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Sample records for level set segmentation

  1. Iris segmentation using variational level set method

    Science.gov (United States)

    Roy, Kaushik; Bhattacharya, Prabir; Suen, Ching Y.

    2011-04-01

    Continuous efforts have been made to process degraded iris images for enhancement of the iris recognition performance in unconstrained situations. Recently, many researchers have focused on developing the iris segmentation techniques, which can deal with iris images in a non-cooperative environment where the probability of acquiring unideal iris images is very high due to gaze deviation, noise, blurring, and occlusion by eyelashes, eyelids, glasses, and hair. Although there have been many iris segmentation methods, most focus primarily on the accurate detection of iris images captured in a closely controlled environment. The novelty of this research effort is that we propose to apply a variational level set-based curve evolution scheme that uses a significantly larger time step to numerically solve the evolution partial differential equation (PDE) for segmentation of an unideal iris image accurately, and thereby, speeding up the curve evolution process drastically. The iris boundary represented by the variational level set may break and merge naturally during evolution, and thus, the topological changes are handled automatically. The proposed variational model is also robust against poor localization and weak iris/sclera boundaries. In order to solve the size irregularities occurring due to arbitrary shapes of the extracted iris/pupil regions, a simple method is applied based on connection of adjacent contour points. Furthermore, to reduce the noise effect, we apply a pixel-wise adaptive 2D Wiener filter. The verification and identification performance of the proposed scheme is validated on three challenging iris image datasets, namely, the ICE 2005, the WVU Unideal, and the UBIRIS Version 1.

  2. Segmenting the Parotid Gland using Registration and Level Set Methods

    DEFF Research Database (Denmark)

    Hollensen, Christian; Hansen, Mads Fogtmann; Højgaard, Liselotte;

    The bilateral parotid glands were segmented using a registration scheme followed by level set segmentation. A training set consisting of computerized tomography from 10 patients with segmentation of the bilateral glands were used to optimize the parameters of registration and level set segmentation....... The method was evaluated on a test set consisting of 8 corresponding data sets. The attained total volume Dice coefficient and mean Haussdorff distance were 0.61 ± 0.20 and 15.6 ± 7.4 mm respectively. The method has improvement potential which could be exploited in order for clinical introduction....

  3. A CT Image Segmentation Algorithm Based on Level Set Method

    Institute of Scientific and Technical Information of China (English)

    QU Jing-yi; SHI Hao-shan

    2006-01-01

    Level Set methods are robust and efficient numerical tools for resolving curve evolution in image segmentation. This paper proposes a new image segmentation algorithm based on Mumford-Shah module. The method is used to CT images and the experiment results demonstrate its efficiency and veracity.

  4. A new level set model for cell image segmentation

    Science.gov (United States)

    Ma, Jing-Feng; Hou, Kai; Bao, Shang-Lian; Chen, Chun

    2011-02-01

    In this paper we first determine three phases of cell images: background, cytoplasm and nucleolus according to the general physical characteristics of cell images, and then develop a variational model, based on these characteristics, to segment nucleolus and cytoplasm from their relatively complicated backgrounds. In the meantime, the preprocessing obtained information of cell images using the OTSU algorithm is used to initialize the level set function in the model, which can speed up the segmentation and present satisfactory results in cell image processing.

  5. A new level set model for cell image segmentation

    Institute of Scientific and Technical Information of China (English)

    Ma Jing-Feng; Hou Kai; Bao Shang-Lian; Chen Chun

    2011-01-01

    In this paper we first determine three phases of cell images: background, cytoplasm and nucleolus according to the general physical characteristics of cell images, and then develop a variational model, based on these characteristics, to segment nucleolus and cytoplasm from their relatively complicated backgrounds. In the meantime, the preprocessing obtained information of cell images using the OTSU algorithm is used to initialize the level set function in the model, which can speed up the segmentation and present satisfactory results in cell image processing.

  6. Haustral fold segmentation with curvature-guided level set evolution.

    Science.gov (United States)

    Zhu, Hongbin; Barish, Matthew; Pickhardt, Perry; Liang, Zhengrong

    2013-02-01

    Human colon has complex structures mostly because of the haustral folds. The folds are thin flat protrusions on the colon wall, which complicate the shape analysis for computer-aided detection (CAD) of colonic polyps. Fold segmentation may help reduce the structural complexity, and the folds can serve as an anatomic reference for computed tomographic colonography (CTC). Therefore, in this study, based on a model of the haustral fold boundaries, we developed a level-set approach to automatically segment the fold surfaces. To evaluate the developed fold segmentation algorithm, we first established the ground truth of haustral fold boundaries by experts' drawing on 15 patient CTC datasets without severe under/over colon distention from two medical centers. The segmentation algorithm successfully detected 92.7% of the folds in the ground truth. In addition to the sensitivity measure, we further developed a merit of segmented-area ratio (SAR), i.e., the ratio between the area of the intersection and union of the expert-drawn folds and the area of the automatically segmented folds, to measure the segmentation accuracy. The segmentation algorithm reached an average value of SAR = 86.2%, showing a good match with the ground truth on the fold surfaces. We believe the automatically segmented fold surfaces have the potential to benefit many postprocedures in CTC, such as CAD, taenia coli extraction, supine-prone registration, etc.

  7. MEDICAL IMAGE SEGMENTATION BASED ON A MODIFIED LEVEL SET ALGORITHM

    Institute of Scientific and Technical Information of China (English)

    Yang Yong; Lin Pan; Zheng Chongxun; Gu Jianwen

    2005-01-01

    Objective To present a novel modified level set algorithm for medical image segmentation. Methods The algorithm is developed by substituting the speed function of level set algorithm with the region and gradient information of the image instead of the conventional gradient information. This new algorithm has been tested by a series of different modality medical images. Results We present various examples and also evaluate and compare the performance of our method with the classical level set method on weak boundaries and noisy images. Conclusion Experimental results show the proposed algorithm is effective and robust.

  8. Cardiac MR image segmentation using CHNN and level set method

    Institute of Scientific and Technical Information of China (English)

    王洪元; 周则明; 王平安; 夏德深

    2004-01-01

    Although cardiac magnetic resonance imaging (MRI) can provide high spatial resolution image, the area gray level inhomogenization, weak boundary and artifact often can be found in MR images. So, the MR images segmentation using the gradient-based methods is poor in quality and efficiency. An algorithm, based on the competitive hopfield neural network (CHNN) and the curve propagation, is proposed for cardiac MR images segmentation in this paper. The algorithm is composed of two phases. In first phase, a CHNN is used to classify the image objects, and to make gray level homogenization and to recognize weak boundaries in objects. In second phase, based on the classified results, the level set velocity function is created and the object boundaries are extracted with the curve propagation algorithm of the narrow band-based level set. The test results are promising and encouraging.

  9. Segmentation of Bacteria Image Based on Level Set Method

    Institute of Scientific and Technical Information of China (English)

    WANG Hua; CHEN Chun-xiao; HU Yong-hong; YANG Wen-ge

    2008-01-01

    In biology ferment engineering, accurate statistics of the quantity of bacte-ria is one of the most important subjects. In this paper, the quantity of bacteria which was observed traditionally manuauy can be detected automatically. Image acquisition and pro-cessing system is designed to accomplish image preprocessing, image segmentation and statistics of the quantity of bacteria. Segmentation of bacteria images is successfully real-ized by means of a region-based level set method and then the quantity of bacteria is com-puted precisely, which plays an important role in optimizing the growth conditions of bac-teria.

  10. Medical image segmentation using level set and watershed transform

    Science.gov (United States)

    Zhu, Fuping; Tian, Jie

    2003-07-01

    One of the most popular level set algorithms is the so-called fast marching method. In this paper, a medical image segmentation algorithm is proposed based on the combination of fast marching method and watershed transformation. First, the original image is smoothed using nonlinear diffusion filter, then the smoothed image is over-segmented by the watershed algorithm. Last, the image is segmented automatically using the modified fast marching method. Due to introducing over-segmentation, the arrival time the seeded point to the boundary of region should be calculated. For other pixels inside the region of the seeded point, the arrival time is not calculated because of the region homogeneity. So the algorithm"s speed improves greatly. Moreover, the speed function is redefined based on the statistical similarity degree of the nearby regions. We also extend our algorithm to 3D circumstance and segment medical image series. Experiments show that the algorithm can fast and accurately obtain segmentation results of medical images.

  11. Variational level set segmentation for forest based on MCMC sampling

    Science.gov (United States)

    Yang, Tie-Jun; Huang, Lin; Jiang, Chuan-xian; Nong, Jian

    2014-11-01

    Environmental protection is one of the themes of today's world. The forest is a recycler of carbon dioxide and natural oxygen bar. Protection of forests, monitoring of forest growth is long-term task of environmental protection. It is very important to automatically statistic the forest coverage rate using optical remote sensing images and the computer, by which we can timely understand the status of the forest of an area, and can be freed from tedious manual statistics. Towards the problem of computational complexity of the global optimization using convexification, this paper proposes a level set segmentation method based on Markov chain Monte Carlo (MCMC) sampling and applies it to forest segmentation in remote sensing images. The presented method needs not to do any convexity transformation for the energy functional of the goal, and uses MCMC sampling method with global optimization capability instead. The possible local minima occurring by using gradient descent method is also avoided. There are three major contributions in the paper. Firstly, by using MCMC sampling, the convexity of the energy functional is no longer necessary and global optimization can still be achieved. Secondly, taking advantage of the data (texture) and knowledge (a priori color) to guide the construction of Markov chain, the convergence rate of Markov chains is improved significantly. Finally, the level set segmentation method by integrating a priori color and texture for forest is proposed. The experiments show that our method can efficiently and accurately segment forest in remote sensing images.

