBA40 dataset show much better performance by our e ACM, compared to the conventional ACM.

Optimal depth-based regional frequency analysis

Directory of Open Access Journals (Sweden)

H. Wazneh

2013-06-01

Full Text Available Classical methods of regional frequency analysis (RFA of hydrological variables face two drawbacks: (1 the restriction to a particular region which can lead to a loss of some information and (2 the definition of a region that generates a border effect. To reduce the impact of these drawbacks on regional modeling performance, an iterative method was proposed recently, based on the statistical notion of the depth function and a weight function φ. This depth-based RFA (DBRFA approach was shown to be superior to traditional approaches in terms of flexibility, generality and performance. The main difficulty of the DBRFA approach is the optimal choice of the weight function ϕ (e.g., φ minimizing estimation errors. In order to avoid a subjective choice and naïve selection procedures of φ, the aim of the present paper is to propose an algorithm-based procedure to optimize the DBRFA and automate the choice of ϕ according to objective performance criteria. This procedure is applied to estimate flood quantiles in three different regions in North America. One of the findings from the application is that the optimal weight function depends on the considered region and can also quantify the region's homogeneity. By comparing the DBRFA to the canonical correlation analysis (CCA method, results show that the DBRFA approach leads to better performances both in terms of relative bias and mean square error.

SU-F-J-183: Interior Region-Of-Interest Tomography by Using Inverse Geometry System

Energy Technology Data Exchange (ETDEWEB)

Kim, K; Kim, D; Kang, S; Kim, T; Shin, D; Cho, M; Noh, Y; Suh, T [Department of Biomedical Engineering and Research Institute of Biomedical Engineering, College of Medicine, The Catholic University of Korea, Seoul (Korea, Republic of)

2016-06-15

Purpose: The inverse geometry computed tomography (IGCT) composed of multiple source and small size detector has several merits such as reduction of scatter effect and large volumetric imaging within one rotation without cone-beam artifact, compared to conventional cone-beam computed tomography (CBCT). By using this multi-source characteristics, we intend to present a selective and multiple interior region-of-interest (ROI) imaging method by using a designed source on-off sequence of IGCT. Methods: All of the IGCT sources are operated one by one sequentially, and each projection in the shape of narrow cone-beam covers its own partial volume of full field of view (FOV) determined from system geometry. Thus, through controlling multi source operation, limited irradiation within ROI is possible and selective radon space data for ROI imaging can be acquired without additional X-ray filtration. With this feature, we designed a source on-off sequence for multi ROI-IGCT imaging, and projections of ROI-IGCT were generated by using the on-off sequence. Multi ROI-IGCT images were reconstructed by using filtered back-projection algorithm. All these imaging process of our study has been performed by utilizing digital phantom and patient CT data. ROI-IGCT images of the phantom were compared to CBCT image and the phantom data for the image quality evaluation. Results: Image quality of ROI-IGCT was comparable to that of CBCT. However, the distal axial-plane from the FOV center, large cone-angle region, ROI-IGCT showed uniform image quality without significant cone-beam artifact contrary to CBCT. Conclusion: ROI-IGCT showed comparable image quality and has the capability to provide multi ROI image within a rotation. Projection of ROI-IGCT is performed by selective irradiation, hence unnecessary imaging dose to non-interest region can be reduced. In this regard, it seems to be useful for diagnostic or image guidance purpose in radiotherapy such as low dose target localization and

SU-F-J-183: Interior Region-Of-Interest Tomography by Using Inverse Geometry System

International Nuclear Information System (INIS)

Kim, K; Kim, D; Kang, S; Kim, T; Shin, D; Cho, M; Noh, Y; Suh, T

2016-01-01

Purpose: The inverse geometry computed tomography (IGCT) composed of multiple source and small size detector has several merits such as reduction of scatter effect and large volumetric imaging within one rotation without cone-beam artifact, compared to conventional cone-beam computed tomography (CBCT). By using this multi-source characteristics, we intend to present a selective and multiple interior region-of-interest (ROI) imaging method by using a designed source on-off sequence of IGCT. Methods: All of the IGCT sources are operated one by one sequentially, and each projection in the shape of narrow cone-beam covers its own partial volume of full field of view (FOV) determined from system geometry. Thus, through controlling multi source operation, limited irradiation within ROI is possible and selective radon space data for ROI imaging can be acquired without additional X-ray filtration. With this feature, we designed a source on-off sequence for multi ROI-IGCT imaging, and projections of ROI-IGCT were generated by using the on-off sequence. Multi ROI-IGCT images were reconstructed by using filtered back-projection algorithm. All these imaging process of our study has been performed by utilizing digital phantom and patient CT data. ROI-IGCT images of the phantom were compared to CBCT image and the phantom data for the image quality evaluation. Results: Image quality of ROI-IGCT was comparable to that of CBCT. However, the distal axial-plane from the FOV center, large cone-angle region, ROI-IGCT showed uniform image quality without significant cone-beam artifact contrary to CBCT. Conclusion: ROI-IGCT showed comparable image quality and has the capability to provide multi ROI image within a rotation. Projection of ROI-IGCT is performed by selective irradiation, hence unnecessary imaging dose to non-interest region can be reduced. In this regard, it seems to be useful for diagnostic or image guidance purpose in radiotherapy such as low dose target localization and

A region-based palliative care intervention trial using the mixed-method approach: Japan OPTIM study

Directory of Open Access Journals (Sweden)

Morita Tatsuya

2012-01-01

Full Text Available Abstract Background Disseminating palliative care is a critical task throughout the world. Several outcome studies explored the effects of regional palliative care programs on a variety of end-points, and some qualitative studies investigated the process of developing community palliative care networks. These studies provide important insights into the potential benefits of regional palliative care programs, but the clinical implications are still limited, because: 1 many interventions included fundamental changes in the structure of the health care system, and, thus, the results would not be applicable for many regions where structural changes are difficult or unfeasible; 2 patient-oriented outcomes were not measured or explored only in a small number of populations, and interpretation of the results from a patient's view is difficult; and 3 no studies adopted a mixed-method approach using both quantitative and qualitative methodologies to interpret the complex phenomenon from multidimensional perspectives. Methods/designs This is a mixed-method regional intervention trial, consisting of a pre-post outcome study and qualitative process studies. The primary aim of the pre-post outcome study is to evaluate the change in the number of home deaths, use of specialized palliative care services, patient-reported quality of palliative care, and family-reported quality of palliative care after regional palliative care intervention. The secondary aim is to explore the changes in a variety of outcomes, including patients' quality of life, pain intensity, family care burden, and physicians' and nurses' knowledge, difficulties, and self-perceived practice. Outcome measurements used in this study include the Care Evaluation Scale, Good Death Inventory, Brief pain Inventory, Caregiving Consequence Inventory, Sense of Security Scale, Palliative Care Knowledge test, Palliative Care Difficulties Scale, and Palliative Care Self-reported Practice Scale. Study

Fully automated quantification of regional cerebral blood flow with three-dimensional stereotaxic region of interest template. Validation using magnetic resonance imaging. Technical note

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Takeuchi, Ryo; Katayama, Shigenori; Takeda, Naoya; Fujita, Katsuzo [Nishi-Kobe Medical Center (Japan); Yonekura, Yoshiharu [Fukui Medical Univ., Matsuoka (Japan); Konishi, Junji [Kyoto Univ. (Japan). Graduate School of Medicine

2003-03-01

The previously reported three-dimensional stereotaxic region of interest (ROI) template (3DSRT-t) for the analysis of anatomically standardized technetium-99m-L,L-ethyl cysteinate dimer ({sup 99m}Tc-ECD) single photon emission computed tomography (SPECT) images was modified for use in a fully automated regional cerebral blood flow (rCBF) quantification software, 3DSRT, incorporating an anatomical standardization engine transplanted from statistical parametric mapping 99 and ROIs for quantification based on 3DSRT-t. Three-dimensional T{sub 2}-weighted magnetic resonance images of 10 patients with localized infarcted areas were compared with the ROI contour of 3DSRT, and the positions of the central sulcus in the primary sensorimotor area were also estimated. All positions of the 20 lesions were in strict accordance with the ROI delineation of 3DSRT. The central sulcus was identified on at least one side of 210 paired ROIs and in the middle of 192 (91.4%) of these 210 paired ROIs among the 273 paired ROIs of the primary sensorimotor area. The central sulcus was recognized in the middle of more than 71.4% of the ROIs in which the central sulcus was identifiable in the respective 28 slices of the primary sensorimotor area. Fully automated accurate ROI delineation on anatomically standardized images is possible with 3DSRT, which enables objective quantification of rCBF and vascular reserve in only a few minutes using {sup 99m}Tc-ECD SPECT images obtained by the resting and vascular reserve (RVR) method. (author)

Fully automated quantification of regional cerebral blood flow with three-dimensional stereotaxic region of interest template. Validation using magnetic resonance imaging. Technical note

International Nuclear Information System (INIS)

Takeuchi, Ryo; Katayama, Shigenori; Takeda, Naoya; Fujita, Katsuzo; Yonekura, Yoshiharu; Konishi, Junji

2003-01-01

The previously reported three-dimensional stereotaxic region of interest (ROI) template (3DSRT-t) for the analysis of anatomically standardized technetium-99m-L,L-ethyl cysteinate dimer ( 99m Tc-ECD) single photon emission computed tomography (SPECT) images was modified for use in a fully automated regional cerebral blood flow (rCBF) quantification software, 3DSRT, incorporating an anatomical standardization engine transplanted from statistical parametric mapping 99 and ROIs for quantification based on 3DSRT-t. Three-dimensional T 2 -weighted magnetic resonance images of 10 patients with localized infarcted areas were compared with the ROI contour of 3DSRT, and the positions of the central sulcus in the primary sensorimotor area were also estimated. All positions of the 20 lesions were in strict accordance with the ROI delineation of 3DSRT. The central sulcus was identified on at least one side of 210 paired ROIs and in the middle of 192 (91.4%) of these 210 paired ROIs among the 273 paired ROIs of the primary sensorimotor area. The central sulcus was recognized in the middle of more than 71.4% of the ROIs in which the central sulcus was identifiable in the respective 28 slices of the primary sensorimotor area. Fully automated accurate ROI delineation on anatomically standardized images is possible with 3DSRT, which enables objective quantification of rCBF and vascular reserve in only a few minutes using 99m Tc-ECD SPECT images obtained by the resting and vascular reserve (RVR) method. (author)

Spatio-temporal characteristics of the extreme precipitation by L-moment-based index-flood method in the Yangtze River Delta region, China

Science.gov (United States)

Yin, Yixing; Chen, Haishan; Xu, Chong-Yu; Xu, Wucheng; Chen, Changchun; Sun, Shanlei

2016-05-01

The regionalization methods, which "trade space for time" by pooling information from different locations in the frequency analysis, are efficient tools to enhance the reliability of extreme quantile estimates. This paper aims at improving the understanding of the regional frequency of extreme precipitation by using regionalization methods, and providing scientific background and practical assistance in formulating the regional development strategies for water resources management in one of the most developed and flood-prone regions in China, the Yangtze River Delta (YRD) region. To achieve the main goals, L-moment-based index-flood (LMIF) method, one of the most popular regionalization methods, is used in the regional frequency analysis of extreme precipitation with special attention paid to inter-site dependence and its influence on the accuracy of quantile estimates, which has not been considered by most of the studies using LMIF method. Extensive data screening of stationarity, serial dependence, and inter-site dependence was carried out first. The entire YRD region was then categorized into four homogeneous regions through cluster analysis and homogenous analysis. Based on goodness-of-fit statistic and L-moment ratio diagrams, generalized extreme-value (GEV) and generalized normal (GNO) distributions were identified as the best fitted distributions for most of the sub-regions, and estimated quantiles for each region were obtained. Monte Carlo simulation was used to evaluate the accuracy of the quantile estimates taking inter-site dependence into consideration. The results showed that the root-mean-square errors (RMSEs) were bigger and the 90 % error bounds were wider with inter-site dependence than those without inter-site dependence for both the regional growth curve and quantile curve. The spatial patterns of extreme precipitation with a return period of 100 years were finally obtained which indicated that there are two regions with highest precipitation

Interest in science: a RIASEC-based analysis of students' interests

Science.gov (United States)

Dierks, Pay O.; Höffler, Tim N.; Blankenburg, Janet S.; Peters, Heide; Parchmann, Ilka

2016-01-01

Considering the reported lack of interest in the STEM-domain and the consequential difficulties in recruiting talented and interested young academics, the development of effective enrichment measures is indispensable. This requires a precise picture of students' interests. The paper presents an approach to characterize interest profiles in explicitly science-related activities. Adapting Holland's RIASEC-model, an instrument was developed and tested which allows the description of interest in activities along Holland's dimensions (and a seventh dimension networking) within the confined science domain. The findings of a study with N = 247 students (age cohorts 12-19 years) uncovered interest differences for the environments school, enrichment, and (prospective) vocation. The mutual importance of the performed activity and the environment the activity is performed in is confirmed by a cross-classified model. Contrasting different subgroups revealed multiple results, e.g., girls showed more interest in artistic and social activities within the science domain. High achieving students showed more interest in science-related activities in all dimensions. In conclusion, using our adapted model, students' interest structure can be described in a differentiated manner. This could lay the foundation for further analyses of students' interest profiles and thereby contribute to future development of effective and congruent enrichment measures, thus enhancing interest in science.

[Interest of ultrasonographic guidance in paediatric regional anaesthesia].

Science.gov (United States)

Dadure, C; Raux, O; Rochette, A; Capdevila, X

2009-10-01

The use of ultrasonographic guidance for regional anaesthesia has known recently a big interest in children in recent years. The linear ultrasound probes with a 25 mm active surface area (or probes with 38 mm active surface area in older children), with high sound frequencies in the range 8-14 MHz, allow a good compromise between excellent resolution for superficial structure and good penetration depths. In children, the easiest ultrasound guided blocks are axillar blocks, femoral blocks, fascia iliaca compartment blocks, ilio-inguinal blocks and para-umbilical blocks, caudal blocks. They permit a safe and easy learning curve of these techniques. The main advantage of ultrasound guided regional anaesthesia is the visualization of different anatomical structures and the approximate localization of the tip of needle. The other advantages for ultrasound guided peripheral nerve blocks in children are: faster onset time of sensory and motor block, longer duration of sensory blockade, increase of blockade quality and reduction of local anesthetic injection. The use of ultrasonographic guidance for central block allows to visualize different structures as well as spine and his content. Spinous process, ligament flavum, dura mater, conus medullaris and cerebrospinal fluid are identifiable, and give some information on spine, epidural space and the depth between epidural space and skin. At last, in caudal block, ultrasounds permit to evaluate the anatomy of caudal epidural space, especially the relation of the sacral hiatus to the dural sac and the search of occult spinal dysraphism. Benefit of this technique is the visualization of targeted nerves or spaces and the spread of injected local anaesthetic.

Evaluation of auto region of interest settings for single photon emission computed tomography findings

International Nuclear Information System (INIS)

Mizuno, Takashi; Takahashi, Masaaki; Yoshioka, Katsunori

2008-01-01

It has been noted that the manual settings of region of interest (ROI) to the single-photon-emission-computed-tomography (SPECT) slice lacked objectivity when the fixed quantity value of regional cerebral blood flow (rCBF) was measured previously. Therefore, we jointly developed software Brain ROI' with Daiichi Radioisotope Laboratories, Ltd. (Present name: FUJIFILM RI Pharma Co., Ltd.) The software normalized an individual brain to a standard brain template by using Statistical Parametric Mapping 2 (SPM 2) of the easy Z-score Imaging System ver. 3.0 (eZIS Ver. 3.0), and the ROI template was set to a specific slice. In this study, we evaluated the accuracy of this software with an ROI template that we made of useful size and shape, in some clinical samples. The method of automatic setting of ROI was the objective. However, we felt that we should use the shape of the ROI template without the influence of brain atrophy. Moreover, we should see normalization of the individual brain and confirm the accuracy of normalization. When normalization failed, we should partially correct the ROI or set everything by manual operation for the operator. However, it was thought that this software was useful if the tendency was understood because examples of failure were few. (author)

BPF-type region-of-interest reconstruction for parallel translational computed tomography.