  12. A Level Set Approach to Image Segmentation With Intensity Inhomogeneity.

    Science.gov (United States)

    Zhang, Kaihua; Zhang, Lei; Lam, Kin-Man; Zhang, David

    2016-02-01

    It is often a difficult task to accurately segment images with intensity inhomogeneity, because most of representative algorithms are region-based that depend on intensity homogeneity of the interested object. In this paper, we present a novel level set method for image segmentation in the presence of intensity inhomogeneity. The inhomogeneous objects are modeled as Gaussian distributions of different means and variances in which a sliding window is used to map the original image into another domain, where the intensity distribution of each object is still Gaussian but better separated. The means of the Gaussian distributions in the transformed domain can be adaptively estimated by multiplying a bias field with the original signal within the window. A maximum likelihood energy functional is then defined on the whole image region, which combines the bias field, the level set function, and the piecewise constant function approximating the true image signal. The proposed level set method can be directly applied to simultaneous segmentation and bias correction for 3 and 7T magnetic resonance images. Extensive evaluation on synthetic and real-images demonstrate the superiority of the proposed method over other representative algorithms.

  13. Fast Streaming 3D Level set Segmentation on the GPU for Smooth Multi-phase Segmentation

    DEFF Research Database (Denmark)

    Sharma, Ojaswa; Zhang, Qin; Anton, François

    2011-01-01

    Level set method based segmentation provides an efficient tool for topological and geometrical shape handling, but it is slow due to high computational burden. In this work, we provide a framework for streaming computations on large volumetric images on the GPU. A streaming computational model...

  14. Integrating spatial fuzzy clustering with level set methods for automated medical image segmentation.

    Science.gov (United States)

    Li, Bing Nan; Chui, Chee Kong; Chang, Stephen; Ong, S H

    2011-01-01

    The performance of the level set segmentation is subject to appropriate initialization and optimal configuration of controlling parameters, which require substantial manual intervention. A new fuzzy level set algorithm is proposed in this paper to facilitate medical image segmentation. It is able to directly evolve from the initial segmentation by spatial fuzzy clustering. The controlling parameters of level set evolution are also estimated from the results of fuzzy clustering. Moreover the fuzzy level set algorithm is enhanced with locally regularized evolution. Such improvements facilitate level set manipulation and lead to more robust segmentation. Performance evaluation of the proposed algorithm was carried on medical images from different modalities. The results confirm its effectiveness for medical image segmentation.

  15. GAUSSIAN MIXTURE MODEL BASED LEVEL SET TECHNIQUE FOR AUTOMATED SEGMENTATION OF CARDIAC MR IMAGES

    Directory of Open Access Journals (Sweden)

    G. Dharanibai,

    2011-04-01

    Full Text Available In this paper we propose a Gaussian Mixture Model (GMM integrated level set method for automated segmentation of left ventricle (LV, right ventricle (RV and myocardium from short axis views of cardiacmagnetic resonance image. By fitting GMM to the image histogram, global pixel intensity characteristics of the blood pool, myocardium and background are estimated. GMM provides initial segmentation andthe segmentation solution is regularized using level set. Parameters for controlling the level set evolution are automatically estimated from the Bayesian inference classification of pixels. We propose a new speed function that combines edge and region information that stops the evolving level set at the myocardial boundary. Segmentation efficacy is analyzed qualitatively via visual inspection. Results show the improved performance of our of proposed speed function over the conventional Bayesian driven adaptive speed function in automatic segmentation of myocardium

  16. Multi-domain, higher order level set scheme for 3D image segmentation on the GPU

    DEFF Research Database (Denmark)

    Sharma, Ojaswa; Zhang, Qin; Anton, François;

    2010-01-01

    Level set method based segmentation provides an efficient tool for topological and geometrical shape handling. Conventional level set surfaces are only $C^0$ continuous since the level set evolution involves linear interpolation to compute derivatives. Bajaj et al. present a higher order method t...

  17. Level set based vertebra segmentation for the evaluation of Ankylosing Spondylitis

    Science.gov (United States)

    Tan, Sovira; Yao, Jianhua; Ward, Michael M.; Yao, Lawrence; Summers, Ronald M.

    2006-03-01

    Ankylosing Spondylitis is a disease of the vertebra where abnormal bone structures (syndesmophytes) grow at intervertebral disk spaces. Because this growth is so slow as to be undetectable on plain radiographs taken over years, it is necessary to resort to computerized techniques to complement qualitative human judgment with precise quantitative measures on 3-D CT images. Very fine segmentation of the vertebral body is required to capture the small structures caused by the pathology. We propose a segmentation algorithm based on a cascade of three level set stages and requiring no training or prior knowledge. First, the noise inside the vertebral body that often blocks the proper evolution of level set surfaces is attenuated by a sigmoid function whose parameters are determined automatically. The 1st level set (geodesic active contour) is designed to roughly segment the interior of the vertebra despite often highly inhomogeneous and even discontinuous boundaries. The result is used as an initial contour for the 2nd level set (Laplacian level set) that closely captures the inner boundary of the cortical bone. The last level set (reversed Laplacian level set) segments the outer boundary of the cortical bone and also corrects small flaws of the previous stage. We carried out extensive tests on 30 vertebrae (5 from each of 6 patients). Two medical experts scored the results at intervertebral disk spaces focusing on end plates and syndesmophytes. Only two minor segmentation errors at vertebral end plates were reported and two syndesmophytes were considered slightly under-segmented.

  18. An Enhanced Level Set Segmentation for Multichannel Images Using Fuzzy Clustering and Lattice Boltzmann Method

    Directory of Open Access Journals (Sweden)

    Savita Agrawal

    2015-11-01

    Full Text Available In the last decades, image segmentation has proved its applicability in various areas like satellite image processing, medical image processing and many more. In the present scenario the researchers tries to develop hybrid image segmentation techniques to generates efficient segmentation. Due to the development of the parallel programming, the lattice Boltzmann method (LBM has attracted much attention as a fast alternative approach for solving partial differential equations. In this project work, first designed an energy functional based on the fuzzy c-means objective function which incorporates the bias field that accounts for the intensity in homogeneity of the real-world image. Using the gradient descent method, corresponding level set equations are obtained from which we deduce a fuzzy external force for the LBM solver based on the model by Zhao. The method is speedy, robust for denoise, and does not dependent on the position of the initial contour, effective in the presence of intensity in homogeneity, highly parallelizable and can detect objects with or without edges. For the implementation of segmentation techniques defined for gray images, most of the time researchers determines single channel segments of the images and superimposes the single channel segment information on color images. This idea leads to provide color image segmentation using single channel segments of multi channel images. Though this method is widely adopted but doesn’t provide complete true segmentation of multichannel ie color images because a color image contains three different channels for Red, green and blue components. Hence segmenting a color image, by having only single channel segments information, will definitely loose important segment regions of color images. To overcome this problem this paper work starts with the development of Enhanced Level Set Segmentation for single channel Images Using Fuzzy Clustering and Lattice Boltzmann Method. For the

  19. An Enhanced Level Set Segmentation for Multichannel Images Using Fuzzy Clustering and Lattice Boltzmann Method

    Directory of Open Access Journals (Sweden)

    Savita Agrawal

    2014-05-01

    Full Text Available In the last decades, image segmentation has proved its applicability in various areas like satellite image processing, medical image processing and many more. In the present scenario the researchers tries to develop hybrid image segmentation techniques to generates efficient segmentation. Due to the development of the parallel programming, the lattice Boltzmann met hod (LBM has attracted much attention as a fast alternative approach for solving partial differential equations. In this project work, first designed an energy functional based on the fuzzy c-means objective function which incorporates the bias field that accounts for the intensity in homogeneity of the real-world image. Using the gradient descent method, corresponding level set equations are obtained from which we deduce a fuzzy external force for the LBM solver based on the model by Zhao. The method is speedy, robust for denoise, and does not dependent on the position of the initial contour, effective in the presence of intensity in homogeneity, highly parallelizable and can detect objects with or without edges. For the implementation of segmentation techniques defined for gr ay images, most of the time researchers determines single channel segments of the images and superimposes the single channel segment information on color images. This idea leads to provide color image segmentation using single channel segments of multi chann el images. Though this method is widely adopted but doesn’t provide complete true segmentation of multichannel ie color images because a color image contains three different channels for Red, green and blue components. Hence segmenting a color image, b y having only single channel segments information, will definitely loose important segment regions of color images. To overcome this problem this paper work starts with the development of Enhanced Level Set Segmentation for single channel Images Using Fuzzy Clustering and Lattice Boltzmann Method. For the

  20. A Novel Image Segmentation Algorithm Based on Neutrosophic Filtering and Level Set

    Directory of Open Access Journals (Sweden)

    Yanhui Guo

    2016-03-01

    Full Text Available Image segmentation is an important step in image processing and analysis, pattern recognition, and machine vision. A few of algorithms based on level set have been proposed for image segmentation in the last twenty years. However, these methods are time consuming, and sometime fail to extract the correct regions especially for noisy images. Recently, neutrosophic set (NS theory has been applied to image processing for noisy images with indeterminant information. In this paper, a novel image segmentation approach is proposed based on the filter in NS and level set theory. At first, the image is transformed into NS domain, which is described by three membership sets (T, I and F. Then, a filter is newly defined and employed to reduce the indeterminacy of the image. Finally, a level set algorithm is used in the image after filtering operation for image segmentation. Experiments have been conducted using different images. The results demonstrate that the proposed method can segment the images effectively and accurately. It is especially able to remove the noise effect and extract the correct regions on both the noise-free images and the images with different levels of noise.