Science.gov (United States)

Wu, Weiwen; Yu, Hengyong; Wang, Shaoyu; Liu, Fenglin

2017-01-01

The objective of this study is to present and test a new ultra-low-cost linear scan based tomography architecture. Similar to linear tomosynthesis, the source and detector are translated in opposite directions and the data acquisition system targets on a region-of-interest (ROI) to acquire data for image reconstruction. This kind of tomographic architecture was named parallel translational computed tomography (PTCT). In previous studies, filtered backprojection (FBP)-type algorithms were developed to reconstruct images from PTCT. However, the reconstructed ROI images from truncated projections have severe truncation artefact. In order to overcome this limitation, we in this study proposed two backprojection filtering (BPF)-type algorithms named MP-BPF and MZ-BPF to reconstruct ROI images from truncated PTCT data. A weight function is constructed to deal with data redundancy for multi-linear translations modes. Extensive numerical simulations are performed to evaluate the proposed MP-BPF and MZ-BPF algorithms for PTCT in fan-beam geometry. Qualitative and quantitative results demonstrate that the proposed BPF-type algorithms cannot only more accurately reconstruct ROI images from truncated projections but also generate high-quality images for the entire image support in some circumstances.

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%.

Volumetric quantification of bone-implant contact using micro-computed tomography analysis based on region-based segmentation.

Science.gov (United States)

Kang, Sung-Won; Lee, Woo-Jin; Choi, Soon-Chul; Lee, Sam-Sun; Heo, Min-Suk; Huh, Kyung-Hoe; Kim, Tae-Il; Yi, Won-Jin

2015-03-01

We have developed a new method of segmenting the areas of absorbable implants and bone using region-based segmentation of micro-computed tomography (micro-CT) images, which allowed us to quantify volumetric bone-implant contact (VBIC) and volumetric absorption (VA). The simple threshold technique generally used in micro-CT analysis cannot be used to segment the areas of absorbable implants and bone. Instead, a region-based segmentation method, a region-labeling method, and subsequent morphological operations were successively applied to micro-CT images. The three-dimensional VBIC and VA of the absorbable implant were then calculated over the entire volume of the implant. Two-dimensional (2D) bone-implant contact (BIC) and bone area (BA) were also measured based on the conventional histomorphometric method. VA and VBIC increased significantly with as the healing period increased (pimplants using micro-CT analysis using a region-based segmentation method.

Accurate Region-of-Interest Recovery Improves the Measurement of the Cell Migration Rate in the In Vitro Wound Healing Assay.

Science.gov (United States)

Bedoya, Cesar; Cardona, Andrés; Galeano, July; Cortés-Mancera, Fabián; Sandoz, Patrick; Zarzycki, Artur

2017-12-01

The wound healing assay is widely used for the quantitative analysis of highly regulated cellular events. In this essay, a wound is voluntarily produced on a confluent cell monolayer, and then the rate of wound reduction (WR) is characterized by processing images of the same regions of interest (ROIs) recorded at different time intervals. In this method, sharp-image ROI recovery is indispensable to compensate for displacements of the cell cultures due either to the exploration of multiple sites of the same culture or to transfers from the microscope stage to a cell incubator. ROI recovery is usually done manually and, despite a low-magnification microscope objective is generally used (10x), repositioning imperfections constitute a major source of errors detrimental to the WR measurement accuracy. We address this ROI recovery issue by using pseudoperiodic patterns fixed onto the cell culture dishes, allowing the easy localization of ROIs and the accurate quantification of positioning errors. The method is applied to a tumor-derived cell line, and the WR rates are measured by means of two different image processing software. Sharp ROI recovery based on the proposed method is found to improve significantly the accuracy of the WR measurement and the positioning under the microscope.

Region of interest based robust watermarking scheme for adaptation in small displays

Science.gov (United States)

Vivekanandhan, Sapthagirivasan; K. B., Kishore Mohan; Vemula, Krishna Manohar

2010-02-01

Now-a-days Multimedia data can be easily replicated and the copyright is not legally protected. Cryptography does not allow the use of digital data in its original form and once the data is decrypted, it is no longer protected. Here we have proposed a new double protected digital image watermarking algorithm, which can embed the watermark image blocks into the adjacent regions of the host image itself based on their blocks similarity coefficient which is robust to various noise effects like Poisson noise, Gaussian noise, Random noise and thereby provide double security from various noises and hackers. As instrumentation application requires a much accurate data, the watermark image which is to be extracted back from the watermarked image must be immune to various noise effects. Our results provide better extracted image compared to the present/existing techniques and in addition we have done resizing the same for various displays. Adaptive resizing for various size displays is being experimented wherein we crop the required information in a frame, zoom it for a large display or resize for a small display using a threshold value and in either cases background is not given much importance but it is only the fore-sight object which gains importance which will surely be helpful in performing surgeries.

Use of X-ray CT-defined regions of interest for the determination of SPECT recovery coefficients

International Nuclear Information System (INIS)

Tang, H.R.; Brown, J.K.; Hasegawa, B.H.

1996-01-01

For accurate activity per unit volume measurements in SPECT, recovery coefficients are usually applied based on the size and shape of objects being imaged to properly account for the resolution limitations of the gamma camera. Because of noise and limited spatial resolution, determination of object sizes and boundaries can be difficult using the SPECT images alone. We therefore have developed a technique which determines activity concentrations for SPECT using regions of interest (ROI's) obtained from coregistered X-ray CT images. In this study, experimental phantoms containing cylindrical and spherical objects were imaged on a combined X-ray CT/SPECT system and reconstructed data volumes were registered using the known geometry of the system. ROI's were defined on the registered CT images and used to help quantify activity concentration in localized regions and to measure object volumes. We have derived the recovery curves for these objects and scan technique. We have also tested a technique that demonstrates activity quantitation without the need for object and size dependent recovery coefficients in the case of low background

A Novel Mobile Video Community Discovery Scheme Using Ontology-Based Semantical Interest Capture

Directory of Open Access Journals (Sweden)

Ruiling Zhang

2016-01-01

Full Text Available Leveraging network virtualization technologies, the community-based video systems rely on the measurement of common interests to define and steady relationship between community members, which promotes video sharing performance and improves scalability community structure. In this paper, we propose a novel mobile Video Community discovery scheme using ontology-based semantical interest capture (VCOSI. An ontology-based semantical extension approach is proposed, which describes video content and measures video similarity according to video key word selection methods. In order to reduce the calculation load of video similarity, VCOSI designs a prefix-filtering-based estimation algorithm to decrease energy consumption of mobile nodes. VCOSI further proposes a member relationship estimate method to construct scalable and resilient node communities, which promotes video sharing capacity of video systems with the flexible and economic community maintenance. Extensive tests show how VCOSI obtains better performance results in comparison with other state-of-the-art solutions.

A SOCIOLOGICAL ANALYSIS OF THE CHILDBEARING COEFFICIENT IN THE ALTAI REGION BASED ON METHOD OF FUZZY LINEAR REGRESSION

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Sergei Vladimirovich Varaksin

2017-06-01

Full Text Available Purpose. Construction of a mathematical model of the dynamics of childbearing change in the Altai region in 2000–2016, analysis of the dynamics of changes in birth rates for multiple age categories of women of childbearing age. Methodology. A auxiliary analysis element is the construction of linear mathematical models of the dynamics of childbearing by using fuzzy linear regression method based on fuzzy numbers. Fuzzy linear regression is considered as an alternative to standard statistical linear regression for short time series and unknown distribution law. The parameters of fuzzy linear and standard statistical regressions for childbearing time series were defined with using the built in language MatLab algorithm. Method of fuzzy linear regression is not used in sociological researches yet. Results. There are made the conclusions about the socio-demographic changes in society, the high efficiency of the demographic policy of the leadership of the region and the country, and the applicability of the method of fuzzy linear regression for sociological analysis.

The partial duration series method in regional index-flood modeling

DEFF Research Database (Denmark)

Madsen, Henrik; Rosbjerg, Dan

1997-01-01

A regional index-flood method based on the partial duration series model is introduced. The model comprises the assumptions of a Poisson-distributed number of threshold exceedances and generalized Pareto (GP) distributed peak magnitudes. The regional T-year event estimator is based on a regional...... estimator is superior to the at-site estimator even in extremely heterogenous regions, the performance of the regional estimator being relatively better in regions with a negative shape parameter. When the record length increases, the relative performance of the regional estimator decreases, but it is still...

Volumetric quantification of bone-implant contact using micro-computed tomography analysis based on region-based segmentation

Energy Technology Data Exchange (ETDEWEB)

Kang, Sung Won; Lee, Woo Jin; Choi, Soon Chul; Lee, Sam Sun; Heo, Min Suk; Huh, Kyung Hoe; Kim, Tae Il; Yi, Won Ji [Dental Research Institute, School of Dentistry, Seoul National University, Seoul (Korea, Republic of)

2015-03-15

We have developed a new method of segmenting the areas of absorbable implants and bone using region-based segmentation of micro-computed tomography (micro-CT) images, which allowed us to quantify volumetric bone-implant contact (VBIC) and volumetric absorption (VA). The simple threshold technique generally used in micro-CT analysis cannot be used to segment the areas of absorbable implants and bone. Instead, a region-based segmentation method, a region-labeling method, and subsequent morphological operations were successively applied to micro-CT images. The three-dimensional VBIC and VA of the absorbable implant were then calculated over the entire volume of the implant. Two-dimensional (2D) bone-implant contact (BIC) and bone area (BA) were also measured based on the conventional histomorphometric method. VA and VBIC increased significantly with as the healing period increased (p<0.05). VBIC values were significantly correlated with VA values (p<0.05) and with 2D BIC values (p<0.05). It is possible to quantify VBIC and VA for absorbable implants using micro-CT analysis using a region-based segmentation method.

Volumetric quantification of bone-implant contact using micro-computed tomography analysis based on region-based segmentation

International Nuclear Information System (INIS)

Kang, Sung Won; Lee, Woo Jin; Choi, Soon Chul; Lee, Sam Sun; Heo, Min Suk; Huh, Kyung Hoe; Kim, Tae Il; Yi, Won Ji

2015-01-01

We have developed a new method of segmenting the areas of absorbable implants and bone using region-based segmentation of micro-computed tomography (micro-CT) images, which allowed us to quantify volumetric bone-implant contact (VBIC) and volumetric absorption (VA). The simple threshold technique generally used in micro-CT analysis cannot be used to segment the areas of absorbable implants and bone. Instead, a region-based segmentation method, a region-labeling method, and subsequent morphological operations were successively applied to micro-CT images. The three-dimensional VBIC and VA of the absorbable implant were then calculated over the entire volume of the implant. Two-dimensional (2D) bone-implant contact (BIC) and bone area (BA) were also measured based on the conventional histomorphometric method. VA and VBIC increased significantly with as the healing period increased (p<0.05). VBIC values were significantly correlated with VA values (p<0.05) and with 2D BIC values (p<0.05). It is possible to quantify VBIC and VA for absorbable implants using micro-CT analysis using a region-based segmentation method.

GIS Supported Landslide Susceptibility Modeling at Regional Scale: An Expert-Based Fuzzy Weighting Method

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Christos Chalkias

2014-04-01

Full Text Available The main aim of this paper is landslide susceptibility assessment using fuzzy expert-based modeling. Factors that influence landslide occurrence, such as elevation, slope, aspect, lithology, land cover, precipitation and seismicity were considered. Expert-based fuzzy weighting (EFW approach was used to combine these factors for landslide susceptibility mapping (Peloponnese, Greece. This method produced a landslide susceptibility map of the investigated area. The landslides under investigation have more or less same characteristics: lateral based and downslope shallow movement of soils or rocks. The validation of the model reveals, that predicted susceptibility levels are found to be in good agreement with the past landslide occurrences. Hence, the obtained landslide susceptibility map could be acceptable, for landslide hazard prevention and mitigation at regional scale.

A composite method based on formal grammar and DNA structural features in detecting human polymerase II promoter region.

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Sutapa Datta

Full Text Available An important step in understanding gene regulation is to identify the promoter regions where the transcription factor binding takes place. Predicting a promoter region de novo has been a theoretical goal for many researchers for a long time. There exists a number of in silico methods to predict the promoter region de novo but most of these methods are still suffering from various shortcomings, a major one being the selection of appropriate features of promoter region distinguishing them from non-promoters. In this communication, we have proposed a new composite method that predicts promoter sequences based on the interrelationship between structural profiles of DNA and primary sequence elements of the promoter regions. We have shown that a Context Free Grammar (CFG can formalize the relationships between different primary sequence features and by utilizing the CFG, we demonstrate that an efficient parser can be constructed for extracting these relationships from DNA sequences to distinguish the true promoter sequences from non-promoter sequences. Along with CFG, we have extracted the structural features of the promoter region to improve upon the efficiency of our prediction system. Extensive experiments performed on different datasets reveals that our method is effective in predicting promoter sequences on a genome-wide scale and performs satisfactorily as compared to other promoter prediction techniques.

A Composite Method Based on Formal Grammar and DNA Structural Features in Detecting Human Polymerase II Promoter Region

Science.gov (United States)

Datta, Sutapa; Mukhopadhyay, Subhasis

2013-01-01

An important step in understanding gene regulation is to identify the promoter regions where the transcription factor binding takes place. Predicting a promoter region de novo has been a theoretical goal for many researchers for a long time. There exists a number of in silico methods to predict the promoter region de novo but most of these methods are still suffering from various shortcomings, a major one being the selection of appropriate features of promoter region distinguishing them from non-promoters. In this communication, we have proposed a new composite method that predicts promoter sequences based on the interrelationship between structural profiles of DNA and primary sequence elements of the promoter regions. We have shown that a Context Free Grammar (CFG) can formalize the relationships between different primary sequence features and by utilizing the CFG, we demonstrate that an efficient parser can be constructed for extracting these relationships from DNA sequences to distinguish the true promoter sequences from non-promoter sequences. Along with CFG, we have extracted the structural features of the promoter region to improve upon the efficiency of our prediction system. Extensive experiments performed on different datasets reveals that our method is effective in predicting promoter sequences on a genome-wide scale and performs satisfactorily as compared to other promoter prediction techniques. PMID:23437045

Strengthening regional innovation through network-based innovation brokering

OpenAIRE

Svare, Helge; Gausdal, Anne Haugen

2015-01-01

The primary objective of this paper is to demonstrate how regional innovation system theory may be translated into manageable micro-level methods with the potential for strengthening the productive dynamics of a regional innovation system. The paper meets this objective by presenting network-based innovation brokering (NBIB), a practical method designed using insights from regional innovation system theory and trust theory. Five cases from two Norwegian regional innovation networks show that ...

Local region power spectrum-based unfocused ship detection method in synthetic aperture radar images

Science.gov (United States)

Wei, Xiangfei; Wang, Xiaoqing; Chong, Jinsong

2018-01-01

Ships on synthetic aperture radar (SAR) images will be severely defocused and their energy will disperse into numerous resolution cells under long SAR integration time. Therefore, the image intensity of ships is weak and sometimes even overwhelmed by sea clutter on SAR image. Consequently, it is hard to detect the ships from SAR intensity images. A ship detection method based on local region power spectrum of SAR complex image is proposed. Although the energies of the ships are dispersed on SAR intensity images, their spectral energies are rather concentrated or will cause the power spectra of local areas of SAR images to deviate from that of sea surface background. Therefore, the key idea of the proposed method is to detect ships via the power spectra distortion of local areas of SAR images. The local region power spectrum of a moving target on SAR image is analyzed and the way to obtain the detection threshold through the probability density function (pdf) of the power spectrum is illustrated. Numerical P- and L-band airborne SAR ocean data are utilized and the detection results are also illustrated. Results show that the proposed method can well detect the unfocused ships, with a detection rate of 93.6% and a false-alarm rate of 8.6%. Moreover, by comparing with some other algorithms, it indicates that the proposed method performs better under long SAR integration time. Finally, the applicability of the proposed method and the way of parameters selection are also discussed.

Interest Aware Location-Based Recommender System Using Geo-Tagged Social Media

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Basma AlBanna

2016-12-01

Full Text Available Advances in location acquisition and mobile technologies led to the addition of the location dimension to Social Networks (SNs and to the emergence of a newer class called Location-Based Social Networks (LBSNs. While LBSNs are richer in their model and functions than SNs, they fail so far to attract as many users as SNs. On the other hand, SNs have large amounts of geo-tagged media that are under-utilized. In this paper, we propose an Interest-Aware Location-Based Recommender system (IALBR, which combines the advantages of both LBSNs and SNs, in order to provide interest-aware location-based recommendations. This recommender system is proposed as an extension to LBSNs. It is novel in: (1 utilizing the geo-content in both LBSNs and SNs; (2 ranking the recommendations based on a novel scoring method that maps to the user interests. It also works for passive users who are not active content contributors to the LBSN. This feature is critical to increase the number of LBSN users. Moreover, it helps with reducing the cold start problem, which is a common problem facing the new users of recommender systems who get random unsatisfying recommendations. This is due to the lack of user interest awareness, which is reliant on user history in most of the recommenders. We evaluated our system with a large-scale real dataset collected from foursquare with respect to precision, recall and the f-measure. We also compared the results with a ground truth system using metrics like the normalized discounted cumulative gain and the mean absolute error. The results confirm that the proposed IALBR generates more efficient recommendations than baselines in terms of interest awareness.