  1. A level set based segmentation approach for point-sampled surfaces

    Institute of Scientific and Technical Information of China (English)

    MIAO Yong-wei; FENG Jie-qing; ZHENG Guo-xian; PENG Qun-sheng

    2007-01-01

    Segmenting a complex 3D surface model into some visually meaningful sub-parts is one of the fundamental problems in digital geometry processing. In this paper, a novel segmentation approach of point-sampled surfaces is proposed, which is based on the level set evolution scheme. To segment the model so as to align the patch boundaries with high curvature zones, the driven speed function for the zero level set inside narrow band is defined by the extended curvature field, which approaches zero speed as the propagating front approaches high curvature zone. The effectiveness of the proposed approach is demonstrated by our experimental results. Furthermore, two applications of model segmentation are illustrated, such as piecewise parameterization and local editing for point-sampled geometry.

  2. A novel breast ultrasound image segmentation algorithm based on neutrosophic similarity score and level set.

    Science.gov (United States)

    Guo, Yanhui; Şengür, Abdulkadir; Tian, Jia-Wei

    2016-01-01

    Breast ultrasound (BUS) image segmentation is a challenging task due to the speckle noise, poor quality of the ultrasound images and size and location of the breast lesions. In this paper, we propose a new BUS image segmentation algorithm based on neutrosophic similarity score (NSS) and level set algorithm. At first, the input BUS image is transferred to the NS domain via three membership subsets T, I and F, and then, a similarity score NSS is defined and employed to measure the belonging degree to the true tumor region. Finally, the level set method is used to segment the tumor from the background tissue region in the NSS image. Experiments have been conducted on a variety of clinical BUS images. Several measurements are used to evaluate and compare the proposed method's performance. The experimental results demonstrate that the proposed method is able to segment the BUS images effectively and accurately. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  3. Total variation based edge enhancement for level set segmentation and asymmetry analysis in breast thermograms.

    Science.gov (United States)

    Prabha, S; Anandh, K R; Sujatha, C M; Ramakrishnan, S

    2014-01-01

    In this work, an attempt has been made to perform asymmetry analysis in breast thermograms using non-linear total variation diffusion filter and reaction diffusion based level set method. Breast images used in this study are obtained from online database of the project PROENG. Initially the images are subjected to total variation (TV) diffusion filter to generate the edge map. Reaction diffusion based level set method is employed to segment the breast tissues using TV edge map as stopping boundary function. Asymmetry analysis is performed on the segmented breast tissues using wavelet based structural texture features. The results show that nonlinear total variation based reaction diffusion level set method could efficiently segment the breast tissues. This method yields high correlation between the segmented output and the ground truth than the conventional level set. Structural texture features extracted from the wavelet coefficients are found to be significant in demarcating normal and abnormal tissues. Hence, it appears that the asymmetry analysis on segmented breast tissues extracted using total variation edge map can be used efficiently to identify the pathological conditions of breast thermograms.

  4. Moving Object Segmentation Using Level Set Method with Shape Prior, Color and Texture

    Directory of Open Access Journals (Sweden)

    Shu Xian

    2013-10-01

    Full Text Available This paper presents a method for the combination of different feature cues in a level set based moving object segmentation framework. To distinguish object from background, motion detection is firstly adopted to locate object position and obtain coarse shape prior. Moreover, the color and texture feature descriptors that represent object contour are designed in this dissertation. Then the finer segmentation solution based on the color and texture difference between the object and background is proposed, which avoids the invalid feature components to hamper segmentation and improves the accuracy. Extensive experiments have been carried out on surveillance video sequences to validate the proposed method

  5. Level set segmentation of medical images based on local region statistics and maximum a posteriori probability.

    Science.gov (United States)

    Cui, Wenchao; Wang, Yi; Lei, Tao; Fan, Yangyu; Feng, Yan

    2013-01-01

    This paper presents a variational level set method for simultaneous segmentation and bias field estimation of medical images with intensity inhomogeneity. In our model, the statistics of image intensities belonging to each different tissue in local regions are characterized by Gaussian distributions with different means and variances. According to maximum a posteriori probability (MAP) and Bayes' rule, we first derive a local objective function for image intensities in a neighborhood around each pixel. Then this local objective function is integrated with respect to the neighborhood center over the entire image domain to give a global criterion. In level set framework, this global criterion defines an energy in terms of the level set functions that represent a partition of the image domain and a bias field that accounts for the intensity inhomogeneity of the image. Therefore, image segmentation and bias field estimation are simultaneously achieved via a level set evolution process. Experimental results for synthetic and real images show desirable performances of our method.

  6. A Variational Level Set Model Combined with FCMS for Image Clustering Segmentation

    Directory of Open Access Journals (Sweden)

    Liming Tang

    2014-01-01

    Full Text Available The fuzzy C means clustering algorithm with spatial constraint (FCMS is effective for image segmentation. However, it lacks essential smoothing constraints to the cluster boundaries and enough robustness to the noise. Samson et al. proposed a variational level set model for image clustering segmentation, which can get the smooth cluster boundaries and closed cluster regions due to the use of level set scheme. However it is very sensitive to the noise since it is actually a hard C means clustering model. In this paper, based on Samson’s work, we propose a new variational level set model combined with FCMS for image clustering segmentation. Compared with FCMS clustering, the proposed model can get smooth cluster boundaries and closed cluster regions due to the use of level set scheme. In addition, a block-based energy is incorporated into the energy functional, which enables the proposed model to be more robust to the noise than FCMS clustering and Samson’s model. Some experiments on the synthetic and real images are performed to assess the performance of the proposed model. Compared with some classical image segmentation models, the proposed model has a better performance for the images contaminated by different noise levels.

  7. MULTI-REGION SEGMENTATION OF SAR IMAGE BY A MULTIPHASE LEVEL SET APPROACH

    Institute of Scientific and Technical Information of China (English)

    Fu Yusheng; Cao Zongjie; Pi Yiming

    2008-01-01

    In this letter, a multiphase level set approach unifying region and boundary-based infor- mation for multi-region segmentation of Synthetic Aperture Radar (SAR) image is presented. An energy functional that is applicable for SAR image segmentation is defined. It consists of two terms describing the local statistic characteristics and the gradient characteristics of SAR image respectively. A multiphase level set model that explicitly describes the different regions in one image is proposed. The purpose of such a multiphase model is not only to simplify the way of denoting multi-region by level set but also to guarantee the accuracy of segmentation. According to the presented multiphase model, the curve evolution equations with respect to edge curves are deduced. The multi-region segmentation is implemented by the numeric solution of the partial differential equations. The performance of the approach is verified by both simulation and real SAR images. The experiments show that the proposed algorithm reduces the speckle effect on segmentation and increases the boundary alignment accuracy, thus correctly divides the multi-region SAR image into different homogenous regions.

  8. Adaptive segmentation of magnetic resonance images with intensity inhomogeneity using level set method.

    Science.gov (United States)

    Liu, Lixiong; Zhang, Qi; Wu, Min; Li, Wu; Shang, Fei

    2013-05-01

    It is a big challenge to segment magnetic resonance (MR) images with intensity inhomogeneity. The widely used segmentation algorithms are region based, which mostly rely on the intensity homogeneity, and could bring inaccurate results. In this paper, we propose a novel region-based active contour model in a variational level set formulation. Based on the fact that intensities in a relatively small local region are separable, a local intensity clustering criterion function is defined. Then, the local function is integrated around the neighborhood center to formulate a global intensity criterion function, which defines the energy term to drive the evolution of the active contour locally. Simultaneously, an intensity fitting term that drives the motion of the active contour globally is added to the energy. In order to segment the image fast and accurately, we utilize a coefficient to make the segmentation adaptive. Finally, the energy is incorporated into a level set formulation with a level set regularization term, and the energy minimization is conducted by a level set evolution process. Experiments on synthetic and real MR images show the effectiveness of our method. Copyright © 2013 Elsevier Inc. All rights reserved.

  9. Breast mass segmentation in digital mammography based on pulse coupled neural network and level set method

    Science.gov (United States)

    Xie, Weiying; Ma, Yide; Li, Yunsong

    2015-05-01

    A novel approach to mammographic image segmentation, termed as PCNN-based level set algorithm, is presented in this paper. Just as its name implies, a method based on pulse coupled neural network (PCNN) in conjunction with the variational level set method for medical image segmentation. To date, little work has been done on detecting the initial zero level set contours based on PCNN algorithm for latterly level set evolution. When all the pixels of the input image are fired by PCNN, the small pixel value will be a much more refined segmentation. In mammographic image, the breast tumor presents big pixel value. Additionally, the mammographic image with predominantly dark region, so that we firstly obtain the negative of mammographic image with predominantly dark region except the breast tumor before all the pixels of an input image are fired by PCNN. Therefore, in here, PCNN algorithm is employed to achieve mammary-specific, initial mass contour detection. After that, the initial contours are all extracted. We define the extracted contours as the initial zero level set contours for automatic mass segmentation by variational level set in mammographic image analysis. What's more, a new proposed algorithm improves external energy of variational level set method in terms of mammographic images in low contrast. In accordance with the gray scale of mass region in mammographic image is higher than the region surrounded, so the Laplace operator is used to modify external energy, which could make the bright spot becoming much brighter than the surrounded pixels in the image. A preliminary evaluation of the proposed method performs on a known public database namely MIAS, rather than synthetic images. The experimental results demonstrate that our proposed approach can potentially obtain better masses detection results in terms of sensitivity and specificity. Ultimately, this algorithm could lead to increase both sensitivity and specificity of the physicians' interpretation of

  10. Unsupervised segmentation of the prostate using MR images based on level set with a shape prior.

    Science.gov (United States)

    Liu, Xin; Langer, D L; Haider, M A; Van der Kwast, T H; Evans, A J; Wernick, M N; Yetik, I S

    2009-01-01

    Prostate cancer is the second leading cause of cancer death in American men. Current prostate MRI can benefit from automated tumor localization to help guide biopsy, radiotherapy and surgical planning. An important step of automated prostate cancer localization is the segmentation of the prostate. In this paper, we propose a fully automatic method for the segmentation of the prostate. We firstly apply a deformable ellipse model to find an ellipse that best fits the prostate shape. Then, this ellipse is used to initiate the level set and constrain the level set evolution with a shape penalty term. Finally, certain post processing methods are applied to refine the prostate boundaries. We apply the proposed method to real diffusion-weighted (DWI) MRI images data to test the performance. Our results show that accurate segmentation can be obtained with the proposed method compared to human readers.