A Topic Space Oriented User Group Discovering Scheme in Social Network: A Trust Chain Based Interest Measuring Perspective

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Wang Dong

2016-01-01

Full Text Available Currently, user group has become an effective platform for information sharing and communicating among users in social network sites. In present work, we propose a single topic user group discovering scheme, which includes three phases: topic impact evaluation, interest degree measurement, and trust chain based discovering, to enable selecting influential topic and discovering users into a topic oriented group. Our main works include (1 an overview of proposed scheme and its related definitions; (2 topic space construction method based on topic relatedness clustering and its impact (influence degree and popularity degree evaluation; (3 a trust chain model to take user relation network topological information into account with a strength classification perspective; (4 an interest degree (user explicit and implicit interest degree evaluation method based on trust chain among users; and (5 a topic space oriented user group discovering method to group core users according to their explicit interest degrees and to predict ordinary users under implicit interest and user trust chain. Finally, experimental results are given to explain effectiveness and feasibility of our scheme.

Problem-based learning in regional anatomy education at Peking University.

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Wang, Jun; Zhang, Weiguang; Qin, Lihua; Zhao, Jing; Zhang, Shuyong; Gu, Jin; Zhou, Changman

2010-01-01

Problem-based learning (PBL) has been introduced to medical schools around the world and has increasingly become a popular pedagogical technique in Asian countries since 1990. Gross anatomy is a fundamental basic science course in virtually all medical training programs, and the methods used to teach it are under frequent scrutiny and revision. Students often struggle with the vast collection of new terms and complex relationships between structures that they must learn. To help students with this process, our department teaches separate systemic and regional anatomy courses, the latter in a PBL format. After three years of using PBL in our regional anatomy course, we have worked out a set of effective instructions that we would like to share with other medical schools. We report here evidence that our clinical PBL approach stimulates students' interest in learning and enhances anatomy education in a way that can foster better practices in our future medical work force. (c) 2010 American Association of Anatomists.

Classication of Status of the Region on Java Island using C4.5, CHAID, and CART Methods

Science.gov (United States)

Syaraswati, R. A.; Slamet, I.; Winarno, B.

2017-06-01

The indicator of region economic success can be measured by economic growth, presented by value of Gross Regional Domestic Product (GRDP). Java island has the biggest GDP contribution toward the Indonesian government, but not all of the region gives equality contribution. The C4.5, CHAID, and CART methods can be used for classifying the status of the region with nonparametric approach. The C4.5 and CHAID methods are non-binary decision tree, meanwhile the CART methods is binary decision tree. The purposes of this paper are to know how the classification and to determine the factors that influence on classification of the region. The dependent variable is status of the region which is divided into four categories based on Klassen typology. The result shows factors that have the biggest contribution on classification of status of the region on Java island based on C4.5 method are economic growth rate, electricity, gas, and water sector, and area. The factors that have the biggest contribution based on CHAID method are growth rate, manufacturing sector, and electricity, gas, and water sector, while based on CART method are growth rate, manufacturing sector, and electricity, gas, and water sector.

A framework of region-based dynamic image fusion

Institute of Scientific and Technical Information of China (English)

WANG Zhong-hua; QIN Zheng; LIU Yu

2007-01-01

A new framework of region-based dynamic image fusion is proposed. First, the technique of target detection is applied to dynamic images (image sequences) to segment images into different targets and background regions. Then different fusion rules are employed in different regions so that the target information is preserved as much as possible. In addition, steerable non-separable wavelet frame transform is used in the process of multi-resolution analysis, so the system achieves favorable characters of orientation and invariant shift. Compared with other image fusion methods, experimental results showed that the proposed method has better capabilities of target recognition and preserves clear background information.

Green's function matching method for adjoining regions having different masses

International Nuclear Information System (INIS)

Morgenstern Horing, Norman J

2006-01-01

We present a primer on the method of Green's function matching for the determination of the global Schroedinger Green's function for all space subject to joining conditions at an interface between two (or more) separate parts of the region having different masses. The object of this technique is to determine the full space Schroedinger Green's function in terms of the individual Green's functions of the constituent parts taken as if they were themselves extended to all space. This analytical method has had successful applications in the theory of surface states, and remains of interest for nanostructures

Trust regions in Kriging-based optimization with expected improvement

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Regis, Rommel G.

2016-06-01

The Kriging-based Efficient Global Optimization (EGO) method works well on many expensive black-box optimization problems. However, it does not seem to perform well on problems with steep and narrow global minimum basins and on high-dimensional problems. This article develops a new Kriging-based optimization method called TRIKE (Trust Region Implementation in Kriging-based optimization with Expected improvement) that implements a trust-region-like approach where each iterate is obtained by maximizing an Expected Improvement (EI) function within some trust region. This trust region is adjusted depending on the ratio of the actual improvement to the EI. This article also develops the Kriging-based CYCLONE (CYClic Local search in OptimizatioN using Expected improvement) method that uses a cyclic pattern to determine the search regions where the EI is maximized. TRIKE and CYCLONE are compared with EGO on 28 test problems with up to 32 dimensions and on a 36-dimensional groundwater bioremediation application in appendices supplied as an online supplement available at http://dx.doi.org/10.1080/0305215X.2015.1082350. The results show that both algorithms yield substantial improvements over EGO and they are competitive with a radial basis function method.

Ensemble-based Regional Climate Prediction: Political Impacts

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Miguel, E.; Dykema, J.; Satyanath, S.; Anderson, J. G.

2008-12-01

Accurate forecasts of regional climate, including temperature and precipitation, have significant implications for human activities, not just economically but socially. Sub Saharan Africa is a region that has displayed an exceptional propensity for devastating civil wars. Recent research in political economy has revealed a strong statistical relationship between year to year fluctuations in precipitation and civil conflict in this region in the 1980s and 1990s. To investigate how climate change may modify the regional risk of civil conflict in the future requires a probabilistic regional forecast that explicitly accounts for the community's uncertainty in the evolution of rainfall under anthropogenic forcing. We approach the regional climate prediction aspect of this question through the application of a recently demonstrated method called generalized scalar prediction (Leroy et al. 2009), which predicts arbitrary scalar quantities of the climate system. This prediction method can predict change in any variable or linear combination of variables of the climate system averaged over a wide range spatial scales, from regional to hemispheric to global. Generalized scalar prediction utilizes an ensemble of model predictions to represent the community's uncertainty range in climate modeling in combination with a timeseries of any type of observational data that exhibits sensitivity to the scalar of interest. It is not necessary to prioritize models in deriving with the final prediction. We present the results of the application of generalized scalar prediction for regional forecasts of temperature and precipitation and Sub Saharan Africa. We utilize the climate predictions along with the established statistical relationship between year-to-year rainfall variability in Sub Saharan Africa to investigate the potential impact of climate change on civil conflict within that region.

Spatio-temporal analysis of the extreme precipitation by the L-moment-based index-flood method in the Yangtze River Delta region, China

Science.gov (United States)

Yin, Yixing; Chen, Haishan; Xu, Chongyu; Xu, Wucheng; Chen, Changchun

2014-05-01

The regionalization methods which 'trade space for time' by including several at-site data records in the frequency analysis are an efficient tool to improve the reliability of extreme quantile estimates. With the main aims of improving the understanding of the regional frequency of extreme precipitation and providing scientific and practical background and assistance in formulating the regional development strategies for water resources management in one of the most developed and flood-prone regions in China, the Yangtze River Delta (YRD) region, in this paper, L-moment-based index-flood (LMIF) method, one of the popular regionalization methods, is used in the regional frequency analysis of extreme precipitation; attention was paid to inter-site dependence and its influence on the accuracy of quantile estimates, which hasn't been considered for most of the studies using LMIF method. Extensive data screening of stationarity, serial dependence and inter-site dependence was carried out first. The entire YRD region was then categorized into four homogeneous regions through cluster analysis and homogenous analysis. Based on goodness-of-fit statistic and L-moment ratio diagrams, Generalized extreme-value (GEV) and Generalized Normal (GNO) distributions were identified as the best-fit distributions for most of the sub regions. Estimated quantiles for each region were further obtained. Monte-Carlo simulation was used to evaluate the accuracy of the quantile estimates taking inter-site dependence into consideration. The results showed that the root mean square errors (RMSEs) were bigger and the 90% error bounds were wider with inter-site dependence than those with no inter-site dependence for both the regional growth curve and quantile curve. The spatial patterns of extreme precipitation with return period of 100 years were obtained which indicated that there are two regions with the highest precipitation extremes (southeastern coastal area of Zhejiang Province and the

Revisiting regional flood frequency analysis in Slovakia: the region-of-influence method vs. traditional regional approaches

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Gaál, Ladislav; Kohnová, Silvia; Szolgay, Ján.

2010-05-01

During the last 10-15 years, the Slovak hydrologists and water resources managers have been devoting considerable efforts to develop statistical tools for modelling probabilities of flood occurrence in a regional context. Initially, these models followed concepts to regional flood frequency analysis that were based on fixed regions, later the Hosking and Wallis's (HW; 1997) theory was adopted and modified. Nevertheless, it turned out to be that delineating homogeneous regions using these approaches is not a straightforward task, mostly due to the complex orography of the country. In this poster we aim at revisiting flood frequency analyses so far accomplished for Slovakia by adopting one of the pooling approaches, i.e. the region-of-influence (ROI) approach (Burn, 1990). In the ROI approach, unique pooling groups of similar sites are defined for each site under study. The similarity of sites is defined through Euclidean distance in the space of site attributes that had also proved applicability in former cluster analyses: catchment area, afforested area, hydrogeological catchment index and the mean annual precipitation. The homogeneity of the proposed pooling groups is evaluated by the built-in homogeneity test by Lu and Stedinger (1992). Two alternatives of the ROI approach are examined: in the first one the target size of the pooling groups is adjusted to the target return period T of the estimated flood quantiles, while in the other one, the target size is fixed, regardless of the target T. The statistical models of the ROI approach are inter-compared by the conventional regionalization approach based on the HW methodology where the parameters of flood frequency distributions were derived by means of L-moment statistics and a regional formula for the estimation of the index flood was derived by multiple regression methods using physiographic and climatic catchment characteristics. The inter-comparison of different frequency models is evaluated by means of the

MRI measurements of water diffusion: impact of region of interest selection on ischemic quantification

International Nuclear Information System (INIS)

Ozsunar, Yelda; Koseoglu, Kutsi; Huisman, Thierry A.G.M.; Koroshetz, Walter; Sorensen, A. Gregory

2004-01-01

Objective: To investigate the effect of ADC heterogeneity on region of interest (ROI) measurement of isotropic and anisotropic water diffusion in acute (<12 h) cerebral infarctions. Methods and materials: Full diffusion tensor images were retrospectively analyzed in 32 patients with acute cerebral infarction. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values were measured in ischemic lesions and in the corresponding contralateral, normal appearing brain by using four ROIs for each patient. The 2x2 pixel square ROIs were placed in the center, the lateral rim and the medial rim of the infarction. In addition, the whole volume of the infarction was measured using a free hand method. Each ROI value obtained from the ischemic lesion was normalized using contralateral normal ROI values. Results: The localization of the ROIs in relation to the ischemic lesion significantly affected ADC measurement (P<0.01, using Friedman test), but not FA measurement (P=0.25). Significant differences were found between ADC values of the center of the infarction versus whole volume (P<0.01), and medial rim versus whole volume of infarction (P<0.001) with variation of relative ADC values up to 11%. The differences of absolute ADC for these groups were 22 and 23%, respectively. The lowest ADC was found in the center, followed by medial rim, lateral rim and whole volume of infarction. Conclusion: ADC quantification may provide variable results depending on ROI method. The ADC and FA values, obtained from the center of infarction tend to be lower compared to the periphery. The researchers who try to compare studies or work on ischemic quantification should be aware of these differences and effects

The regional ground-based wind energy scheme of Pays-de-la-Loire: project, Assessment of the consultation on the regional wind energy project, final version, Prefect decree bearing approval of the regional ground-based wind energy scheme of Pays-de-la-Loire

International Nuclear Information System (INIS)

2012-08-01

This document first presents the regional wind energy scheme (SRE) as a framework for ground-based wind energy development, and as the wind energy component of the regional climate air energy scheme (SRCAE), briefly presents the elaboration approach, and indicates the legal scope of this scheme. The next part outlines the high rate development of wind energy in the Pays-de-la-Loire region. The third part reports the identification, analysis and assessment of areas of interest for the development of wind energy. Finally, the objective of this development by 2020 is estimated

Methods of formation of efficiency indexes of electric power sources integration in regional electric power systems

International Nuclear Information System (INIS)

Marder, L.I.; Myzin, A.I.

1993-01-01

A methodic approach to the grounding of the integration process efficiency within the Unified electric power system is given together with the selection of a rational areal structure and concentration of power-generating source capacities. Formation of an economic functional according to alternative scenavies including the cost components taking account of the regional interests is considered. A method for estimation and distribution of the effect from electric power production integration in the power systems under new economic conditions is proposed

Forming of the regional core transport network taking into account the allocation of alternative energy sources based on artificial intelligence methods

Directory of Open Access Journals (Sweden)

Marina ZHURAVSKAYA

2014-12-01

Full Text Available In the modern world the alternative energy sources, which considerably depend on a region, play more and more significant role. However, the transition of regions to new energy sources lead to the change of transport and logistic network configuration. The formation of optimal core transport network today is a guarantee of the successful economic development of a region tomorrow. The present article studies the issue of advanced core transport network development in a region based on the experience of European and Asian countries and the opportunity to adapt the best foreign experience to Russian conditions. On the basis of artificial intelligence methods for forest industry complex of Sverdlovskaya Oblast the algorithm of problem solution of an optimal logistic infrastructure allocation is offered and some results of a regional transport network are presented. These methods allowed to solve the set task in the conditions of information uncertainty. There are suggestions on the improvement of transport and logistic network in the territory of Sverdlovskaya Oblast. Traditionally the logistics of mineral fuel plays main role in regions development. Actually it is required to develop logistic strategic plans to be able to provide different possibilities of power-supply, flexible enough to change with the population density, transport infrastructure and demographics of different regions. The problem of logistic centers allocation was studied by many authors. The approach, offered by the authors of this paper is to solve the set of tasks by applying artificial intelligence methods, such as fuzzy set theory and genetic algorithms.

A REGION-BASED MULTI-SCALE APPROACH FOR OBJECT-BASED IMAGE ANALYSIS

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T. Kavzoglu

2016-06-01

Full Text Available Within the last two decades, object-based image analysis (OBIA considering objects (i.e. groups of pixels instead of pixels has gained popularity and attracted increasing interest. The most important stage of the OBIA is image segmentation that groups spectrally similar adjacent pixels considering not only the spectral features but also spatial and textural features. Although there are several parameters (scale, shape, compactness and band weights to be set by the analyst, scale parameter stands out the most important parameter in segmentation process. Estimating optimal scale parameter is crucially important to increase the classification accuracy that depends on image resolution, image object size and characteristics of the study area. In this study, two scale-selection strategies were implemented in the image segmentation process using pan-sharped Qickbird-2 image. The first strategy estimates optimal scale parameters for the eight sub-regions. For this purpose, the local variance/rate of change (LV-RoC graphs produced by the ESP-2 tool were analysed to determine fine, moderate and coarse scales for each region. In the second strategy, the image was segmented using the three candidate scale values (fine, moderate, coarse determined from the LV-RoC graph calculated for whole image. The nearest neighbour classifier was applied in all segmentation experiments and equal number of pixels was randomly selected to calculate accuracy metrics (overall accuracy and kappa coefficient. Comparison of region-based and image-based segmentation was carried out on the classified images and found that region-based multi-scale OBIA produced significantly more accurate results than image-based single-scale OBIA. The difference in classification accuracy reached to 10% in terms of overall accuracy.

Latency-Based and Psychophysiological Measures of Sexual Interest Show Convergent and Concurrent Validity.