  11. Level set method with automatic selective local statistics for brain tumor segmentation in MR images.

    Science.gov (United States)

    Thapaliya, Kiran; Pyun, Jae-Young; Park, Chun-Su; Kwon, Goo-Rak

    2013-01-01

    The level set approach is a powerful tool for segmenting images. This paper proposes a method for segmenting brain tumor images from MR images. A new signed pressure function (SPF) that can efficiently stop the contours at weak or blurred edges is introduced. The local statistics of the different objects present in the MR images were calculated. Using local statistics, the tumor objects were identified among different objects. In this level set method, the calculation of the parameters is a challenging task. The calculations of different parameters for different types of images were automatic. The basic thresholding value was updated and adjusted automatically for different MR images. This thresholding value was used to calculate the different parameters in the proposed algorithm. The proposed algorithm was tested on the magnetic resonance images of the brain for tumor segmentation and its performance was evaluated visually and quantitatively. Numerical experiments on some brain tumor images highlighted the efficiency and robustness of this method.

  12. A chance-constrained programming level set method for longitudinal segmentation of lung tumors in CT.

    Science.gov (United States)

    Rouchdy, Youssef; Bloch, Isabelle

    2011-01-01

    This paper presents a novel stochastic level set method for the longitudinal tracking of lung tumors in computed tomography (CT). The proposed model addresses the limitations of registration based and segmentation based methods for longitudinal tumor tracking. It combines the advantages of each approach using a new probabilistic framework, namely Chance-Constrained Programming (CCP). Lung tumors can shrink or grow over time, which can be reflected in large changes of shape, appearance and volume in CT images. Traditional level set methods with a priori knowledge about shape are not suitable since the tumors are undergoing random and large changes in shape. Our CCP level set model allows to introduce a flexible prior to track structures with a highly variable shape by permitting a constraint violation of the prior up to a specified probability level. The chance constraints are computed from two given points by the user or from segmented tumors from a reference image. The reference image can be one of the images studied or an external template. We present a numerical scheme to approximate the solution of the proposed model and apply it to track lung tumors in CT. Finally, we compare our approach with a Bayesian level set. The CCP level set model gives the best results: it is more coherent with the manual segmentation.

  13. Comparison of bladder segmentation using deep-learning convolutional neural network with and without level sets

    Science.gov (United States)

    Cha, Kenny H.; Hadjiiski, Lubomir M.; Samala, Ravi K.; Chan, Heang-Ping; Cohan, Richard H.; Caoili, Elaine M.

    2016-03-01

    We are developing a CAD system for detection of bladder cancer in CTU. In this study we investigated the application of deep-learning convolutional neural network (DL-CNN) to the segmentation of the bladder, which is a challenging problem because of the strong boundary between the non-contrast and contrast-filled regions in the bladder. We trained a DL-CNN to estimate the likelihood of a pixel being inside the bladder using neighborhood information. The segmented bladder was obtained from thresholding and hole-filling of the likelihood map. We compared the segmentation performance of the DL-CNN alone and with additional cascaded 3D and 2D level sets to refine the segmentation using 3D hand-segmented contours as reference standard. The segmentation accuracy was evaluated by five performance measures: average volume intersection %, average % volume error, average absolute % error, average minimum distance, and average Jaccard index for a data set of 81 training and 92 test cases. For the training set, DLCNN with level sets achieved performance measures of 87.2+/-6.1%, 6.0+/-9.1%, 8.7+/-6.1%, 3.0+/-1.2 mm, and 81.9+/-7.6%, respectively, while the DL-CNN alone obtained the values of 73.6+/-8.5%, 23.0+/-8.5%, 23.0+/-8.5%, 5.1+/-1.5 mm, and 71.5+/-9.2%, respectively. For the test set, the DL-CNN with level sets achieved performance measures of 81.9+/-12.1%, 10.2+/-16.2%, 14.0+/-13.0%, 3.6+/-2.0 mm, and 76.2+/-11.8%, respectively, while DL-CNN alone obtained 68.7+/-12.0%, 27.2+/-13.7%, 27.4+/-13.6%, 5.7+/-2.2 mm, and 66.2+/-11.8%, respectively. DL-CNN alone is effective in segmenting bladders but may not follow the details of the bladder wall. The combination of DL-CNN with level sets provides highly accurate bladder segmentation.

  14. Polarimetric SAR Image Object Segmentation via Level Set with Stationary Global Minimum

    Directory of Open Access Journals (Sweden)

    Wen Yang

    2010-01-01

    Full Text Available We present a level set-based method for object segmentation in polarimetric synthetic aperture radar (PolSAR images. In our method, a modified energy functional via active contour model is proposed based on complex Gaussian/Wishart distribution model for both single-look and multilook PolSAR images. The modified functional has two interesting properties: (1 the curve evolution does not enter into local minimum; (2 the level set function has a unique stationary convergence state. With these properties, the desired object can be segmented more accurately. Besides, the modified functional allows us to set an effective automatic termination criterion and makes the algorithm more practical. The experimental results on synthetic and real PolSAR images demonstrate the effectiveness of our method.

  15. A fast level set method for synthetic aperture radar ocean image segmentation.

    Science.gov (United States)

    Huang, Xiaoxia; Huang, Bo; Li, Hongga

    2009-01-01

    Segmentation of high noise imagery like Synthetic Aperture Radar (SAR) images is still one of the most challenging tasks in image processing. While level set, a novel approach based on the analysis of the motion of an interface, can be used to address this challenge, the cell-based iterations may make the process of image segmentation remarkably slow, especially for large-size images. For this reason fast level set algorithms such as narrow band and fast marching have been attempted. Built upon these, this paper presents an improved fast level set method for SAR ocean image segmentation. This competent method is dependent on both the intensity driven speed and curvature flow that result in a stable and smooth boundary. Notably, it is optimized to track moving interfaces for keeping up with the point-wise boundary propagation using a single list and a method of fast up-wind scheme iteration. The list facilitates efficient insertion and deletion of pixels on the propagation front. Meanwhile, the local up-wind scheme is used to update the motion of the curvature front instead of solving partial differential equations. Experiments have been carried out on extraction of surface slick features from ERS-2 SAR images to substantiate the efficacy of the proposed fast level set method.

  16. Segmentation of ventricles in Alzheimer mr images using anisotropic diffusion filtering and level set method.

    Science.gov (United States)

    Anandh, K R; Sujatha, C M; Ramakrishnan, S

    2014-01-01

    Ventricle enlargement is a useful structural biomarker for the diagnosis of Alzheimer’s Disease (AD). This devastating neurodegenerative disorder results in progression of dementia. Although AD results in the passive increment of ventricle volume, there exists a large overlap in the volume measurements of AD and normal subjects. Hence, shape based analysis of ventricle dilation is appropriate to detect the subtle morphological changes among these two groups. In this work, segmentation of ventricle in Alzheimer MR images is employed using level set method and anisotropic based diffusion filtering. Images considered for this study are preprocessed using filters. Anisotropic based diffusion filtering is employed to extract the edge map. This filtering performs region specific smoothing process using the diffusion coefficient as a function of image gradient. Filtered images are subjected to level set method which employs an improved diffusion rate equation for the level set evolution. Geometric features are extracted from the segmented ventricles. Results show that the diffusion filter could extract edge map with sharp region boundaries. The modified level set method is able to extract the morphological changes in ventricles. The observed morphological changes are distinct for normal and AD subjects (p < 0.0001). It is also observed that the sizes of ventricle in the AD subjects are noticeably enlarged when compared to normal subjects. Features obtained from the segmented ventricles are also clearly distinct and demonstrate the differences in the AD subjects. As ventricle volume and its morphometry are significant biomarkers, this study seems to be clinically relevant.

  17. Multiatlas segmentation of thoracic and abdominal anatomy with level set-based local search.

    Science.gov (United States)

    Schreibmann, Eduard; Marcus, David M; Fox, Tim

    2014-07-08

    Segmentation of organs at risk (OARs) remains one of the most time-consuming tasks in radiotherapy treatment planning. Atlas-based segmentation methods using single templates have emerged as a practical approach to automate the process for brain or head and neck anatomy, but pose significant challenges in regions where large interpatient variations are present. We show that significant changes are needed to autosegment thoracic and abdominal datasets by combining multi-atlas deformable registration with a level set-based local search. Segmentation is hierarchical, with a first stage detecting bulk organ location, and a second step adapting the segmentation to fine details present in the patient scan. The first stage is based on warping multiple presegmented templates to the new patient anatomy using a multimodality deformable registration algorithm able to cope with changes in scanning conditions and artifacts. These segmentations are compacted in a probabilistic map of organ shape using the STAPLE algorithm. Final segmentation is obtained by adjusting the probability map for each organ type, using customized combinations of delineation filters exploiting prior knowledge of organ characteristics. Validation is performed by comparing automated and manual segmentation using the Dice coefficient, measured at an average of 0.971 for the aorta, 0.869 for the trachea, 0.958 for the lungs, 0.788 for the heart, 0.912 for the liver, 0.884 for the kidneys, 0.888 for the vertebrae, 0.863 for the spleen, and 0.740 for the spinal cord. Accurate atlas segmentation for abdominal and thoracic regions can be achieved with the usage of a multi-atlas and perstructure refinement strategy. To improve clinical workflow and efficiency, the algorithm was embedded in a software service, applying the algorithm automatically on acquired scans without any user interaction.