Science.gov (United States)

Ó Ciardha, Caoilte; Attard-Johnson, Janice; Bindemann, Markus

2018-04-01

Latency-based measures of sexual interest require additional evidence of validity, as do newer pupil dilation approaches. A total of 102 community men completed six latency-based measures of sexual interest. Pupillary responses were recorded during three of these tasks and in an additional task where no participant response was required. For adult stimuli, there was a high degree of intercorrelation between measures, suggesting that tasks may be measuring the same underlying construct (convergent validity). In addition to being correlated with one another, measures also predicted participants' self-reported sexual interest, demonstrating concurrent validity (i.e., the ability of a task to predict a more validated, simultaneously recorded, measure). Latency-based and pupillometric approaches also showed preliminary evidence of concurrent validity in predicting both self-reported interest in child molestation and viewing pornographic material containing children. Taken together, the study findings build on the evidence base for the validity of latency-based and pupillometric measures of sexual interest.

3D Wavelet-Based Filter and Method

Science.gov (United States)

Moss, William C.; Haase, Sebastian; Sedat, John W.

2008-08-12

A 3D wavelet-based filter for visualizing and locating structural features of a user-specified linear size in 2D or 3D image data. The only input parameter is a characteristic linear size of the feature of interest, and the filter output contains only those regions that are correlated with the characteristic size, thus denoising the image.

Double tracer autoradiographic method for sequential evaluation of regional cerebral perfusion

International Nuclear Information System (INIS)

Matsuda, H.; Tsuji, S.; Oba, H.; Kinuya, K.; Terada, H.; Sumiya, H.; Shiba, K.; Mori, H.; Hisada, K.; Maeda, T.

1989-01-01

A new double tracer autoradiographic method for the sequential evaluation of altered regional cerebral perfusion in the same animal is presented. This method is based on the sequential injection of two tracers, 99m Tc-hexamethylpropyleneamine oxime and N-isopropyl-( 125 I)p-iodoamphetamine. This method is validated in the assessment of brovincamine effects on regional cerebral perfusion in an experimental model of chronic brain ischemia in the rat. The drug enhanced perfusion recovery in low-flow areas, selectively in surrounding areas of infarction. The results suggest that this technique is of potential use in the study of neuropharmacological effects applied during the experiment

IMPLEMENTATION OF SIMPLE ADDITIVE WEIGHTING (SAW METHODE IN DETERMINING HIGH SCHOOL STUDENT’S INTEREST

Directory of Open Access Journals (Sweden)

Prind Triajeng Pungkasanti

2017-09-01

Full Text Available The Ministry of Research, Technology, and Higher Education of Republic of Indonesia has set a regulation about curriculum applied in education field named Kurikulum 2013. One of the subsections in the Kurikulum 2013 regulates all requirements of majoring in high school. High school students determine their major based on Kurrikulum 2013 as they are on the 10th grade. The purpose of the majoring in education is to allow children development based on their skills and interests, because before, majoring have been done based on scores obtained. The main problem is the majoring requirements considered are admission test score and Junior High School National Test score. Both scores are not sufficient enough to determine the students major therefore academic aptitude test score is required. In term of weighting, the school has not been imposed the weighting system so the scores obtained is the average of admission test score and national test score. Based on the issue above, a solution required to solve the issue using a method. Method used in this research is Simple Additive Weighting (SAW, wherein this methode is looking for the weighted sum of performance rate on every alternative of atributes. This research provides the information about which potential students is suitable to enter the science major and social major so this results can be used as consideration of school decisions.

Spine segmentation from C-arm CT data sets: application to region-of-interest volumes for spinal interventions

Science.gov (United States)

Buerger, C.; Lorenz, C.; Babic, D.; Hoppenbrouwers, J.; Homan, R.; Nachabe, R.; Racadio, J. M.; Grass, M.

2017-03-01

Spinal fusion is a common procedure to stabilize the spinal column by fixating parts of the spine. In such procedures, metal screws are inserted through the patients back into a vertebra, and the screws of adjacent vertebrae are connected by metal rods to generate a fixed bridge. In these procedures, 3D image guidance for intervention planning and outcome control is required. Here, for anatomical guidance, an automated approach for vertebra segmentation from C-arm CT images of the spine is introduced and evaluated. As a prerequisite, 3D C-arm CT images are acquired covering the vertebrae of interest. An automatic model-based segmentation approach is applied to delineate the outline of the vertebrae of interest. The segmentation approach is based on 24 partial models of the cervical, thoracic and lumbar vertebrae which aggregate information about (i) the basic shape itself, (ii) trained features for image based adaptation, and (iii) potential shape variations. Since the volume data sets generated by the C-arm system are limited to a certain region of the spine the target vertebra and hence initial model position is assigned interactively. The approach was trained and tested on 21 human cadaver scans. A 3-fold cross validation to ground truth annotations yields overall mean segmentation errors of 0.5 mm for T1 to 1.1 mm for C6. The results are promising and show potential to support the clinician in pedicle screw path and rod planning to allow accurate and reproducible insertions.

Regional analysis of annual maximum rainfall using TL-moments method

Science.gov (United States)

Shabri, Ani Bin; Daud, Zalina Mohd; Ariff, Noratiqah Mohd

2011-06-01

Information related to distributions of rainfall amounts are of great importance for designs of water-related structures. One of the concerns of hydrologists and engineers is the probability distribution for modeling of regional data. In this study, a novel approach to regional frequency analysis using L-moments is revisited. Subsequently, an alternative regional frequency analysis using the TL-moments method is employed. The results from both methods were then compared. The analysis was based on daily annual maximum rainfall data from 40 stations in Selangor Malaysia. TL-moments for the generalized extreme value (GEV) and generalized logistic (GLO) distributions were derived and used to develop the regional frequency analysis procedure. TL-moment ratio diagram and Z-test were employed in determining the best-fit distribution. Comparison between the two approaches showed that the L-moments and TL-moments produced equivalent results. GLO and GEV distributions were identified as the most suitable distributions for representing the statistical properties of extreme rainfall in Selangor. Monte Carlo simulation was used for performance evaluation, and it showed that the method of TL-moments was more efficient for lower quantile estimation compared with the L-moments.

The effects of alignment quality, distance calculation method, sequence filtering, and region on the analysis of 16S rRNA gene-based studies.

Directory of Open Access Journals (Sweden)

Patrick D Schloss

Full Text Available Pyrosequencing of PCR-amplified fragments that target variable regions within the 16S rRNA gene has quickly become a powerful method for analyzing the membership and structure of microbial communities. This approach has revealed and introduced questions that were not fully appreciated by those carrying out traditional Sanger sequencing-based methods. These include the effects of alignment quality, the best method of calculating pairwise genetic distances for 16S rRNA genes, whether it is appropriate to filter variable regions, and how the choice of variable region relates to the genetic diversity observed in full-length sequences. I used a diverse collection of 13,501 high-quality full-length sequences to assess each of these questions. First, alignment quality had a significant impact on distance values and downstream analyses. Specifically, the greengenes alignment, which does a poor job of aligning variable regions, predicted higher genetic diversity, richness, and phylogenetic diversity than the SILVA and RDP-based alignments. Second, the effect of different gap treatments in determining pairwise genetic distances was strongly affected by the variation in sequence length for a region; however, the effect of different calculation methods was subtle when determining the sample's richness or phylogenetic diversity for a region. Third, applying a sequence mask to remove variable positions had a profound impact on genetic distances by muting the observed richness and phylogenetic diversity. Finally, the genetic distances calculated for each of the variable regions did a poor job of correlating with the full-length gene. Thus, while it is tempting to apply traditional cutoff levels derived for full-length sequences to these shorter sequences, it is not advisable. Analysis of beta-diversity metrics showed that each of these factors can have a significant impact on the comparison of community membership and structure. Taken together, these results

Academic or Community Resource? Stakeholder Interests and Collection Management at Charles Sturt University Regional Archives, 1973-2003

Science.gov (United States)

Boadle, Don

2003-01-01

This analysis of the transformation of the Charles Sturt University Regional Archives from a library special collection to a multi-function regional repository highlights the importance of stakeholder interests in determining institutional configurations and collection development priorities. It also demonstrates the critical importance of…

Spatial Data Envelopment Analysis Method for the Evaluation of Regional Infrastructure Disparities

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Birutė Galinienė

2012-12-01

Full Text Available Purpose—to achieve a more detailed assessment of regional differences, exploring regional infrastructure and human capital usage efficiency and to display analysis capabilities of spatial data efficient frontier method.Design/methodology/approach—the data envelopment analysis (DEA is applied to find the efficient frontier, which extends the application of production function of the regions. This method of mathematical programming optimization allows assessing the effectiveness of the regional spatial aspects presented. In recent studies this method is applied for evaluating the European Union regional policy issues.Findings—the application of DEA reveals its feasibility for regional input and output studies to evaluate more detailed and more reasonable fund allocation between Lithuanian regions. This analysis shows that in the comparatively efficient Lithuanian regions, such as Vilnius and Klaipėda, “the bottleneck” of usage of transport infrastructure and regional specific human capital is reached. It is stated that decision-making units could enhance region attractiveness for private investors by improving indirect factors in these regions. For practical significance of the study the results are compared with German regional analysis, conducted by Schaffer and other researchers (2011.Practical implications—the practical value of this work is based on giving more accurate planning tools for fund allocation decisions in Lithuanian regions while planning infrastructure and human capital development. The regional indicators were analyzed for 2010.Research type—case study.

Stochastic rainfall synthesis for urban applications using different regionalization methods

Science.gov (United States)

Callau Poduje, A. C.; Leimbach, S.; Haberlandt, U.

2017-12-01

The proper design and efficient operation of urban drainage systems require long and continuous rainfall series in a high temporal resolution. Unfortunately, these time series are usually available in a few locations and it is therefore suitable to develop a stochastic precipitation model to generate rainfall in locations without observations. The model presented is based on an alternating renewal process and involves an external and an internal structure. The members of these structures are described by probability distributions which are site specific. Different regionalization methods based on site descriptors are presented which are used for estimating the distributions for locations without observations. Regional frequency analysis, multiple linear regressions and a vine-copula method are applied for this purpose. An area located in the north-west of Germany is used to compare the different methods and involves a total of 81 stations with 5 min rainfall records. The site descriptors include information available for the whole region: position, topography and hydrometeorologic characteristics which are estimated from long term observations. The methods are compared directly by cross validation of different rainfall statistics. Given that the model is stochastic the evaluation is performed based on ensembles of many long synthetic time series which are compared with observed ones. The performance is as well indirectly evaluated by setting up a fictional urban hydrological system to test the capability of the different methods regarding flooding and overflow characteristics. The results show a good representation of the seasonal variability and good performance in reproducing the sample statistics of the rainfall characteristics. The copula based method shows to be the most robust of the three methods. Advantages and disadvantages of the different methods are presented and discussed.

MOCC: A Fast and Robust Correlation-Based Method for Interest Point Matching under Large Scale Changes

Science.gov (United States)

Zhao, Feng; Huang, Qingming; Wang, Hao; Gao, Wen

2010-12-01

Similarity measures based on correlation have been used extensively for matching tasks. However, traditional correlation-based image matching methods are sensitive to rotation and scale changes. This paper presents a fast correlation-based method for matching two images with large rotation and significant scale changes. Multiscale oriented corner correlation (MOCC) is used to evaluate the degree of similarity between the feature points. The method is rotation invariant and capable of matching image pairs with scale changes up to a factor of 7. Moreover, MOCC is much faster in comparison with the state-of-the-art matching methods. Experimental results on real images show the robustness and effectiveness of the proposed method.

Mapping the regional influence of genetics on brain structure variability--a tensor-based morphometry study.

Science.gov (United States)

Brun, Caroline C; Leporé, Natasha; Pennec, Xavier; Lee, Agatha D; Barysheva, Marina; Madsen, Sarah K; Avedissian, Christina; Chou, Yi-Yu; de Zubicaray, Greig I; McMahon, Katie L; Wright, Margaret J; Toga, Arthur W; Thompson, Paul M

2009-10-15

Genetic and environmental factors influence brain structure and function profoundly. The search for heritable anatomical features and their influencing genes would be accelerated with detailed 3D maps showing the degree to which brain morphometry is genetically determined. As part of an MRI study that will scan 1150 twins, we applied Tensor-Based Morphometry to compute morphometric differences in 23 pairs of identical twins and 23 pairs of same-sex fraternal twins (mean age: 23.8+/-1.8 SD years). All 92 twins' 3D brain MRI scans were nonlinearly registered to a common space using a Riemannian fluid-based warping approach to compute volumetric differences across subjects. A multi-template method was used to improve volume quantification. Vector fields driving each subject's anatomy onto the common template were analyzed to create maps of local volumetric excesses and deficits relative to the standard template. Using a new structural equation modeling method, we computed the voxelwise proportion of variance in volumes attributable to additive (A) or dominant (D) genetic factors versus shared environmental (C) or unique environmental factors (E). The method was also applied to various anatomical regions of interest (ROIs). As hypothesized, the overall volumes of the brain, basal ganglia, thalamus, and each lobe were under strong genetic control; local white matter volumes were mostly controlled by common environment. After adjusting for individual differences in overall brain scale, genetic influences were still relatively high in the corpus callosum and in early-maturing brain regions such as the occipital lobes, while environmental influences were greater in frontal brain regions that have a more protracted maturational time-course.

MOCC: A Fast and Robust Correlation-Based Method for Interest Point Matching under Large Scale Changes

OpenAIRE

Wang Hao; Gao Wen; Huang Qingming; Zhao Feng

2010-01-01

Similarity measures based on correlation have been used extensively for matching tasks. However, traditional correlation-based image matching methods are sensitive to rotation and scale changes. This paper presents a fast correlation-based method for matching two images with large rotation and significant scale changes. Multiscale oriented corner correlation (MOCC) is used to evaluate the degree of similarity between the feature points. The method is rotation invariant and capable of matchin...

Algorithm based on regional separation for automatic grain boundary extraction using improved mean shift method

Science.gov (United States)

Zhenying, Xu; Jiandong, Zhu; Qi, Zhang; Yamba, Philip

2018-06-01

Metallographic microscopy shows that the vast majority of metal materials are composed of many small grains; the grain size of a metal is important for determining the tensile strength, toughness, plasticity, and other mechanical properties. In order to quantitatively evaluate grain size in metals, grain boundaries must be identified in metallographic images. Based on the phenomenon of grain boundary blurring or disconnection in metallographic images, this study develops an algorithm based on regional separation for automatically extracting grain boundaries by an improved mean shift method. Experimental observation shows that the grain boundaries obtained by the proposed algorithm are highly complete and accurate. This research has practical value because the proposed algorithm is suitable for grain boundary extraction from most metallographic images.

MOCC: A Fast and Robust Correlation-Based Method for Interest Point Matching under Large Scale Changes

Directory of Open Access Journals (Sweden)

Wang Hao

2010-01-01

Full Text Available Similarity measures based on correlation have been used extensively for matching tasks. However, traditional correlation-based image matching methods are sensitive to rotation and scale changes. This paper presents a fast correlation-based method for matching two images with large rotation and significant scale changes. Multiscale oriented corner correlation (MOCC is used to evaluate the degree of similarity between the feature points. The method is rotation invariant and capable of matching image pairs with scale changes up to a factor of 7. Moreover, MOCC is much faster in comparison with the state-of-the-art matching methods. Experimental results on real images show the robustness and effectiveness of the proposed method.