  18. Level set segmentation of brain magnetic resonance images based on local Gaussian distribution fitting energy.

    Science.gov (United States)

    Wang, Li; Chen, Yunjie; Pan, Xiaohua; Hong, Xunning; Xia, Deshen

    2010-05-15

    This paper presents a variational level set approach in a multi-phase formulation to segmentation of brain magnetic resonance (MR) images with intensity inhomogeneity. In our model, the local image intensities are characterized by Gaussian distributions with different means and variances. We define a local Gaussian distribution fitting energy with level set functions and local means and variances as variables. The means and variances of local intensities are considered as spatially varying functions. Therefore, our method is able to deal with intensity inhomogeneity without inhomogeneity correction. Our method has been applied to 3T and 7T MR images with promising results.

  19. Minimum mutual information based level set clustering algorithm for fast MRI tissue segmentation.

    Science.gov (United States)

    Dai, Shuanglu; Man, Hong; Zhan, Shu

    2015-01-01

    Accurate and accelerated MRI tissue recognition is a crucial preprocessing for real-time 3d tissue modeling and medical diagnosis. This paper proposed an information de-correlated clustering algorithm implemented by variational level set method for fast tissue segmentation. The key idea is to design a local correlation term between original image and piecewise constant into the variational framework. The minimized correlation will then lead to de-correlated piecewise regions. Firstly, by introducing a continuous bounded variational domain describing the image, a probabilistic image restoration model is assumed to modify the distortion. Secondly, regional mutual information is introduced to measure the correlation between piecewise regions and original images. As a de-correlated description of the image, piecewise constants are finally solved by numerical approximation and level set evolution. The converged piecewise constants automatically clusters image domain into discriminative regions. The segmentation results show that our algorithm performs well in terms of time consuming, accuracy, convergence and clustering capability.

  20. Active contour segmentation using level set function with enhanced image from prior intensity.

    Science.gov (United States)

    Kim, Sunhee; Kim, Youngjun; Lee, Deukhee; Park, Sehyung

    2015-01-01

    This paper presents a new active contour segmentation model using a level set function that can correctly capture both the strong and the weak boundaries of a target enclosed by bright and dark regions at the same time. We introduce an enhanced image obtained from prior information about the intensity of the target. The enhanced image emphasizes the regions where pixels have intensities close to the prior intensity. This enables a desirable segmentation of an image having a partially low contrast with the target surrounded by regions that are brighter or darker than the target. We define an edge indicator function on an original image, and local and regularization forces on an enhanced image. An edge indicator function and two forces are incorporated in order to identify the strong and weak boundaries, respectively. We established an evolution equation of contours in the level set formulation and experimented with several medical images to show the performance of the proposed method.

  1. Segmentation of teeth in CT volumetric dataset by panoramic projection and variational level set

    Energy Technology Data Exchange (ETDEWEB)

    Hosntalab, Mohammad [Islamic Azad University, Faculty of Engineering, Science and Research Branch, Tehran (Iran); Aghaeizadeh Zoroofi, Reza [University of Tehran, Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, College of Engineering, Tehran (Iran); Abbaspour Tehrani-Fard, Ali [Islamic Azad University, Faculty of Engineering, Science and Research Branch, Tehran (Iran); Sharif University of Technology, Department of Electrical Engineering, Tehran (Iran); Shirani, Gholamreza [Faculty of Dentistry Medical Science of Tehran University, Oral and Maxillofacial Surgery Department, Tehran (Iran)

    2008-09-15

    Quantification of teeth is of clinical importance for various computer assisted procedures such as dental implant, orthodontic planning, face, jaw and cosmetic surgeries. In this regard, segmentation is a major step. In this paper, we propose a method for segmentation of teeth in volumetric computed tomography (CT) data using panoramic re-sampling of the dataset in the coronal view and variational level set. The proposed method consists of five steps as follows: first, we extract a mask in a CT images using Otsu thresholding. Second, the teeth are segmented from other bony tissues by utilizing anatomical knowledge of teeth in the jaws. Third, the proposed method is followed by estimating the arc of the upper and lower jaws and panoramic re-sampling of the dataset. Separation of upper and lower jaws and initial segmentation of teeth are performed by employing the horizontal and vertical projections of the panoramic dataset, respectively. Based the above mentioned procedures an initial mask for each tooth is obtained. Finally, we utilize the initial mask of teeth and apply a Variational level set to refine initial teeth boundaries to final contours. The proposed algorithm was evaluated in the presence of 30 multi-slice CT datasets including 3,600 images. Experimental results reveal the effectiveness of the proposed method. In the proposed algorithm, the variational level set technique was utilized to trace the contour of the teeth. In view of the fact that, this technique is based on the characteristic of the overall region of the teeth image, it is possible to extract a very smooth and accurate tooth contour using this technique. In the presence of the available datasets, the proposed technique was successful in teeth segmentation compared to previous techniques. (orig.)

  2. Segmentation of Lungs via Hybridization of CA and Level Set Algorithm

    National Research Council Canada - National Science Library

    A. Anbu Megelin Star; P. Subburaj

    2014-01-01

    ...) and then the level set algorithm is applied for acquiring the acute tumor tissues. As a result of the mentioned process, the tumor sector is segmented and the results are depicted. Studies on lung tumor datasets demonstrate 80-85% overlap performance of the proposed algorithm with less sensitivity to seed initialization, robustness with respect to heterogeneous tumor types and its efficiency in terms of computation time.

  3. Joint infrared target recognition and segmentation using a shape manifold-aware level set.

    Science.gov (United States)

    Yu, Liangjiang; Fan, Guoliang; Gong, Jiulu; Havlicek, Joseph P

    2015-04-29

    We propose new techniques for joint recognition, segmentation and pose estimation of infrared (IR) targets. The problem is formulated in a probabilistic level set framework where a shape constrained generative model is used to provide a multi-class and multi-view shape prior and where the shape model involves a couplet of view and identity manifolds (CVIM). A level set energy function is then iteratively optimized under the shape constraints provided by the CVIM. Since both the view and identity variables are expressed explicitly in the objective function, this approach naturally accomplishes recognition, segmentation and pose estimation as joint products of the optimization process. For realistic target chips, we solve the resulting multi-modal optimization problem by adopting a particle swarm optimization (PSO) algorithm and then improve the computational efficiency by implementing a gradient-boosted PSO (GB-PSO). Evaluation was performed using the Military Sensing Information Analysis Center (SENSIAC) ATR database, and experimental results show that both of the PSO algorithms reduce the cost of shape matching during CVIM-based shape inference. Particularly, GB-PSO outperforms other recent ATR algorithms, which require intensive shape matching, either explicitly (with pre-segmentation) or implicitly (without pre-segmentation).

  4. Joint Infrared Target Recognition and Segmentation Using a Shape Manifold-Aware Level Set

    Directory of Open Access Journals (Sweden)

    Liangjiang Yu

    2015-04-01

    Full Text Available We propose new techniques for joint recognition, segmentation and pose estimation of infrared (IR targets. The problem is formulated in a probabilistic level set framework where a shape constrained generative model is used to provide a multi-class and multi-view shape prior and where the shape model involves a couplet of view and identity manifolds (CVIM. A level set energy function is then iteratively optimized under the shape constraints provided by the CVIM. Since both the view and identity variables are expressed explicitly in the objective function, this approach naturally accomplishes recognition, segmentation and pose estimation as joint products of the optimization process. For realistic target chips, we solve the resulting multi-modal optimization problem by adopting a particle swarm optimization (PSO algorithm and then improve the computational efficiency by implementing a gradient-boosted PSO (GB-PSO. Evaluation was performed using the Military Sensing Information Analysis Center (SENSIAC ATR database, and experimental results show that both of the PSO algorithms reduce the cost of shape matching during CVIM-based shape inference. Particularly, GB-PSO outperforms other recent ATR algorithms, which require intensive shape matching, either explicitly (with pre-segmentation or implicitly (without pre-segmentation.

  5. Active Contours and Mumford-Shah Segmentation Based on Level Sets

    Institute of Scientific and Technical Information of China (English)

    NASSIR H.SALMAN; LIU Chong-qing(刘重庆)

    2003-01-01

    This paper is to detect regions (objects) boundaries, also to isolate and extract individual componentsfrom a medical image. This can be done using an active contours to detect regions in a given image, based on tech-niques of curve evolution, Mumford-Shah functional for segmentation and level sets. The paper classified the im-ages into different intensity regions based on Markov random field, then detected regions whose boundaries are notnecessarily defined by gradient by minimizing an energy of Mumford-Shah functional for segmentation which can beseen as a particular case of the minimal partition problem. In the level set formulation, the problem becomes amean-curvature flow like evolving the active contour, which will stop on the desired boundary. The stopping termdoes not depend on the gradient of the image, as in the classical active contour and the initial curve of level set canbe anywhere in the image, and interior contours are automatically detected. The final image segmentation is oneclosed boundary per actual region in the image.