Hyperspectral Based Skin Detection for Person of Interest Identification

Science.gov (United States)

2015-03-01

short-wave infrared VIS visible spectrum PCA principal component analysis FCBF Fast Correlation- Based Filter POI person of interest ANN artificial neural...an artificial neural network (ANN) that is created in MATLAB® using the Neural Network Toolbox to identify a POI based on their skin spectral data. A...identifying a POI based on skin spectral data. She identified an optimal feature subset to be used with the hyperspectral data she collected using a

Regional projection of climate impact indices over the Mediterranean region

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Casanueva, Ana; Frías, M.; Dolores; Herrera, Sixto; Bedia, Joaquín; San Martín, Daniel; Gutiérrez, José Manuel; Zaninovic, Ksenija

2014-05-01

Climate Impact Indices (CIIs) are being increasingly used in different socioeconomic sectors to transfer information about climate change impacts and risks to stakeholders. CIIs are typically based on different weather variables such as temperature, wind speed, precipitation or humidity and comprise, in a single index, the relevant meteorological information for the particular impact sector (in this study wildfires and tourism). This dependence on several climate variables poses important limitations to the application of statistical downscaling techniques, since physical consistency among variables is required in most cases to obtain reliable local projections. The present study assesses the suitability of the "direct" downscaling approach, in which the downscaling method is directly applied to the CII. In particular, for illustrative purposes, we consider two popular indices used in the wildfire and tourism sectors, the Fire Weather Index (FWI) and the Physiological Equivalent Temperature (PET), respectively. As an example, two case studies are analysed over two representative Mediterranean regions of interest for the EU CLIM-RUN project: continental Spain for the FWI and Croatia for the PET. Results obtained with this "direct" downscaling approach are similar to those found from the application of the statistical downscaling to the individual meteorological drivers prior to the index calculation ("component" downscaling) thus, a wider range of statistical downscaling methods could be used. As an illustration, future changes in both indices are projected by applying two direct statistical downscaling methods, analogs and linear regression, to the ECHAM5 model. Larger differences were found between the two direct statistical downscaling approaches than between the direct and the component approaches with a single downscaling method. While these examples focus on particular indices and Mediterranean regions of interest for CLIM-RUN stakeholders, the same study

Reference voltage calculation method based on zero-sequence component optimisation for a regional compensation DVR

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Jian, Le; Cao, Wang; Jintao, Yang; Yinge, Wang

2018-04-01

This paper describes the design of a dynamic voltage restorer (DVR) that can simultaneously protect several sensitive loads from voltage sags in a region of an MV distribution network. A novel reference voltage calculation method based on zero-sequence voltage optimisation is proposed for this DVR to optimise cost-effectiveness in compensation of voltage sags with different characteristics in an ungrounded neutral system. Based on a detailed analysis of the characteristics of voltage sags caused by different types of faults and the effect of the wiring mode of the transformer on these characteristics, the optimisation target of the reference voltage calculation is presented with several constraints. The reference voltages under all types of voltage sags are calculated by optimising the zero-sequence component, which can reduce the degree of swell in the phase-to-ground voltage after compensation to the maximum extent and can improve the symmetry degree of the output voltages of the DVR, thereby effectively increasing the compensation ability. The validity and effectiveness of the proposed method are verified by simulation and experimental results.

Voxel based statistical analysis method for microPET studies to assess the cerebral glucose metabolism in cat deafness model: comparison to ROI based method

International Nuclear Information System (INIS)

Kim, Jin Su; Lee, Jae Sung; Park, Min Hyun; Lee, Jong Jin; Kang, Hye Jin; Lee, Hyo Jeong; Oh, Seung Ha; Kim, Chong Sun; Jung, June Key; Lee, Myung Chul; Lee, Dong Soo; Lim, Sang Moo

2005-01-01

Imaging research on the brain of sensory-deprived cats using small animal PET scanner has gained interest since the abundant information about the sensory system of ths animal is available and close examination of the brain is possible due to larger size of its brain than mouse or rat. In this study, we have established the procedures for 3D voxel-based statistical analysis (SPM) of FDG PET image of cat brain, and confirmed using ROI based-method. FDG PET scans of 4 normal and 4 deaf cats were acquired for 30 minutes using microPET R4 scanner. Only the brain cortices were extracted using a masking and threshold method to facilitate spatial normalization. After spatial normalization and smoothing, 3D voxel-wise and ROI based t-test were performed to identify the regions with significant different FDG uptake between the normal and deaf cats. In ROI analysis, 26 ROIs were drawn on both hemispheres, and regional mean pixel value in each ROI was normalized to the global mean of the brain. Cat brains were spatially normalized well onto the target brain due to the removal of background activity. When cerebral glucose metabolism of deaf cats were compared to the normal controls after removing the effects of the global count, the glucose metabolism in the auditory cortex, head of caudate nucleus, and thalamus in both hemispheres of the deaf cats was significantly lower than that of the controls (P<0.01). No area showed a significantly increased metabolism in the deaf cats even in higher significance level (P<0.05). ROI analysis also showed significant reduction of glucose metabolism in the same region. This study established and confirmed a method for voxel-based analysis of animal PET data of cat brain, which showed high localization accuracy and specificity and was useful for examining the cerebral glucose metabolism in a cat cortical deafness model

Voxel based statistical analysis method for microPET studies to assess the cerebral glucose metabolism in cat deafness model: comparison to ROI based method

Energy Technology Data Exchange (ETDEWEB)

Kim, Jin Su; Lee, Jae Sung; Park, Min Hyun; Lee, Jong Jin; Kang, Hye Jin; Lee, Hyo Jeong; Oh, Seung Ha; Kim, Chong Sun; Jung, June Key; Lee, Myung Chul; Lee, Dong Soo [Seoul National University College of Medicine, Seoul (Korea, Republic of); Lim, Sang Moo [KIRAMS, Seoul (Korea, Republic of)

2005-07-01

Imaging research on the brain of sensory-deprived cats using small animal PET scanner has gained interest since the abundant information about the sensory system of ths animal is available and close examination of the brain is possible due to larger size of its brain than mouse or rat. In this study, we have established the procedures for 3D voxel-based statistical analysis (SPM) of FDG PET image of cat brain, and confirmed using ROI based-method. FDG PET scans of 4 normal and 4 deaf cats were acquired for 30 minutes using microPET R4 scanner. Only the brain cortices were extracted using a masking and threshold method to facilitate spatial normalization. After spatial normalization and smoothing, 3D voxel-wise and ROI based t-test were performed to identify the regions with significant different FDG uptake between the normal and deaf cats. In ROI analysis, 26 ROIs were drawn on both hemispheres, and regional mean pixel value in each ROI was normalized to the global mean of the brain. Cat brains were spatially normalized well onto the target brain due to the removal of background activity. When cerebral glucose metabolism of deaf cats were compared to the normal controls after removing the effects of the global count, the glucose metabolism in the auditory cortex, head of caudate nucleus, and thalamus in both hemispheres of the deaf cats was significantly lower than that of the controls (P<0.01). No area showed a significantly increased metabolism in the deaf cats even in higher significance level (P<0.05). ROI analysis also showed significant reduction of glucose metabolism in the same region. This study established and confirmed a method for voxel-based analysis of animal PET data of cat brain, which showed high localization accuracy and specificity and was useful for examining the cerebral glucose metabolism in a cat cortical deafness model.

Standardization and awtomatic plotting of zones of interest in processing scintigrams of a head and neck

International Nuclear Information System (INIS)

Ivanov, Yu.N.; Prikhod'ko, A.G.; Chelyshev, M.M.

1982-01-01

A method for determining quantitative indeces of the level of accumulation and localization of lesion centers in scintigrams of head and neck by means of automatic plotting of standardized zones of interest, using the PDP-11/34 computer, is suggested. A supposition that for anatomic regions of head and neck, which are of interest for an investigator, relatively constant forms and inconsiderable variability of sizes are characteristic lies in the basis of the method suggested. Under such conditions the task of standardization and automatic plotting of zones of interest is reduced to determination of anatomic region boundaries relatively reference points selected. On the basis of analysis of archives data 26 zones of interest have been selected. Names of the zones and their abbreviations are presented. A conclusion is made that the suggested method of scintigram processing permits to increase the accuracy of localization determination of pathological centers. At that, the objectivity of diagnostic solution increases and reproducibility and comparability of different investigation results are ensured

History-Based Instruction Enriched with Various Sources of Situational Interest on the Topic of the Atom: the Effect on Students' Achievement and Interest

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Pekdağ, Bülent; Azizoğlu, Nursen

2018-05-01

This study examines the effect of history-based instruction on the topic of the atom on students' academic achievement and their interest in the history of science, investigating as well the relationship between student interest and academic achievement. The sample of the study consisted of two groups of freshman students from an undergraduate elementary science teachers program. The same chemistry instructor taught the groups, which were randomly assigned as an experimental and a control group. The students in the control group received traditional teacher-centered instruction, while the experimental group students were taught the topic of the atom using history-based instruction enriched with various sources of situational interest such as novelty, autonomy, social involvement, and knowledge acquisition (NASK). Data gathering instruments were the Atom Achievement Test and the History of Science Interest Scale, administered to both of the groups before and after the instruction. The data were analyzed with the independent-samples t test, the paired-samples t test, and one-way ANCOVA statistical analysis. The results showed that the history-based instruction including NASK was more effective than traditional instruction in improving the students' learning of the subject of the atom as well as in stimulating and improving students' interest in the history of science. Further, students with high interest displayed significantly better achievement than students with low interest. The better learning of the topic of the atom was more pronounced in the case of students with a high interest in the history of science compared to students with moderate or low interest.

Influence of parameter settings in voxel-based morphometry 8. Using DARTEL and region-of-interest on reproducibility in gray matter volumetry.

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Goto, M; Abe, O; Aoki, S; Hayashi, N; Miyati, T; Takao, H; Matsuda, H; Yamashita, F; Iwatsubo, T; Mori, H; Kunimatsu, A; Ino, K; Yano, K; Ohtomo, K

2015-01-01

To investigate whether reproducibility of gray matter volumetry is influenced by parameter settings for VBM 8 using Diffeomorphic Anatomical Registration Through Exponentiated Lie Algebra (DARTEL) with region-of-interest (ROI) analyses. We prepared three-dimensional T1-weighted magnetic resonance images (3D-T1WIs) of 21 healthy subjects. All subjects were imaged with each of five MRI systems. Voxel-based morphometry 8 (VBM 8) and WFU PickAtlas software were used for gray matter volumetry. The bilateral ROI labels used were those provided as default settings with the software: Frontal Lobe, Hippocampus, Occipital Lobe, Orbital Gyrus, Parietal Lobe, Putamen, and Temporal Lobe. All 3D-T1WIs were segmented to gray matter with six parameters of VBM 8, with each parameter having between three and eight selectable levels. Reproducibility was evaluated as the standard deviation (mm³) of measured values for the five MRI systems. Reproducibility was influenced by 'Bias regularization (BiasR)', 'Bias FWHM', and 'De-noising filter' settings, but not by 'MRF weighting', 'Sampling distance', or 'Warping regularization' settings. Reproducibility in BiasR was influenced by ROI. Superior reproducibility was observed in Frontal Lobe with the BiasR1 setting, and in Hippocampus, Parietal Lobe, and Putamen with the BiasR3*, BiasR1, and BiasR5 settings, respectively. Reproducibility of gray matter volumetry was influenced by parameter settings in VBM 8 using DARTEL and ROI. In multi-center studies, the use of appropriate settings in VBM 8 with DARTEL results in reduced scanner effect.

Is ASEAN Ready for Banking Integration? Evidence from Interest Rate Convergence

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Fazelina Sahul Hamid

2016-07-01

Full Text Available Convergence in prices or returns of assets with similar characteristics indicates that the financial market is integrated with regional markets. This paper is the first that test of the movements of interest rates in ASEAN banking sector for the period 1990 - 2012. The empirical analysis is based on a yearly panel of commercial bank interest rate data from 5 ASEAN countries, namely, Indonesia, Malaysia, Philippines, Singapore and Thailand. We assessed the degree and speed of interest rate convergence using beta and sigma convergence method. The findings show that the difference and the dispersion in the interbank rates have reduced since the Asian financial crisis and this trend has become stronger after the Global financial crisis. The findings of this study confirm that interest rates in the ASEAN banking sector are converging. This provides evidence that the ASEAN banking sector is ready for financial integration.

Regional frequency analysis of extreme rainfalls using partial L moments method

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Zakaria, Zahrahtul Amani; Shabri, Ani

2013-07-01

An approach based on regional frequency analysis using L moments and LH moments are revisited in this study. Subsequently, an alternative regional frequency analysis using the partial L moments (PL moments) method is employed, and a new relationship for homogeneity analysis is developed. The results were then compared with those obtained using the method of L moments and LH moments of order two. The Selangor catchment, consisting of 37 sites and located on the west coast of Peninsular Malaysia, is chosen as a case study. PL moments for the generalized extreme value (GEV), generalized logistic (GLO), and generalized Pareto distributions were derived and used to develop the regional frequency analysis procedure. PL moment ratio diagram and Z test were employed in determining the best-fit distribution. Comparison between the three approaches showed that GLO and GEV distributions were identified as the suitable distributions for representing the statistical properties of extreme rainfall in Selangor. Monte Carlo simulation used for performance evaluation shows that the method of PL moments would outperform L and LH moments methods for estimation of large return period events.

Segmentation of Multi-Isotope Imaging Mass Spectrometry Data for Semi-Automatic Detection of Regions of Interest

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Poczatek, J. Collin; Turck, Christoph W.; Lechene, Claude

2012-01-01

Multi-isotope imaging mass spectrometry (MIMS) associates secondary ion mass spectrometry (SIMS) with detection of several atomic masses, the use of stable isotopes as labels, and affiliated quantitative image-analysis software. By associating image and measure, MIMS allows one to obtain quantitative information about biological processes in sub-cellular domains. MIMS can be applied to a wide range of biomedical problems, in particular metabolism and cell fate [1], [2], [3]. In order to obtain morphologically pertinent data from MIMS images, we have to define regions of interest (ROIs). ROIs are drawn by hand, a tedious and time-consuming process. We have developed and successfully applied a support vector machine (SVM) for segmentation of MIMS images that allows fast, semi-automatic boundary detection of regions of interests. Using the SVM, high-quality ROIs (as compared to an expert's manual delineation) were obtained for 2 types of images derived from unrelated data sets. This automation simplifies, accelerates and improves the post-processing analysis of MIMS images. This approach has been integrated into “Open MIMS,” an ImageJ-plugin for comprehensive analysis of MIMS images that is available online at http://www.nrims.hms.harvard.edu/NRIMS_ImageJ.php. PMID:22347386

Effective management models and methods of economic educations in regional industrial complexes

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Andrey Gennadyevich Butrin

2014-06-01

Full Text Available In the article, the methodical bases of management by the integrated industrial enterprises is developed according to the indicators of sustainable economic development of the region. The scope of the research is the region as the difficult mesosystem consisting of logistic clusters. The subject matter of the research is the organizational and economic relations developing in the course of interaction of participants of the regional economy as mesosystems. The models and methods of management by the large economic systems in the economy of the industrially developed region are developed; the organizational and economic essence of a logistic cluster as the subject of the regional economy us revealed. The mechanism of management by the integrated enterprises with using the cluster approach, technologies of logistics, management of supply chains is offered. They allow to the management of an enterprises to make scientifically reasonable effective decisions developing programs of supply, economic production and realization of finished goods in the close connection with programs of regional economic development.

Stereoscopic Visual Attention-Based Regional Bit Allocation Optimization for Multiview Video Coding

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Dai Qionghai

2010-01-01

Full Text Available We propose a Stereoscopic Visual Attention- (SVA- based regional bit allocation optimization for Multiview Video Coding (MVC by the exploiting visual redundancies from human perceptions. We propose a novel SVA model, where multiple perceptual stimuli including depth, motion, intensity, color, and orientation contrast are utilized, to simulate the visual attention mechanisms of human visual system with stereoscopic perception. Then, a semantic region-of-interest (ROI is extracted based on the saliency maps of SVA. Both objective and subjective evaluations of extracted ROIs indicated that the proposed SVA model based on ROI extraction scheme outperforms the schemes only using spatial or/and temporal visual attention clues. Finally, by using the extracted SVA-based ROIs, a regional bit allocation optimization scheme is presented to allocate more bits on SVA-based ROIs for high image quality and fewer bits on background regions for efficient compression purpose. Experimental results on MVC show that the proposed regional bit allocation algorithm can achieve over % bit-rate saving while maintaining the subjective image quality. Meanwhile, the image quality of ROIs is improved by  dB at the cost of insensitive image quality degradation of the background image.

RCAS: an RNA centric annotation system for transcriptome-wide regions of interest.

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Uyar, Bora; Yusuf, Dilmurat; Wurmus, Ricardo; Rajewsky, Nikolaus; Ohler, Uwe; Akalin, Altuna

2017-06-02

In the field of RNA, the technologies for studying the transcriptome have created a tremendous potential for deciphering the puzzles of the RNA biology. Along with the excitement, the unprecedented volume of RNA related omics data is creating great challenges in bioinformatics analyses. Here, we present the RNA Centric Annotation System (RCAS), an R package, which is designed to ease the process of creating gene-centric annotations and analysis for the genomic regions of interest obtained from various RNA-based omics technologies. The design of RCAS is modular, which enables flexible usage and convenient integration with other bioinformatics workflows. RCAS is an R/Bioconductor package but we also created graphical user interfaces including a Galaxy wrapper and a stand-alone web service. The application of RCAS on published datasets shows that RCAS is not only able to reproduce published findings but also helps generate novel knowledge and hypotheses. The meta-gene profiles, gene-centric annotation, motif analysis and gene-set analysis provided by RCAS provide contextual knowledge which is necessary for understanding the functional aspects of different biological events that involve RNAs. In addition, the array of different interfaces and deployment options adds the convenience of use for different levels of users. RCAS is available at http://bioconductor.org/packages/release/bioc/html/RCAS.html and http://rcas.mdc-berlin.de. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Multiple Interests of Users in Collaborative Tagging Systems

Science.gov (United States)

Au Yeung, Ching-Man; Gibbins, Nicholas; Shadbolt, Nigel

Performance of recommender systems depends on whether the user profiles contain accurate information about the interests of the users, and this in turn relies on whether enough information about their interests can be collected. Collaborative tagging systems allow users to use their own words to describe their favourite resources, resulting in some user-generated categorisation schemes commonly known as folksonomies. Folksonomies thus contain rich information about the interests of the users, which can be used to support various recommender systems. Our analysis of the folksonomy in Delicious reveals that the interests of a single user can be very diverse. Traditional methods for representing interests of users are usually not able to reflect such diversity. We propose a method to construct user profiles of multiple interests from folksonomies based on a network clustering technique. Our evaluation shows that the proposed method is able to generate user profiles which reflect the diversity of user interests and can be used as a basis of providing more focused recommendation to the users.