  6. Level set segmentation of bovine corpora lutea in ex situ ovarian ultrasound images

    Directory of Open Access Journals (Sweden)

    Adams Gregg P

    2008-08-01

    Full Text Available Abstract Background The objective of this study was to investigate the viability of level set image segmentation methods for the detection of corpora lutea (corpus luteum, CL boundaries in ultrasonographic ovarian images. It was hypothesized that bovine CL boundaries could be located within 1–2 mm by a level set image segmentation methodology. Methods Level set methods embed a 2D contour in a 3D surface and evolve that surface over time according to an image-dependent speed function. A speed function suitable for segmentation of CL's in ovarian ultrasound images was developed. An initial contour was manually placed and contour evolution was allowed to proceed until the rate of change of the area was sufficiently small. The method was tested on ovarian ultrasonographic images (n = 8 obtained ex situ. A expert in ovarian ultrasound interpretation delineated CL boundaries manually to serve as a "ground truth". Accuracy of the level set segmentation algorithm was determined by comparing semi-automatically determined contours with ground truth contours using the mean absolute difference (MAD, root mean squared difference (RMSD, Hausdorff distance (HD, sensitivity, and specificity metrics. Results and discussion The mean MAD was 0.87 mm (sigma = 0.36 mm, RMSD was 1.1 mm (sigma = 0.47 mm, and HD was 3.4 mm (sigma = 2.0 mm indicating that, on average, boundaries were accurate within 1–2 mm, however, deviations in excess of 3 mm from the ground truth were observed indicating under- or over-expansion of the contour. Mean sensitivity and specificity were 0.814 (sigma = 0.171 and 0.990 (sigma = 0.00786, respectively, indicating that CLs were consistently undersegmented but rarely did the contour interior include pixels that were judged by the human expert not to be part of the CL. It was observed that in localities where gradient magnitudes within the CL were strong due to high contrast speckle, contour expansion stopped too early. Conclusion The

  7. Level Set Segmentation of Medical Images Based on Local Region Statistics and Maximum a Posteriori Probability

    Directory of Open Access Journals (Sweden)

    Wenchao Cui

    2013-01-01

    Full Text Available This paper presents a variational level set method for simultaneous segmentation and bias field estimation of medical images with intensity inhomogeneity. In our model, the statistics of image intensities belonging to each different tissue in local regions are characterized by Gaussian distributions with different means and variances. According to maximum a posteriori probability (MAP and Bayes’ rule, we first derive a local objective function for image intensities in a neighborhood around each pixel. Then this local objective function is integrated with respect to the neighborhood center over the entire image domain to give a global criterion. In level set framework, this global criterion defines an energy in terms of the level set functions that represent a partition of the image domain and a bias field that accounts for the intensity inhomogeneity of the image. Therefore, image segmentation and bias field estimation are simultaneously achieved via a level set evolution process. Experimental results for synthetic and real images show desirable performances of our method.

  8. Method: automatic segmentation of mitochondria utilizing patch classification, contour pair classification, and automatically seeded level sets.

    Science.gov (United States)

    Giuly, Richard J; Martone, Maryann E; Ellisman, Mark H

    2012-02-09

    While progress has been made to develop automatic segmentation techniques for mitochondria, there remains a need for more accurate and robust techniques to delineate mitochondria in serial blockface scanning electron microscopic data. Previously developed texture based methods are limited for solving this problem because texture alone is often not sufficient to identify mitochondria. This paper presents a new three-step method, the Cytoseg process, for automated segmentation of mitochondria contained in 3D electron microscopic volumes generated through serial block face scanning electron microscopic imaging. The method consists of three steps. The first is a random forest patch classification step operating directly on 2D image patches. The second step consists of contour-pair classification. At the final step, we introduce a method to automatically seed a level set operation with output from previous steps. We report accuracy of the Cytoseg process on three types of tissue and compare it to a previous method based on Radon-Like Features. At step 1, we show that the patch classifier identifies mitochondria texture but creates many false positive pixels. At step 2, our contour processing step produces contours and then filters them with a second classification step, helping to improve overall accuracy. We show that our final level set operation, which is automatically seeded with output from previous steps, helps to smooth the results. Overall, our results show that use of contour pair classification and level set operations improve segmentation accuracy beyond patch classification alone. We show that the Cytoseg process performs well compared to another modern technique based on Radon-Like Features. We demonstrated that texture based methods for mitochondria segmentation can be enhanced with multiple steps that form an image processing pipeline. While we used a random-forest based patch classifier to recognize texture, it would be possible to replace this with

  9. Method: automatic segmentation of mitochondria utilizing patch classification, contour pair classification, and automatically seeded level sets

    Directory of Open Access Journals (Sweden)

    Giuly Richard J

    2012-02-01

    Full Text Available Abstract Background While progress has been made to develop automatic segmentation techniques for mitochondria, there remains a need for more accurate and robust techniques to delineate mitochondria in serial blockface scanning electron microscopic data. Previously developed texture based methods are limited for solving this problem because texture alone is often not sufficient to identify mitochondria. This paper presents a new three-step method, the Cytoseg process, for automated segmentation of mitochondria contained in 3D electron microscopic volumes generated through serial block face scanning electron microscopic imaging. The method consists of three steps. The first is a random forest patch classification step operating directly on 2D image patches. The second step consists of contour-pair classification. At the final step, we introduce a method to automatically seed a level set operation with output from previous steps. Results We report accuracy of the Cytoseg process on three types of tissue and compare it to a previous method based on Radon-Like Features. At step 1, we show that the patch classifier identifies mitochondria texture but creates many false positive pixels. At step 2, our contour processing step produces contours and then filters them with a second classification step, helping to improve overall accuracy. We show that our final level set operation, which is automatically seeded with output from previous steps, helps to smooth the results. Overall, our results show that use of contour pair classification and level set operations improve segmentation accuracy beyond patch classification alone. We show that the Cytoseg process performs well compared to another modern technique based on Radon-Like Features. Conclusions We demonstrated that texture based methods for mitochondria segmentation can be enhanced with multiple steps that form an image processing pipeline. While we used a random-forest based patch classifier to

  10. Toward accurate tooth segmentation from computed tomography images using a hybrid level set model

    Energy Technology Data Exchange (ETDEWEB)

    Gan, Yangzhou; Zhao, Qunfei [Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240 (China); Xia, Zeyang, E-mail: zy.xia@siat.ac.cn, E-mail: jing.xiong@siat.ac.cn; Hu, Ying [Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, and The Chinese University of Hong Kong, Shenzhen 518055 (China); Xiong, Jing, E-mail: zy.xia@siat.ac.cn, E-mail: jing.xiong@siat.ac.cn [Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 510855 (China); Zhang, Jianwei [TAMS, Department of Informatics, University of Hamburg, Hamburg 22527 (Germany)

    2015-01-15

    Purpose: A three-dimensional (3D) model of the teeth provides important information for orthodontic diagnosis and treatment planning. Tooth segmentation is an essential step in generating the 3D digital model from computed tomography (CT) images. The aim of this study is to develop an accurate and efficient tooth segmentation method from CT images. Methods: The 3D dental CT volumetric images are segmented slice by slice in a two-dimensional (2D) transverse plane. The 2D segmentation is composed of a manual initialization step and an automatic slice by slice segmentation step. In the manual initialization step, the user manually picks a starting slice and selects a seed point for each tooth in this slice. In the automatic slice segmentation step, a developed hybrid level set model is applied to segment tooth contours from each slice. Tooth contour propagation strategy is employed to initialize the level set function automatically. Cone beam CT (CBCT) images of two subjects were used to tune the parameters. Images of 16 additional subjects were used to validate the performance of the method. Volume overlap metrics and surface distance metrics were adopted to assess the segmentation accuracy quantitatively. The volume overlap metrics were volume difference (VD, mm{sup 3}) and Dice similarity coefficient (DSC, %). The surface distance metrics were average symmetric surface distance (ASSD, mm), RMS (root mean square) symmetric surface distance (RMSSSD, mm), and maximum symmetric surface distance (MSSD, mm). Computation time was recorded to assess the efficiency. The performance of the proposed method has been compared with two state-of-the-art methods. Results: For the tested CBCT images, the VD, DSC, ASSD, RMSSSD, and MSSD for the incisor were 38.16 ± 12.94 mm{sup 3}, 88.82 ± 2.14%, 0.29 ± 0.03 mm, 0.32 ± 0.08 mm, and 1.25 ± 0.58 mm, respectively; the VD, DSC, ASSD, RMSSSD, and MSSD for the canine were 49.12 ± 9.33 mm{sup 3}, 91.57 ± 0.82%, 0.27 ± 0.02 mm, 0

  11. Image registration via level-set motion: applications to atlas-based segmentation.

    Science.gov (United States)

    Vemuri, B C; Ye, J; Chen, Y; Leonard, C M

    2003-03-01

    Image registration is an often encountered problem in various fields including medical imaging, computer vision and image processing. Numerous algorithms for registering image data have been reported in these areas. In this paper, we present a novel curve evolution approach expressed in a level-set framework to achieve image intensity morphing and a simple non-linear PDE for the corresponding coordinate registration. The key features of the intensity morphing model are that (a) it is very fast and (b) existence and uniqueness of the solution for the evolution model are established in a Sobolev space as opposed to using viscosity methods. The salient features of the coordinate registration model are its simplicity and computational efficiency. The intensity morph is easily achieved via evolving level-sets of one image into the level-sets of the other. To explicitly estimate the coordinate transformation between the images, we derive a non-linear PDE-based motion model which can be solved very efficiently. We demonstrate the performance of our algorithm on a variety of images including synthetic and real data. As an application of the PDE-based motion model, atlas based segmentation of hippocampal shape from several MR brain scans is depicted. In each of these experiments, automated hippocampal shape recovery results are validated via manual "expert" segmentations.

  12. Variational Level Set Method for Two-Stage Image Segmentation Based on Morphological Gradients

    Directory of Open Access Journals (Sweden)

    Zemin Ren

    2014-01-01

    Full Text Available We use variational level set method and transition region extraction techniques to achieve image segmentation task. The proposed scheme is done by two steps. We first develop a novel algorithm to extract transition region based on the morphological gradient. After this, we integrate the transition region into a variational level set framework and develop a novel geometric active contour model, which include an external energy based on transition region and fractional order edge indicator function. The external energy is used to drive the zero level set toward the desired image features, such as object boundaries. Due to this external energy, the proposed model allows for more flexible initialization. The fractional order edge indicator function is incorporated into the length regularization term to diminish the influence of noise. Moreover, internal energy is added into the proposed model to penalize the deviation of the level set function from a signed distance function. The results evolution of the level set function is the gradient flow that minimizes the overall energy functional. The proposed model has been applied to both synthetic and real images with promising results.

  13. Texture analysis improves level set segmentation of the anterior abdominal wall

    Energy Technology Data Exchange (ETDEWEB)

    Xu, Zhoubing [Electrical Engineering, Vanderbilt University, Nashville, Tennessee 37235 (United States); Allen, Wade M. [Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee 37235 (United States); Baucom, Rebeccah B.; Poulose, Benjamin K. [General Surgery, Vanderbilt University Medical Center, Nashville, Tennessee 37235 (United States); Landman, Bennett A. [Electrical Engineering, Vanderbilt University, Nashville, Tennessee 37235 and Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee 37235 (United States)

    2013-12-15

    Purpose: The treatment of ventral hernias (VH) has been a challenging problem for medical care. Repair of these hernias is fraught with failure; recurrence rates ranging from 24% to 43% have been reported, even with the use of biocompatible mesh. Currently, computed tomography (CT) is used to guide intervention through expert, but qualitative, clinical judgments, notably, quantitative metrics based on image-processing are not used. The authors propose that image segmentation methods to capture the three-dimensional structure of the abdominal wall and its abnormalities will provide a foundation on which to measure geometric properties of hernias and surrounding tissues and, therefore, to optimize intervention.Methods: In this study with 20 clinically acquired CT scans on postoperative patients, the authors demonstrated a novel approach to geometric classification of the abdominal. The authors’ approach uses a texture analysis based on Gabor filters to extract feature vectors and follows a fuzzy c-means clustering method to estimate voxelwise probability memberships for eight clusters. The memberships estimated from the texture analysis are helpful to identify anatomical structures with inhomogeneous intensities. The membership was used to guide the level set evolution, as well as to derive an initial start close to the abdominal wall.Results: Segmentation results on abdominal walls were both quantitatively and qualitatively validated with surface errors based on manually labeled ground truth. Using texture, mean surface errors for the outer surface of the abdominal wall were less than 2 mm, with 91% of the outer surface less than 5 mm away from the manual tracings; errors were significantly greater (2–5 mm) for methods that did not use the texture.Conclusions: The authors’ approach establishes a baseline for characterizing the abdominal wall for improving VH care. Inherent texture patterns in CT scans are helpful to the tissue classification, and texture

  14. Vascular Tree Segmentation in Medical Images Using Hessian-Based Multiscale Filtering and Level Set Method

    Directory of Open Access Journals (Sweden)

    Jiaoying Jin

    2013-01-01

    extraction of vascular trees from 2D medical images is presented, which combines Hessian-based multiscale filtering and a modified level set method. In the proposed algorithm, the morphological top-hat transformation is firstly adopted to attenuate background. Then Hessian-based multiscale filtering is used to enhance vascular structures by combining Hessian matrix with Gaussian convolution to tune the filtering response to the specific scales. Because Gaussian convolution tends to blur vessel boundaries, which makes scale selection inaccurate, an improved level set method is finally proposed to extract vascular structures by introducing an external constrained term related to the standard deviation of Gaussian function into the traditional level set. Our approach was tested on synthetic images with vascular-like structures and 2D slices extracted from real 3D abdomen magnetic resonance angiography (MRA images along the coronal plane. The segmentation rates for synthetic images are above 95%. The results for MRA images demonstrate that the proposed method can extract most of the vascular structures successfully and accurately in visualization. Therefore, the proposed method is effective for the vascular tree extraction in medical images.

  15. Architecture-Driven Level Set Optimization: From Clustering to Subpixel Image Segmentation.

    Science.gov (United States)

    Balla-Arabe, Souleymane; Gao, Xinbo; Ginhac, Dominique; Brost, Vincent; Yang, Fan

    2016-12-01

    Thanks to their effectiveness, active contour models (ACMs) are of great interest for computer vision scientists. The level set methods (LSMs) refer to the class of geometric active contours. Comparing with the other ACMs, in addition to subpixel accuracy, it has the intrinsic ability to automatically handle topological changes. Nevertheless, the LSMs are computationally expensive. A solution for their time consumption problem can be hardware acceleration using some massively parallel devices such as graphics processing units (GPUs). But the question is: which accuracy can we reach while still maintaining an adequate algorithm to massively parallel architecture? In this paper, we attempt to push back the compromise between, speed and accuracy, efficiency and effectiveness, to a higher level, comparing with state-of-the-art methods. To this end, we designed a novel architecture-aware hybrid central processing unit (CPU)-GPU LSM for image segmentation. The initialization step, using the well-known k -means algorithm, is fast although executed on a CPU, while the evolution equation of the active contour is inherently local and therefore suitable for GPU-based acceleration. The incorporation of local statistics in the level set evolution allowed our model to detect new boundaries which are not extracted by the used clustering algorithm. Comparing with some cutting-edge LSMs, the introduced model is faster, more accurate, less subject to giving local minima, and therefore suitable for automatic systems. Furthermore, it allows two-phase clustering algorithms to benefit from the numerous LSM advantages such as the ability to achieve robust and subpixel accurate segmentation results with smooth and closed contours. Intensive experiments demonstrate, objectively and subjectively, the good performance of the introduced framework both in terms of speed and accuracy.

  16. Coupled Segmentation of Nuclear and Membrane-bound Macromolecules through Voting and Multiphase Level Set.

    Science.gov (United States)

    Chang, Hang; Wen, Quan; Parvin, Bahram

    2015-03-01

    Membrane-bound macromolecules play an important role in tissue architecture and cell-cell communication, and is regulated by almost one-third of the genome. At the optical scale, one group of membrane proteins expresses themselves as linear structures along the cell surface boundaries, while others are sequestered; and this paper targets the former group. Segmentation of these membrane proteins on a cell-by-cell basis enables the quantitative assessment of localization for comparative analysis. However, such membrane proteins typically lack continuity, and their intensity distributions are often very heterogeneous; moreover, nuclei can form large clump, which further impedes the quantification of membrane signals on a cell-by-cell basis. To tackle these problems, we introduce a three-step process to (i) regularize the membrane signal through iterative tangential voting, (ii) constrain the location of surface proteins by nuclear features, where clumps of nuclei are segmented through a delaunay triangulation approach, and (iii) assign membrane-bound macromolecules to individual cells through an application of multi-phase geodesic level-set. We have validated our method using both synthetic data and a dataset of 200 images, and are able to demonstrate the efficacy of our approach with superior performance.

  17. GPU-BASED IMAGE SEGMENTATION USING LEVEL SET METHOD WITH SCALING APPROACH

    Directory of Open Access Journals (Sweden)

    Zafer Guler

    2013-11-01

    Full Text Available In recent years, with the development of graphics processors, graphics cards have been widely used to perform general-purpose calculations. Especially with release of CUDA C programming languages in 2007, most of the researchers have been used CUDA C programming language for the processes which needs high performance computing. In this paper, a scaling approach for image segmentation using level sets is carried out by the GPU programming techniques. Approach to level sets is mainly based on the solution of partial differential equations. The proposed method does not require the solution of partial differential equation. Scaling approach, which uses basic geometric transformations, is used. Thus, the required computational cost reduces. The use of the CUDA programming on the GPU has taken advantage of classic programming as spending time and performance. Thereby results are obtained faster. The use of the GPU has provided to enable real-time processing. The developed application in this study is used to find tumor on MRI brain images.

  18. [Layer-dependent multi-constrained algorithms based on improved level set for segmentation of teeth MRI-UTE image].

    Science.gov (United States)

    Zheng, Caixian; Xu, Xiu; Wang, Cheng; Ye, Xiuxia

    2013-07-01

    To introduce algorithms for effective segmentation of teeth MRI-UTE image. To construct second-segmentation algorithm process based on layer-dependent multi-constrained method. Firstly, a level set method was used to segment the initial boundary from the region determined by user in the reference slice. Secondly, both crown and root of the tooth were segmented by the improved level set method which took the information of the former layer's result as constraint conditions. Finally, the improved level set based on the information of the former and later layer's results was executed for the second time to improve the accuracy of segmentation, in which, the parameter of the overlapping ratio was considered. The accuracy was 86.98% for the first-segmentation and was increased to 88.35% for the second-segmentation. Compared to the two other methods, the accuracy of the algorithms provided was improved significantly (P algorithms can effectively achieve the segmentation of teeth MRI-UTE image and has a great improvement on accuracy.

  19. Integrating Compact Constraint and Distance Regularization with Level Set for Hepatocellular Carcinoma (HCC) Segmentation on Computed Tomography (CT) Images

    Science.gov (United States)

    Gui, Luying; He, Jian; Qiu, Yudong; Yang, Xiaoping

    2017-01-01

    This paper presents a variational level set approach to segment lesions with compact shapes on medical images. In this study, we investigate to address the problem of segmentation for hepatocellular carcinoma which are usually of various shapes, variable intensities, and weak boundaries. An efficient constraint which is called the isoperimetric constraint to describe the compactness of shapes is applied in this method. In addition, in order to ensure the precise segmentation and stable movement of the level set, a distance regularization is also implemented in the proposed variational framework. Our method is applied to segment various hepatocellular carcinoma regions on Computed Tomography images with promising results. Comparison results also prove that the proposed method is more accurate than other two approaches.

  20. Robust Anisotropic Diffusion Based Edge Enhancement for Level Set Segmentation and Asymmetry Analysis of Breast Thermograms using Zernike Moments.