Interest in Currency Trading Learning – Preferred Methods and Motivational Factors

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Pintar Rok

2016-02-01

Full Text Available Background and purpose: This paper analyzes the interest of potential users for learning in the field of currency trading or foreign exchange (forex, FX. The purpose of our article is a to present currency trading, b to present different options, methods and learning approaches to educating in forex, c to present the research results discovering the interest of potential users for learning in the field of currency trading.

Delayed Gadolinium-Enhanced MRI of Cartilage (dGEMRIC): Intra- and Interobserver Variability in Standardized Drawing of Regions of Interest

International Nuclear Information System (INIS)

Tiderius, C.J.; Tjoernstrand, J.; Aakeson, P.; Soedersten, K.; Dahlberg, L.; Leander, P.

2004-01-01

Purpose: To establish the reproducibility of a standardized region of interest (ROI) drawing procedure in delayed gadolinium-enhanced magnetic resonance imaging (MRI) of cartilage (dGEMRIC). Material and Methods: A large ROI in lateral and medial femoral weight-bearing cartilage was drawn in images of 12 healthy male volunteers by 6 investigators with different skills in MRI. The procedure was done twice, with a 1-week interval. Calculated T1-values were evaluated for intra- and interobserver variability. Results: The mean interobserver variability for both compartments ranged between 1.3% and 2.3% for the 6 different investigators without correlation to their experience in MRI. Post-contrast intra-observer variability was low in both the lateral and the medial femoral cartilage, 2.6% and 1.5%, respectively. The larger variability in lateral than in medial cartilage was related to slightly longer and thinner ROIs. Conclusion: Intra-observer variability and interobserver variability are both low when a large standardized ROI is used in dGEMRIC. The experience of the investigator does not affect the variability, which further supports a clinical applicability of the method

Functional connectivity analysis of the neural bases of emotion regulation: A comparison of independent component method with density-based k-means clustering method.

Science.gov (United States)

Zou, Ling; Guo, Qian; Xu, Yi; Yang, Biao; Jiao, Zhuqing; Xiang, Jianbo

2016-04-29

Functional magnetic resonance imaging (fMRI) is an important tool in neuroscience for assessing connectivity and interactions between distant areas of the brain. To find and characterize the coherent patterns of brain activity as a means of identifying brain systems for the cognitive reappraisal of the emotion task, both density-based k-means clustering and independent component analysis (ICA) methods can be applied to characterize the interactions between brain regions involved in cognitive reappraisal of emotion. Our results reveal that compared with the ICA method, the density-based k-means clustering method provides a higher sensitivity of polymerization. In addition, it is more sensitive to those relatively weak functional connection regions. Thus, the study concludes that in the process of receiving emotional stimuli, the relatively obvious activation areas are mainly distributed in the frontal lobe, cingulum and near the hypothalamus. Furthermore, density-based k-means clustering method creates a more reliable method for follow-up studies of brain functional connectivity.

Convex-based void filling method for CAD-based Monte Carlo geometry modeling

International Nuclear Information System (INIS)

Yu, Shengpeng; Cheng, Mengyun; Song, Jing; Long, Pengcheng; Hu, Liqin

2015-01-01

Highlights: • We present a new void filling method named CVF for CAD based MC geometry modeling. • We describe convex based void description based and quality-based space subdivision. • The results showed improvements provided by CVF for both modeling and MC calculation efficiency. - Abstract: CAD based automatic geometry modeling tools have been widely applied to generate Monte Carlo (MC) calculation geometry for complex systems according to CAD models. Automatic void filling is one of the main functions in the CAD based MC geometry modeling tools, because the void space between parts in CAD models is traditionally not modeled while MC codes such as MCNP need all the problem space to be described. A dedicated void filling method, named Convex-based Void Filling (CVF), is proposed in this study for efficient void filling and concise void descriptions. The method subdivides all the problem space into disjointed regions using Quality based Subdivision (QS) and describes the void space in each region with complementary descriptions of the convex volumes intersecting with that region. It has been implemented in SuperMC/MCAM, the Multiple-Physics Coupling Analysis Modeling Program, and tested on International Thermonuclear Experimental Reactor (ITER) Alite model. The results showed that the new method reduced both automatic modeling time and MC calculation time

A multilevel-ROI-features-based machine learning method for detection of morphometric biomarkers in Parkinson's disease.

Science.gov (United States)

Peng, Bo; Wang, Suhong; Zhou, Zhiyong; Liu, Yan; Tong, Baotong; Zhang, Tao; Dai, Yakang

2017-06-09

Machine learning methods have been widely used in recent years for detection of neuroimaging biomarkers in regions of interest (ROIs) and assisting diagnosis of neurodegenerative diseases. The innovation of this study is to use multilevel-ROI-features-based machine learning method to detect sensitive morphometric biomarkers in Parkinson's disease (PD). Specifically, the low-level ROI features (gray matter volume, cortical thickness, etc.) and high-level correlative features (connectivity between ROIs) are integrated to construct the multilevel ROI features. Filter- and wrapper- based feature selection method and multi-kernel support vector machine (SVM) are used in the classification algorithm. T1-weighted brain magnetic resonance (MR) images of 69 PD patients and 103 normal controls from the Parkinson's Progression Markers Initiative (PPMI) dataset are included in the study. The machine learning method performs well in classification between PD patients and normal controls with an accuracy of 85.78%, a specificity of 87.79%, and a sensitivity of 87.64%. The most sensitive biomarkers between PD patients and normal controls are mainly distributed in frontal lobe, parental lobe, limbic lobe, temporal lobe, and central region. The classification performance of our method with multilevel ROI features is significantly improved comparing with other classification methods using single-level features. The proposed method shows promising identification ability for detecting morphometric biomarkers in PD, thus confirming the potentiality of our method in assisting diagnosis of the disease. Copyright © 2017 Elsevier B.V. All rights reserved.

Examining Brain Morphometry Associated with Self-Esteem in Young Adults Using Multilevel-ROI-Features-Based Classification Method

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Bo Peng

2017-05-01

Full Text Available Purpose: This study is to exam self-esteem related brain morphometry on brain magnetic resonance (MR images using multilevel-features-based classification method.Method: The multilevel region of interest (ROI features consist of two types of features: (i ROI features, which include gray matter volume, white matter volume, cerebrospinal fluid volume, cortical thickness, and cortical surface area, and (ii similarity features, which are based on similarity calculation of cortical thickness between ROIs. For each feature type, a hybrid feature selection method, comprising of filter-based and wrapper-based algorithms, is used to select the most discriminating features. ROI features and similarity features are integrated by using multi-kernel support vector machines (SVMs with appropriate weighting factor.Results: The classification performance is improved by using multilevel ROI features with an accuracy of 96.66%, a specificity of 96.62%, and a sensitivity of 95.67%. The most discriminating ROI features that are related to self-esteem spread over occipital lobe, frontal lobe, parietal lobe, limbic lobe, temporal lobe, and central region, mainly involving white matter and cortical thickness. The most discriminating similarity features are distributed in both the right and left hemisphere, including frontal lobe, occipital lobe, limbic lobe, parietal lobe, and central region, which conveys information of structural connections between different brain regions.Conclusion: By using ROI features and similarity features to exam self-esteem related brain morphometry, this paper provides a pilot evidence that self-esteem is linked to specific ROIs and structural connections between different brain regions.

Influence of region of interest size and ultrasound lesion size on the performance of 2D shear wave elastography (SWE) in solid breast masses

International Nuclear Information System (INIS)

Skerl, K.; Vinnicombe, S.; Giannotti, E.; Thomson, K.; Evans, A.

2015-01-01

Aim: To evaluate the influence of the region of interest (ROI) size and lesion diameter on the diagnostic performance of 2D shear wave elastography (SWE) of solid breast lesions. Materials and methods: A study group of 206 consecutive patients (age range 21–92 years) with 210 solid breast lesions (70 benign, 140 malignant) who underwent core biopsy or surgical excision was evaluated. Lesions were divided into small (diameter <15 mm, n=112) and large lesions (diameter ≥15 mm, n=98). An ROI with a diameter of 1, 2, and 3 mm was positioned over the stiffest part of the lesion. The maximum elasticity (E_m_a_x), mean elasticity (E_m_e_a_n) and standard deviation (SD) for each ROI size were compared to the pathological outcome. Statistical analysis was undertaken using the chi-square test and receiver operating characteristic (ROC) analysis. Results: The ROI size used has a significant impact on the performance of E_m_e_a_n and SD but not on E_m_a_x. Youden's indices show a correlation with the ROI size and lesion size: generally, the benign/malignant threshold is lower with increasing ROI size but higher with increasing lesion size. Conclusions: No single SWE parameter has superior performance. Lesion size and ROI size influence diagnostic performance. - Highlights: • Optimal cut-off for benign/malignant differentiation depends on lesion size. • Region of interest size influences measurements of mean elasticity and standard deviation. • Large lesions are stiffer than small lesions. • Optimal cut-off for benign/malignant differentiation should increase with increasing lesion size. • Region of interest of 2 mm achieved best compromise of the diagnostic performance for all SWE parameter.

Defect inspection in hot slab surface: multi-source CCD imaging based fuzzy-rough sets method

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Zhao, Liming; Zhang, Yi; Xu, Xiaodong; Xiao, Hong; Huang, Chao

2016-09-01

To provide an accurate surface defects inspection method and make the automation of robust image region of interests(ROI) delineation strategy a reality in production line, a multi-source CCD imaging based fuzzy-rough sets method is proposed for hot slab surface quality assessment. The applicability of the presented method and the devised system are mainly tied to the surface quality inspection for strip, billet and slab surface etcetera. In this work we take into account the complementary advantages in two common machine vision (MV) systems(line array CCD traditional scanning imaging (LS-imaging) and area array CCD laser three-dimensional (3D) scanning imaging (AL-imaging)), and through establishing the model of fuzzy-rough sets in the detection system the seeds for relative fuzzy connectedness(RFC) delineation for ROI can placed adaptively, which introduces the upper and lower approximation sets for RIO definition, and by which the boundary region can be delineated by RFC region competitive classification mechanism. For the first time, a Multi-source CCD imaging based fuzzy-rough sets strategy is attempted for CC-slab surface defects inspection that allows an automatic way of AI algorithms and powerful ROI delineation strategies to be applied to the MV inspection field.

[An interesting experience on the use of information and population data bases].

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Expósito, J; Johnson, A P

2012-01-01

In order to support decisions and analyze outcomes, the Spanish Health System has shown a great interest in developing data bases and high quality information systems. Nevertheless the use of these data bases are limited, not very systematized and, some times, their accessibility may be difficult. We describe in this review the experience in using the Institute for Clinical Evaluative Science (ICES, Ontario, Canada) as an efficient model to improve the usefulness of these data bases. Under restrictive conditions of confidentiality and privacy, the ICES has the legal capacity to use several population based data bases, for research projects and reports. ICES's functional structure (with an administrative and scientific level) is an interesting framework since it guarantees its independent and economic assessment. To date, its scientific production has been high in many areas of knowledge and open to those interested, with points of view of many health care professionals (including management), for whom the quality of research is of the ultimate importance, to be able to access these resources. Copyright © 2011 SECA. Published by Elsevier Espana. All rights reserved.

Diffeomorphic Anatomical Registration Through Exponentiated Lie Algebra provides reduced effect of scanner for cortex volumetry with atlas-based method in healthy subjects.

Science.gov (United States)

Goto, Masami; Abe, Osamu; Aoki, Shigeki; Hayashi, Naoto; Miyati, Tosiaki; Takao, Hidemasa; Iwatsubo, Takeshi; Yamashita, Fumio; Matsuda, Hiroshi; Mori, Harushi; Kunimatsu, Akira; Ino, Kenji; Yano, Keiichi; Ohtomo, Kuni

2013-07-01

This study aimed to investigate whether the effect of scanner for cortex volumetry with atlas-based method is reduced using Diffeomorphic Anatomical Registration Through Exponentiated Lie Algebra (DARTEL) normalization compared with standard normalization. Three-dimensional T1-weighted magnetic resonance images (3D-T1WIs) of 21 healthy subjects were obtained and evaluated for effect of scanner in cortex volumetry. 3D-T1WIs of the 21 subjects were obtained with five MRI systems. Imaging of each subject was performed on each of five different MRI scanners. We used the Voxel-Based Morphometry 8 tool implemented in Statistical Parametric Mapping 8 and WFU PickAtlas software (Talairach brain atlas theory). The following software default settings were used as bilateral region-of-interest labels: "Frontal Lobe," "Hippocampus," "Occipital Lobe," "Orbital Gyrus," "Parietal Lobe," "Putamen," and "Temporal Lobe." Effect of scanner for cortex volumetry using the atlas-based method was reduced with DARTEL normalization compared with standard normalization in Frontal Lobe, Occipital Lobe, Orbital Gyrus, Putamen, and Temporal Lobe; was the same in Hippocampus and Parietal Lobe; and showed no increase with DARTEL normalization for any region of interest (ROI). DARTEL normalization reduces the effect of scanner, which is a major problem in multicenter studies.

Diffeomorphic Anatomical Registration Through Exponentiated Lie Algebra provides reduced effect of scanner for cortex volumetry with atlas-based method in healthy subjects

International Nuclear Information System (INIS)

Goto, Masami; Ino, Kenji; Yano, Keiichi; Abe, Osamu; Aoki, Shigeki; Hayashi, Naoto; Miyati, Tosiaki; Takao, Hidemasa; Mori, Harushi; Kunimatsu, Akira; Ohtomo, Kuni; Iwatsubo, Takeshi; Yamashita, Fumio; Matsuda, Hiroshi

2013-01-01

This study aimed to investigate whether the effect of scanner for cortex volumetry with atlas-based method is reduced using Diffeomorphic Anatomical Registration Through Exponentiated Lie Algebra (DARTEL) normalization compared with standard normalization. Three-dimensional T1-weighted magnetic resonance images (3D-T1WIs) of 21 healthy subjects were obtained and evaluated for effect of scanner in cortex volumetry. 3D-T1WIs of the 21 subjects were obtained with five MRI systems. Imaging of each subject was performed on each of five different MRI scanners. We used the Voxel-Based Morphometry 8 tool implemented in Statistical Parametric Mapping 8 and WFU PickAtlas software (Talairach brain atlas theory). The following software default settings were used as bilateral region-of-interest labels: ''Frontal Lobe,'' ''Hippocampus,'' ''Occipital Lobe,'' ''Orbital Gyrus,'' ''Parietal Lobe,'' ''Putamen,'' and ''Temporal Lobe.'' Effect of scanner for cortex volumetry using the atlas-based method was reduced with DARTEL normalization compared with standard normalization in Frontal Lobe, Occipital Lobe, Orbital Gyrus, Putamen, and Temporal Lobe; was the same in Hippocampus and Parietal Lobe; and showed no increase with DARTEL normalization for any region of interest (ROI). DARTEL normalization reduces the effect of scanner, which is a major problem in multicenter studies. (orig.)

Assessment of automatic segmentation of teeth using a watershed-based method.

Science.gov (United States)

Galibourg, Antoine; Dumoncel, Jean; Telmon, Norbert; Calvet, Adèle; Michetti, Jérôme; Maret, Delphine

2018-01-01

Tooth 3D automatic segmentation (AS) is being actively developed in research and clinical fields. Here, we assess the effect of automatic segmentation using a watershed-based method on the accuracy and reproducibility of 3D reconstructions in volumetric measurements by comparing it with a semi-automatic segmentation(SAS) method that has already been validated. The study sample comprised 52 teeth, scanned with micro-CT (41 µm voxel size) and CBCT (76; 200 and 300 µm voxel size). Each tooth was segmented by AS based on a watershed method and by SAS. For all surface reconstructions, volumetric measurements were obtained and analysed statistically. Surfaces were then aligned using the SAS surfaces as the reference. The topography of the geometric discrepancies was displayed by using a colour map allowing the maximum differences to be located. AS reconstructions showed similar tooth volumes when compared with SAS for the 41 µm voxel size. A difference in volumes was observed, and increased with the voxel size for CBCT data. The maximum differences were mainly found at the cervical margins and incisal edges but the general form was preserved. Micro-CT, a modality used in dental research, provides data that can be segmented automatically, which is timesaving. AS with CBCT data enables the general form of the region of interest to be displayed. However, our AS method can still be used for metrically reliable measurements in the field of clinical dentistry if some manual refinements are applied.

Susceptibility assessment of landslides: A comparison of two GIS-based methods in the region of Al Hoceima (Eastern Rif, Morocco.

Directory of Open Access Journals (Sweden)

El Fahchouch A. N.

2018-01-01

Full Text Available The evaluation of the degree of susceptibility to landslides has become a major concern in mountainous areas, it is a key component of manager policies efforts in disaster prevention, mitigate risk and manage the consequences. The region of Al Hoceima is one of most mountain regions in Morocco, and is highly exposed landslides events. For this reason, the area was selected in order to determine its susceptibility to landslides using two methods. The purpose of this study is to evaluate and to compare the results of multivariate (logical regression and bivariate (landslide susceptibility methods in Geographical Information System (GIS based landslide susceptibility assessment procedures. In order to achieve this goal, the selected methods were compared by the Seed Cell Area Indexes (SCAI and by the spatial locations of the resultant susceptibility pixels. We found that both of the methods converge in 80% of the area; however, the weighting algorithm in the bivariate technique (landslide susceptibility method had some severe deficiencies, as the resultant hazard classes in overweighed areas did not converge with the factual landslide inventory map. The result of the multivariate technique (logical regression was more sensitive to the different local features of the test zone and it resulted in more accurate and homogeneous susceptibility maps. This information may have direct applications in landslides susceptibility research programs and can assist decision-makers in the implementation of preventive management strategies in the most sensitive areas.

Optimal regional biases in ECB interest rate setting

NARCIS (Netherlands)

Arnold, I.J.M.

2005-01-01

This paper uses a simple model of optimal monetary policy to consider whether the influence of national output and inflation rates on ECB interest rate setting should equal a country’s weight in the eurozone economy. The findings depend on assumptions regarding interest rate elasticities, exchange

Adaptive Steganalysis Based on Selection Region and Combined Convolutional Neural Networks

Directory of Open Access Journals (Sweden)

Donghui Hu

2017-01-01

Full Text Available Digital image steganalysis is the art of detecting the presence of information hiding in carrier images. When detecting recently developed adaptive image steganography methods, state-of-art steganalysis methods cannot achieve satisfactory detection accuracy, because the adaptive steganography methods can adaptively embed information into regions with rich textures via the guidance of distortion function and thus make the effective steganalysis features hard to be extracted. Inspired by the promising success which convolutional neural network (CNN has achieved in the fields of digital image analysis, increasing researchers are devoted to designing CNN based steganalysis methods. But as for detecting adaptive steganography methods, the results achieved by CNN based methods are still far from expected. In this paper, we propose a hybrid approach by designing a region selection method and a new CNN framework. In order to make the CNN focus on the regions with complex textures, we design a region selection method by finding a region with the maximal sum of the embedding probabilities. To evolve more diverse and effective steganalysis features, we design a new CNN framework consisting of three separate subnets with independent structure and configuration parameters and then merge and split the three subnets repeatedly. Experimental results indicate that our approach can lead to performance improvement in detecting adaptive steganography.

Context-based adaptive filtering of interest points in image retrieval

DEFF Research Database (Denmark)

Nguyen, Phuong Giang; Andersen, Hans Jørgen

2009-01-01

Interest points have been used as local features with success in many computer vision applications such as image/video retrieval and object recognition. However, a major issue when using this approach is a large number of interest points detected from each image and created a dense feature space...... a subset of features. Our approach differs from others in a fact that selected feature is based on the context of the given image. Our experimental results show a significant reduction rate of features while preserving the retrieval performance....

From community-based pilot testing to region-wide systems change: lessons from a local quality improvement collaborative.

Science.gov (United States)

Keyser, Donna J; Pincus, Harold Alan

2010-01-01

A community-based collaborative conducted a 2-year pilot study to inform efforts for improving maternal and child health care practice and policy in Allegheny County, Pennsylvania. (1) To test whether three small-scale versions of an evidence-based, systems improvement approach would be workable in local community settings and (2) to identify specific policy/infrastructure reforms for sustaining improvements. A mixed methods approach was used, including quantitative performance measurement supplemented with qualitative data about factors related to outcomes of interest, as well as key stakeholder interviews and a literature review/Internet search. Quantitative performance results varied; qualitative data revealed critical factors for the success and failure of the practices tested. Policy/infrastructure recommendations were developed to address specific practice barriers. This information was important for designing a region-wide quality improvement initiative focused on maternal depression. The processes and outcomes provide valuable insights for other communities interested in conducting similar quality improvement initiatives.

Using the standard deviation of a region of interest in an image to estimate camera to emitter distance.

Science.gov (United States)

Cano-García, Angel E; Lazaro, José Luis; Infante, Arturo; Fernández, Pedro; Pompa-Chacón, Yamilet; Espinoza, Felipe

2012-01-01

In this study, a camera to infrared diode (IRED) distance estimation problem was analyzed. The main objective was to define an alternative to measures depth only using the information extracted from pixel grey levels of the IRED image to estimate the distance between the camera and the IRED. In this paper, the standard deviation of the pixel grey level in the region of interest containing the IRED image is proposed as an empirical parameter to define a model for estimating camera to emitter distance. This model includes the camera exposure time, IRED radiant intensity and the distance between the camera and the IRED. An expression for the standard deviation model related to these magnitudes was also derived and calibrated using different images taken under different conditions. From this analysis, we determined the optimum parameters to ensure the best accuracy provided by this alternative. Once the model calibration had been carried out, a differential method to estimate the distance between the camera and the IRED was defined and applied, considering that the camera was aligned with the IRED. The results indicate that this method represents a useful alternative for determining the depth information.

Using the Standard Deviation of a Region of Interest in an Image to Estimate Camera to Emitter Distance

Directory of Open Access Journals (Sweden)

Felipe Espinoza

2012-05-01

Full Text Available In this study, a camera to infrared diode (IRED distance estimation problem was analyzed. The main objective was to define an alternative to measures depth only using the information extracted from pixel grey levels of the IRED image to estimate the distance between the camera and the IRED. In this paper, the standard deviation of the pixel grey level in the region of interest containing the IRED image is proposed as an empirical parameter to define a model for estimating camera to emitter distance. This model includes the camera exposure time, IRED radiant intensity and the distance between the camera and the IRED. An expression for the standard deviation model related to these magnitudes was also derived and calibrated using different images taken under different conditions. From this analysis, we determined the optimum parameters to ensure the best accuracy provided by this alternative. Once the model calibration had been carried out, a differential method to estimate the distance between the camera and the IRED was defined and applied, considering that the camera was aligned with the IRED. The results indicate that this method represents a useful alternative for determining the depth information.

Application of qualitative biospeckle methods for the identification of scar region in a green orange

Science.gov (United States)

Retheesh, R.; Ansari, Md. Zaheer; Radhakrishnan, P.; Mujeeb, A.

2018-03-01

This study demonstrates the feasibility of a view-based method, the motion history image (MHI) to map biospeckle activity around the scar region in a green orange fruit. The comparison of MHI with the routine intensity-based methods validated the effectiveness of the proposed method. The results show that MHI can be implementated as an alternative online image processing tool in the biospeckle analysis.

A new reprojection method based on a comparison of popular reprojection models

International Nuclear Information System (INIS)

Guedouar, R.; Zarrad, B.

2010-01-01

Reprojection is of interest in several applications such as iterative tomographic reconstruction, dose-calculation in radiotherapy and 3D-display volume-rendering. All numerical implementations of reprojection result in varying degrees of errors. Popular reprojection methods were compared using 128x128 2D-noiseless-numerical uniform-disk and Shepp-Logan phantoms to evaluate errors in external-border, interior and overall regions of the reprojected sinogram, in order to investigate a new method for increasing their accuracy on all regions. Root mean squared errors (RMSE) (with calculated projection as reference) were used. No method gives the least errors in all regions. Smoothing projectors decrease noise but introduce important errors in the border region, whereas other projectors increase errors inside the reprojected sinogram. The overall-error is a trade-off between interior and border errors. The conventional ray-driven (R1) and the bilinear-interpolated pixel driven with 5x5 sub-pixels (L5) provide the highest accuracy for border and interior regions, respectively. These results motivate the implementation of a new reprojection method that uses R1 to project pixels near borders in the sinogram and L5 for the others. Feature borders were localized using the spatial derivatives of sinogram count profile. This method provides the least errors for all regions. The performance of the new method was investigated on iterative reconstruction tasks with MLEM. Results show that the new method can promise more accuracy in terms of RMSE and aliasing reduction of the reconstructed images.

Molecular methods for bacterial genotyping and analyzed gene regions

Directory of Open Access Journals (Sweden)

İbrahim Halil Yıldırım1, Seval Cing Yıldırım2, Nadir Koçak3

2011-06-01

Full Text Available Bacterial strain typing is an important process for diagnosis, treatment and epidemiological investigations. Current bacterial strain typing methods may be classified into two main categories: phenotyping and genotyping. Phenotypic characters are the reflection of genetic contents. Genotyping, which refers discrimination of bacterial strains based on their genetic content, has recently become widely used for bacterial strain typing. The methods already used in genotypingof bacteria are quite different from each other. In this review we tried to summarize the basic principles of DNA-based methods used in genotyping of bacteria and describe some important DNA regions that are used in genotyping of bacteria. J Microbiol Infect Dis 2011;1(1:42-46.

Interest Matters: The Importance of Promoting Interest in Education.

Science.gov (United States)

Harackiewicz, Judith M; Smith, Jessi L; Priniski, Stacy J

2016-10-01

Interest is a powerful motivational process that energizes learning, guides academic and career trajectories, and is essential to academic success. Interest is both a psychological state of attention and affect toward a particular object or topic, and an enduring predisposition to reengage over time. Integrating these two definitions, the four-phase model of interest development guides interventions that promote interest and capitalize on existing interests. Four interest-enhancing interventions seem useful: attention-getting settings, contexts evoking prior individual interest, problem-based learning, and enhancing utility value. Promoting interest can contribute to a more engaged, motivated, learning experience for students.

Lung region extraction based on the model information and the inversed MIP method by using chest CT images

International Nuclear Information System (INIS)

Tomita, Toshihiro; Miguchi, Ryosuke; Okumura, Toshiaki; Yamamoto, Shinji; Matsumoto, Mitsuomi; Tateno, Yukio; Iinuma, Takeshi; Matsumoto, Toru.

1997-01-01

We developed a lung region extraction method based on the model information and the inversed MIP method in the Lung Cancer Screening CT (LSCT). Original model is composed of typical 3-D lung contour lines, a body axis, an apical point, and a convex hull. First, the body axis. the apical point, and the convex hull are automatically extracted from the input image Next, the model is properly transformed to fit to those of input image by the affine transformation. Using the same affine transformation coefficients, typical lung contour lines are also transferred, which correspond to rough contour lines of input image. Experimental results applied for 68 samples showed this method quite promising. (author)

[Application of case-based method in genetics and eugenics teaching].

Science.gov (United States)

Li, Ya-Xuan; Zhao, Xin; Zhang, Fei-Xiong; Hu, Ying-Kao; Yan, Yue-Ming; Cai, Min-Hua; Li, Xiao-Hui

2012-05-01

Genetics and Eugenics is a cross-discipline between genetics and eugenics. It is a common curriculum in many Chinese universities. In order to increase the learning interest, we introduced case teaching method and got a better teaching effect. Based on our teaching practices, we summarized some experiences about this subject. In this article, the main problem of case-based method applied in Genetics and Eugenics teaching was discussed.

Human Detection System by Fusing Depth Map-Based Method and Convolutional Neural Network-Based Method

Directory of Open Access Journals (Sweden)

Anh Vu Le

2017-01-01

Full Text Available In this paper, the depth images and the colour images provided by Kinect sensors are used to enhance the accuracy of human detection. The depth-based human detection method is fast but less accurate. On the other hand, the faster region convolutional neural network-based human detection method is accurate but requires a rather complex hardware configuration. To simultaneously leverage the advantages and relieve the drawbacks of each method, one master and one client system is proposed. The final goal is to make a novel Robot Operation System (ROS-based Perception Sensor Network (PSN system, which is more accurate and ready for the real time application. The experimental results demonstrate the outperforming of the proposed method compared with other conventional methods in the challenging scenarios.

A method of acoustic wave registration and determination their generation region

International Nuclear Information System (INIS)

Kozin, I.D.; Marchenko, M.V.

1998-01-01

Here is presented a method of acoustic wave registration with using of a synchronous LF broadcasting system. This method of detection and determination of underground nuclear explosion location is based on a registration of ionospheric disturbances induced by acoustic waves at the region of LF sign al reflection. The measuring complex created in the institute of the Ionosphere /1/ allows to register amplitude-frequency characteristics of composite signal from synchronous broadcasting net

Comparison of features response in texture-based iris segmentation

CSIR Research Space (South Africa)

Bachoo, A

2009-03-01

Full Text Available the Fisher linear discriminant and the iris region of interest is extracted. Four texture description methods are compared for segmenting iris texture using a region based pattern classification approach: Grey Level Co-occurrence Matrix (GLCM), Discrete...

A Hybrid Positioning Method Based on Hypothesis Testing

DEFF Research Database (Denmark)

Amiot, Nicolas; Pedersen, Troels; Laaraiedh, Mohamed

2012-01-01

maxima. We propose to first estimate the support region of the two peaks of the likelihood function using a set membership method, and then decide between the two regions using a rule based on the less reliable observations. Monte Carlo simulations show that the performance of the proposed method...

Discovery of accessible locations using region-based geo-social data

KAUST Repository

Wang, Yan

2018-03-17

Geo-social data plays a significant role in location discovery and recommendation. In this light, we propose and study a novel problem of discovering accessible locations in spatial networks using region-based geo-social data. Given a set Q of query regions, the top-k accessible location discovery query (k ALDQ) finds k locations that have the highest spatial-density correlations to Q. Both the spatial distances between locations and regions and the POI (point of interest) density within the regions are taken into account. We believe that this type of k ALDQ query can bring significant benefit to many applications such as travel planning, facility allocation, and urban planning. Three challenges exist in k ALDQ: (1) how to model the spatial-density correlation practically, (2) how to prune the search space effectively, and (3) how to schedule the searches from multiple query regions. To tackle the challenges and process k ALDQ effectively and efficiently, we first define a series of spatial and density metrics to model the spatial-density correlation. Then we propose a novel three-phase solution with a pair of upper and lower bounds of the spatial-density correlation and a heuristic scheduling strategy to schedule multiple query regions. Finally, we conduct extensive experiments on real and synthetic spatial data to demonstrate the performance of the developed solutions.

SOFTWARE FOR REGIONS OF INTEREST RETRIEVAL ON MEDICAL 3D IMAGES

Directory of Open Access Journals (Sweden)

G. G. Stromov

2014-01-01

Full Text Available Background. Implementation of software for areas of interest retrieval in 3D medical images is described in this article. It has been tested against large volume of model MRIs.Material and methods. We tested software against normal and pathological (severe multiple sclerosis model MRIs from tge BrainWeb resource. Technological stack is based on open-source cross-platform solutions. We implemented storage system on Maria DB (an open-sourced fork of MySQL with P/SQL extensions. Python 2.7 scripting was used for automatization of extract-transform-load operations. The computational core is written on Java 7 with Spring framework 3. MongoDB was used as a cache in the cluster of workstations. Maven 3 was chosen as a dependency manager and build system, the project is hosted at Github.Results. As testing on SSMU's LAN has showed, software has been developed is quite efficiently retrieves ROIs are matching for the morphological substratum on pathological MRIs.Conclusion. Automation of a diagnostic process using medical imaging allows to level down the subjective component in decision making and increase the availability of hi-tech medicine. Software has shown in the article is a complex solution for ROI retrieving and segmentation process on model medical images in full-automated mode.We would like to thank Robert Vincent for great help with consulting of usage the BrainWeb resource.

The Council of Regional Accrediting Commissions Framework for Competency-Based Education: A Grounded Theory Study

Science.gov (United States)

Butland, Mark James

2017-01-01

Colleges facing pressures to increase student outcomes while reducing costs have shown an increasing interest in competency-based education (CBE) models. Regional accreditors created a joint policy on CBE evaluation. Two years later, through this grounded theory study, I sought to understand from experts the nature of this policy, its impact, and…

Energy for our future: Balancing regional interests

International Nuclear Information System (INIS)

Brand, S.

1993-01-01

An emerging global governance is suggested in which the environment is the central organizing principle of civilization. A shift is noted in which transnational, regional, nation-state, local, and tribal structures exist and compete. Nations with strong environmental regulations are more able to meet international competition in such a scenario. It has also been observed in many instances that for managing common resources such as forests and fish stocks, there have been traditional institutions resembling neither state or market but based on such principles as clearly defined boundaries, monitoring of compliance, graduated sanctions, and collective choice arrangements. Examples of a certain kind of well-managed common resource are provided by certain energy utilities which make profits from energy conservation. One such example is the Tennessee Valley Authority, which helps customers install and finance energy-efficient windows for mutual benefit of both parties

Study of regional cerebral blood flow in obsessive compulsive disorder patients with SPM and ROI method

International Nuclear Information System (INIS)

Li Peiyong; Jiang Xufeng; Zhang Liying; Guo Wanhua; Zhu Chengmo

2002-01-01

Objective: To investigate the alternations in regional cerebral blood flow (rCBF) in obsessive compulsive disorder (OCD) patients using statistical parametric mapping (SPM). Methods: rCBF measurements using 99 Tc m -ethyl cysteinate dimer (ECD) SPECT was performed on 14 OCD patients and 23 age-matched healthy volunteers. The rCBF distribution was compared between these two groups with SPM under the conditions of increased and decreased perfusion, and with regions of interest (ROIs) using cerebral template. P value was set at 0.01 level. Results: SPM analysis showed that rCBF decreased in cerebral areas including bilateral putamen, superior temporal gyrus and precuneus, and right orbital gyrus, superior and middle frontal gyrus, and left temporo-occipital lobule and superior parietal gyrus, and vermis. rCBF was also increased in left inferior frontal gyrus and posterior cingulate gyrus. With ROIs method, rCBF was decreased in right anterior frontal, temporo-parietal lobule and left temporo-occipital lobule. Conclusions: The study supports the viewpoint that rCBF abnormality of fronto-striatal circuits is involved in OCD patients. SPM method is a forceful tool in analyzing cerebral regional characters

A simple approach to spectrally resolved fluorescence and bright field microscopy over select regions of interest

OpenAIRE

Dahlberg, Peter D.; Boughter, Christopher T.; Faruk, Nabil F.; Hong, Lu; Koh, Young Hoon; Reyer, Matthew A.; Shaiber, Alon; Sherani, Aiman; Zhang, Jiacheng; Jureller, Justin E.; Hammond, Adam T.

2016-01-01

A standard wide field inverted microscope was converted to a spatially selective spectrally resolved microscope through the addition of a polarizing beam splitter, a pair of polarizers, an amplitude-mode liquid crystal-spatial light modulator, and a USB spectrometer. The instrument is capable of simultaneously imaging and acquiring spectra over user defined regions of interest. The microscope can also be operated in a bright-field mode to acquire absorption spectra of micron scale objects. Th...

Theories and calculation methods for regional objective ET

Institute of Scientific and Technical Information of China (English)

QIN DaYong; LO JinYan; LIU JiaHong; WANG MingNa

2009-01-01

The regional objective ET (Evapotranspiration) is a new concept in water resources research, which refers to the total amount of water that could be exhausted from a region in the form of vapor per year. The objective-ET based water resources management allocates water to different regions in terms of ET. It controls the water exhausted from a region to meet the objective ET. The regional objective ET must be adapted to fit the region's local available water resources. By improving the water utilization effi-ciency and reducing the unrecoverable water in the social water circle, it is saved so that water related production is maintained or even increased under the same water consumption conditions. Regional water balance is realized by rationally deploying the available water among different industries, adjusting industrial structures, and adopting new water-saving technologies, therefore to meeting the requirements for groundwater conservation, agricultural income stability, and avoiding environmental damages. Furthermore, water competition among various departments and industries (including envi-ronmental and ecological water use) may be avoided. This paper proposes an innovative definition of objective ET, and its principles, sub-index systems. Besides, a computational method for regional ob-jective ET is developed by combining the distributed hydrological model and the soil moisture model.

Aplikasi Pendeteksi Kualitas Daging Menggunakan Segmentasi Region of Interest Berbasis Mobile

Directory of Open Access Journals (Sweden)

Rismawan Fajril Falah

2016-04-01

Full Text Available Peningkatan kebutuhan daging sapi di Indonesia saat ini dimanfaatkan pedagang-pedagang curang untuk mengambil banyak keuntungan. Penjualan daging sapi berkualitas buruk menimbulkan kecemasan bagi masyarakat karena kandungan yang sangat berbahaya. Kualitas daging sapi yang baik dapat ditentukan dari warna, bau, tekstur dan kenampakan. Masyarakat pada umumnya menggunakan penglihatan kasat mata untuk menentukan kualitas daging sapi. Namun cara tersebut masih kurang efektif karena mata memiliki kelemahan untuk melihat suatu objek secara detail. Penelitian ini bertujuan merancang dan membuat aplikasi untuk mendeteksi kualitas daging sapi dengan menggunakan proses pengolahan citra. Aplikasi dibuat menggunakan sistem operasi Android yang terintegrasi dengan SDK Android, library OpenCV dan Eclipse. Proses deteksi dilakukan dengan cara pengambilan gambar daging sapi dan diolah dengan beberapa tahap pengolahan citra digital. Tahap pengolahan terdiri dari pra pengolahan citra aras keabuan, segmentasi Region of Interest, ekualisasi histogram dan analisis nilai statistik ekstraksi ciri. Penentukan kualitas daging sapi yang lebih efektif dapat dilakukan dengan melihat hasil analisis pengolahan citra. Penelitian ini menunjukkan hasil analisis akurasi ketepatan baca aplikasi adalah 90%.

Enhancement of bone shadow region using local phase-based ultrasound transmission maps.

Science.gov (United States)

Hacihaliloglu, Ilker

2017-06-01

Ultrasound is increasingly being employed in different orthopedic procedures as an imaging modality for real-time guidance. Nevertheless, low signal-to-noise-ratio and different imaging artifacts continue to hamper the success of ultrasound-based procedures. Bone shadow region is an important feature indicating the presence of bone/tissue interface in the acquired ultrasound data. Enhancement and automatic detection of this region could improve the sensitivity of ultrasound for imaging bone and result in improved guidance for various orthopedic procedures. In this work, a method is introduced for the enhancement of bone shadow regions from B-mode ultrasound data. The method is based on the combination of three different image phase features: local phase tensor, local weighted mean phase angle, and local phase energy. The combined local phase image features are used as an input to an [Formula: see text] norm-based contextual regularization method which emphasizes uncertainty in the shadow regions. The enhanced bone shadow images are automatically segmented and compared against expert segmentation. Qualitative and quantitative validation was performed on 100 in vivo US scans obtained from five subjects by scanning femur and vertebrae bones. Validation against expert segmentation achieved a mean dice similarity coefficient of 0.88. The encouraging results obtained in this initial study suggest that the proposed method is promising enough for further evaluation. The calculated bone shadow maps could be incorporated into different ultrasound bone segmentation and registration approaches as an additional feature.

Creating multithemed ecological regions for macroscale ecology: Testing a flexible, repeatable, and accessible clustering method

Science.gov (United States)

Cheruvelil, Kendra Spence; Yuan, Shuai; Webster, Katherine E.; Tan, Pang-Ning; Lapierre, Jean-Francois; Collins, Sarah M.; Fergus, C. Emi; Scott, Caren E.; Norton Henry, Emily; Soranno, Patricia A.; Filstrup, Christopher T.; Wagner, Tyler

2017-01-01

Understanding broad-scale ecological patterns and processes often involves accounting for regional-scale heterogeneity. A common way to do so is to include ecological regions in sampling schemes and empirical models. However, most existing ecological regions were developed for specific purposes, using a limited set of geospatial features and irreproducible methods. Our study purpose was to: (1) describe a method that takes advantage of recent computational advances and increased availability of regional and global data sets to create customizable and reproducible ecological regions, (2) make this algorithm available for use and modification by others studying different ecosystems, variables of interest, study extents, and macroscale ecology research questions, and (3) demonstrate the power of this approach for the research question—How well do these regions capture regional-scale variation in lake water quality? To achieve our purpose we: (1) used a spatially constrained spectral clustering algorithm that balances geospatial homogeneity and region contiguity to create ecological regions using multiple terrestrial, climatic, and freshwater geospatial data for 17 northeastern U.S. states (~1,800,000 km2); (2) identified which of the 52 geospatial features were most influential in creating the resulting 100 regions; and (3) tested the ability of these ecological regions to capture regional variation in water nutrients and clarity for ~6,000 lakes. We found that: (1) a combination of terrestrial, climatic, and freshwater geospatial features influenced region creation, suggesting that the oft-ignored freshwater landscape provides novel information on landscape variability not captured by traditionally used climate and terrestrial metrics; and (2) the delineated regions captured macroscale heterogeneity in ecosystem properties not included in region delineation—approximately 40% of the variation in total phosphorus and water clarity among lakes was at the regional

Research on frequency control strategy of interconnected region based on fuzzy PID

Science.gov (United States)

Zhang, Yan; Li, Chunlan

2018-05-01

In order to improve the frequency control performance of the interconnected power grid, overcome the problems of poor robustness and slow adjustment of traditional regulation, the paper puts forward a frequency control method based on fuzzy PID. The method takes the frequency deviation and tie-line deviation of each area as the control objective, takes the regional frequency deviation and its deviation as input, and uses fuzzy mathematics theory, adjusts PID control parameters online. By establishing the regional frequency control model of water-fire complementary power generation in MATLAB, the regional frequency control strategy is given, and three control modes (TBC-FTC, FTC-FTC, FFC-FTC) are simulated and analyzed. The simulation and experimental results show that, this method has better control performance compared with the traditional regional frequency regulation.

TU-CD-BRA-04: Evaluation of An Atlas-Based Segmentation Method for Prostate and Peripheral Zone Regions On MRI

International Nuclear Information System (INIS)

Nelson, AS; Piper, J; Curry, K; Swallen, A; Padgett, K; Pollack, A; Stoyanova, RS

2015-01-01

Purpose: Prostate MRI plays an important role in diagnosis, biopsy guidance, and therapy planning for prostate cancer. Prostate MRI contours can be used to aid in image fusion for ultrasound biopsy guidance and delivery of radiation. Our goal in this study is to evaluate an automatic atlas-based segmentation method for generating prostate and peripheral zone (PZ) contours on MRI. Methods: T2-weighted MRIs were acquired on 3T-Discovery MR750 System (GE, Milwaukee). The Volumes of Interest (VOIs): prostate and PZ were outlined by an expert radiation oncologist and used to create an atlas library for atlas-based segmentation. The atlas-segmentation accuracy was evaluated using a leave-one-out analysis. The method involved automatically finding the atlas subject that best matched the test subject followed by a normalized intensity-based free-form deformable registration of the atlas subject to the test subject. The prostate and PZ contours were transformed to the test subject using the same deformation. For each test subject the three best matches were used and the final contour was combined using Majority Vote. The atlas-segmentation process was fully automatic. Dice similarity coefficients (DSC) and mean Hausdorff values were used for comparison. Results: VOIs contours were available for 28 subjects. For the prostate, the atlas-based segmentation method resulted in an average DSC of 0.88+/−0.08 and a mean Hausdorff distance of 1.1+/−0.9mm. The number of patients (#) in DSC ranges are as follows: 0.60–0.69(1), 0.70–0.79(2), 0.80–0.89(13), >0.89(11). For the PZ, the average DSC was 0.72+/−0.17 and average Hausdorff of 0.9+/−0.9mm. The number of patients (#) in DSC ranges are as follows: 0.89(1). Conclusion: The MRI atlas-based segmentation method achieved good results for both the whole prostate and PZ compared to expert defined VOIs. The technique is fast, fully automatic, and has the potential to provide significant time savings for prostate VOI

Cycle-Based Cluster Variational Method for Direct and Inverse Inference

Science.gov (United States)

Furtlehner, Cyril; Decelle, Aurélien

2016-08-01

Large scale inference problems of practical interest can often be addressed with help of Markov random fields. This requires to solve in principle two related problems: the first one is to find offline the parameters of the MRF from empirical data (inverse problem); the second one (direct problem) is to set up the inference algorithm to make it as precise, robust and efficient as possible. In this work we address both the direct and inverse problem with mean-field methods of statistical physics, going beyond the Bethe approximation and associated belief propagation algorithm. We elaborate on the idea that loop corrections to belief propagation can be dealt with in a systematic way on pairwise Markov random fields, by using the elements of a cycle basis to define regions in a generalized belief propagation setting. For the direct problem, the region graph is specified in such a way as to avoid feed-back loops as much as possible by selecting a minimal cycle basis. Following this line we are led to propose a two-level algorithm, where a belief propagation algorithm is run alternatively at the level of each cycle and at the inter-region level. Next we observe that the inverse problem can be addressed region by region independently, with one small inverse problem per region to be solved. It turns out that each elementary inverse problem on the loop geometry can be solved efficiently. In particular in the random Ising context we propose two complementary methods based respectively on fixed point equations and on a one-parameter log likelihood function minimization. Numerical experiments confirm the effectiveness of this approach both for the direct and inverse MRF inference. Heterogeneous problems of size up to 10^5 are addressed in a reasonable computational time, notably with better convergence properties than ordinary belief propagation.

A simple derivation and analysis of a helical cone beam tomographic algorithm for long object imaging via a novel definition of region of interest

International Nuclear Information System (INIS)

Hu Jicun; Tam, Kwok; Johnson, Roger H

2004-01-01

We derive and analyse a simple algorithm first proposed by Kudo et al (2001 Proc. 2001 Meeting on Fully 3D Image Reconstruction in Radiology and Nuclear Medicine (Pacific Grove, CA) pp 7-10) for long object imaging from truncated helical cone beam data via a novel definition of region of interest (ROI). Our approach is based on the theory of short object imaging by Kudo et al (1998 Phys. Med. Biol. 43 2885-909). One of the key findings in their work is that filtering of the truncated projection can be divided into two parts: one, finite in the axial direction, results from ramp filtering the data within the Tam window. The other, infinite in the z direction, results from unbounded filtering of ray sums over PI lines only. We show that for an ROI defined by PI lines emanating from the initial and final source positions on a helical segment, the boundary data which would otherwise contaminate the reconstruction of the ROI can be completely excluded. This novel definition of the ROI leads to a simple algorithm for long object imaging. The overscan of the algorithm is analytically calculated and it is the same as that of the zero boundary method. The reconstructed ROI can be divided into two regions: one is minimally contaminated by the portion outside the ROI, while the other is reconstructed free of contamination. We validate the algorithm with a 3D Shepp-Logan phantom and a disc phantom

Subpathway-GM: identification of metabolic subpathways via joint power of interesting genes and metabolites and their topologies within pathways.

Science.gov (United States)

Li, Chunquan; Han, Junwei; Yao, Qianlan; Zou, Chendan; Xu, Yanjun; Zhang, Chunlong; Shang, Desi; Zhou, Lingyun; Zou, Chaoxia; Sun, Zeguo; Li, Jing; Zhang, Yunpeng; Yang, Haixiu; Gao, Xu; Li, Xia

2013-05-01

Various 'omics' technologies, including microarrays and gas chromatography mass spectrometry, can be used to identify hundreds of interesting genes, proteins and metabolites, such as differential genes, proteins and metabolites associated with diseases. Identifying metabolic pathways has become an invaluable aid to understanding the genes and metabolites associated with studying conditions. However, the classical methods used to identify pathways fail to accurately consider joint power of interesting gene/metabolite and the key regions impacted by them within metabolic pathways. In this study, we propose a powerful analytical method referred to as Subpathway-GM for the identification of metabolic subpathways. This provides a more accurate level of pathway analysis by integrating information from genes and metabolites, and their positions and cascade regions within the given pathway. We analyzed two colorectal cancer and one metastatic prostate cancer data sets and demonstrated that Subpathway-GM was able to identify disease-relevant subpathways whose corresponding entire pathways might be ignored using classical entire pathway identification methods. Further analysis indicated that the power of a joint genes/metabolites and subpathway strategy based on their topologies may play a key role in reliably recalling disease-relevant subpathways and finding novel subpathways.