    Science.gov (United States)

    Prabha, S; Sujatha, C M; Ramakrishnan, S

    2015-01-01

    Breast thermography plays a major role in early detection of breast cancer in which the thermal variations are associated with precancerous state of breast. The distribution of asymmetrical thermal patterns indicates the pathological condition in breast thermal images. In this work, asymmetry analysis of breast thermal images is carried out using level set segmentation and Zernike moments. The breast tissues are subjected to Tukey’s biweight robust anisotropic diffusion filtering (TBRAD) for the generation of edge map. Reaction diffusion level set method is employed for segmentation in which TBRAD edge map is used as stopping criterion during the level set evolution. Zernike moments are extracted from the segmented breast tissues to perform asymmetry analysis. Results show that the TBRAD filter is able to enhance the edges near infra mammary folds and lower breast boundaries effectively. It is observed that segmented breast tissues are found to be continuous and has sharper boundary. This method yields high degree of correlation (98%) between the segmented output and the ground truth images. Among the extracted Zernike features, higher order moments are found to be significant in demarcating normal and carcinoma breast tissues by 9%. It appears that, the methodology adopted here is useful in accurate segmentation and differentiation of normal and carcinoma breast tissues for automated diagnosis of breast abnormalities.

  1. An automatic method for fast and accurate liver segmentation in CT images using a shape detection level set method

    Science.gov (United States)

    Lee, Jeongjin; Kim, Namkug; Lee, Ho; Seo, Joon Beom; Won, Hyung Jin; Shin, Yong Moon; Shin, Yeong Gil

    2007-03-01

    Automatic liver segmentation is still a challenging task due to the ambiguity of liver boundary and the complex context of nearby organs. In this paper, we propose a faster and more accurate way of liver segmentation in CT images with an enhanced level set method. The speed image for level-set propagation is smoothly generated by increasing number of iterations in anisotropic diffusion filtering. This prevents the level-set propagation from stopping in front of local minima, which prevails in liver CT images due to irregular intensity distributions of the interior liver region. The curvature term of shape modeling level-set method captures well the shape variations of the liver along the slice. Finally, rolling ball algorithm is applied for including enhanced vessels near the liver boundary. Our approach are tested and compared to manual segmentation results of eight CT scans with 5mm slice distance using the average distance and volume error. The average distance error between corresponding liver boundaries is 1.58 mm and the average volume error is 2.2%. The average processing time for the segmentation of each slice is 5.2 seconds, which is much faster than the conventional ones. Accurate and fast result of our method will expedite the next stage of liver volume quantification for liver transplantations.

  2. A level set method for image segmentation in the presence of intensity inhomogeneities with application to MRI.

    Science.gov (United States)

    Li, Chunming; Huang, Rui; Ding, Zhaohua; Gatenby, J Chris; Metaxas, Dimitris N; Gore, John C

    2011-07-01

    Intensity inhomogeneity often occurs in real-world images, which presents a considerable challenge in image segmentation. The most widely used image segmentation algorithms are region-based and typically rely on the homogeneity of the image intensities in the regions of interest, which often fail to provide accurate segmentation results due to the intensity inhomogeneity. This paper proposes a novel region-based method for image segmentation, which is able to deal with intensity inhomogeneities in the segmentation. First, based on the model of images with intensity inhomogeneities, we derive a local intensity clustering property of the image intensities, and define a local clustering criterion function for the image intensities in a neighborhood of each point. This local clustering criterion function is then integrated with respect to the neighborhood center to give a global criterion of image segmentation. In a level set formulation, this criterion defines an energy in terms of the level set functions that represent a partition of the image domain and a bias field that accounts for the intensity inhomogeneity of the image. Therefore, by minimizing this energy, our method is able to simultaneously segment the image and estimate the bias field, and the estimated bias field can be used for intensity inhomogeneity correction (or bias correction). Our method has been validated on synthetic images and real images of various modalities, with desirable performance in the presence of intensity inhomogeneities. Experiments show that our method is more robust to initialization, faster and more accurate than the well-known piecewise smooth model. As an application, our method has been used for segmentation and bias correction of magnetic resonance (MR) images with promising results.

  3. A hybrid method based on fuzzy clustering and local region-based level set for segmentation of inhomogeneous medical images.

    Science.gov (United States)

    Rastgarpour, Maryam; Shanbehzadeh, Jamshid; Soltanian-Zadeh, Hamid

    2014-08-01

    medical images are more affected by intensity inhomogeneity rather than noise and outliers. This has a great impact on the efficiency of region-based image segmentation methods, because they rely on homogeneity of intensities in the regions of interest. Meanwhile, initialization and configuration of controlling parameters affect the performance of level set segmentation. To address these problems, this paper proposes a new hybrid method that integrates a local region-based level set method with a variation of fuzzy clustering. Specifically it takes an information fusion approach based on a coarse-to-fine framework that seamlessly fuses local spatial information and gray level information with the information of the local region-based level set method. Also, the controlling parameters of level set are directly computed from fuzzy clustering result. This approach has valuable benefits such as automation, no need to prior knowledge about the region of interest (ROI), robustness on intensity inhomogeneity, automatic adjustment of controlling parameters, insensitivity to initialization, and satisfactory accuracy. So, the contribution of this paper is to provide these advantages together which have not been proposed yet for inhomogeneous medical images. Proposed method was tested on several medical images from different modalities for performance evaluation. Experimental results approve its effectiveness in segmenting medical images in comparison with similar methods.

  4. 3D Segmentation with an application of level set-method using MRI volumes for image guided surgery.

    Science.gov (United States)

    Bosnjak, A; Montilla, G; Villegas, R; Jara, I

    2007-01-01

    This paper proposes an innovation in the application for image guided surgery using a comparative study of three different method of segmentation. This segmentation method is faster than the manual segmentation of images, with the advantage that it allows to use the same patient as anatomical reference, which has more precision than a generic atlas. This new methodology for 3D information extraction is based on a processing chain structured of the following modules: 1) 3D Filtering: the purpose is to preserve the contours of the structures and to smooth the homogeneous areas; several filters were tested and finally an anisotropic diffusion filter was used. 2) 3D Segmentation. This module compares three different methods: Region growing Algorithm, Cubic spline hand assisted, and Level Set Method. It then proposes a Level Set-based on the front propagation method that allows the making of the reconstruction of the internal walls of the anatomical structures of the brain. 3) 3D visualization. The new contribution of this work consists on the visualization of the segmented model and its use in the pre-surgery planning.

  5. Analysis and Implementation of Kidney Stone Detection by Reaction Diffusion Level Set Segmentation Using Xilinx System Generator on FPGA

    Directory of Open Access Journals (Sweden)

    Kalannagari Viswanath

    2015-01-01

    Full Text Available Ultrasound imaging is one of the available imaging techniques used for diagnosis of kidney abnormalities, which may be like change in shape and position and swelling of limb; there are also other Kidney abnormalities such as formation of stones, cysts, blockage of urine, congenital anomalies, and cancerous cells. During surgical processes it is vital to recognize the true and precise location of kidney stone. The detection of kidney stones using ultrasound imaging is a highly challenging task as they are of low contrast and contain speckle noise. This challenge is overcome by employing suitable image processing techniques. The ultrasound image is first preprocessed to get rid of speckle noise using the image restoration process. The restored image is smoothened using Gabor filter and the subsequent image is enhanced by histogram equalization. The preprocessed image is achieved with level set segmentation to detect the stone region. Segmentation process is employed twice for getting better results; first to segment kidney portion and then to segment the stone portion, respectively. In this work, the level set segmentation uses two terms, namely, momentum and resilient propagation (Rprop to detect the stone portion. After segmentation, the extracted region of the kidney stone is given to Symlets, Biorthogonal (bio3.7, bio3.9, and bio4.4, and Daubechies lifting scheme wavelet subbands to extract energy levels. These energy levels provide evidence about presence of stone, by comparing them with that of the normal energy levels. They are trained by multilayer perceptron (MLP and back propagation (BP ANN to classify and its type of stone with an accuracy of 98.8%. The prosed work is designed and real time is implemented on both Filed Programmable Gate Array Vertex-2Pro FPGA using Xilinx System Generator (XSG Verilog and Matlab 2012a.

  6. A new Level-set based Protocol for Accurate Bone Segmentation from CT Imaging

    CERN Document Server

    Pinheiro, Manuel

    2015-01-01

    In this work it is proposed a medical image segmentation pipeline for accurate bone segmentation from CT imaging. It is a two-step methodology, with a pre-segmentation step and a segmentation refinement step. First, the user performs a rough segmenting of the desired region of interest. Next, a fully automatic refinement step is applied to the pre-segmented data. The automatic segmentation refinement is composed by several sub-stpng, namely image deconvolution, image cropping and interpolation. The user-defined pre-segmentation is then refined over the deconvolved, cropped, and up-sampled version of the image. The algorithm is applied in the segmentation of CT images of a composite femur bone, reconstructed with different reconstruction protocols. Segmentation outcomes are validated against a gold standard model obtained with coordinate measuring machine Nikon Metris LK V20 with a digital line scanner LC60-D that guarantees an accuracy of 28 $\\mu m$. High sub-pixel accuracy models were obtained for all tested...

  7. Joint Target Tracking, Recognition and Segmentation for Infrared Imagery Using a Shape Manifold-Based Level Set

    Directory of Open Access Journals (Sweden)

    Jiulu Gong

    2014-06-01

    Full Text Available We propose a new integrated target tracking, recognition and segmentation algorithm, called ATR-Seg, for infrared imagery. ATR-Seg is formulated in a probabilistic shape-aware level set framework that incorporates a joint view-identity manifold (JVIM for target shape modeling. As a shape generative model, JVIM features a unified manifold structure in the latent space that is embedded with one view-independent identity manifold and infinite identity-dependent view manifolds. In the ATR-Seg algorithm, the ATR problem formulated as a sequential level-set optimization process over the latent space of JVIM, so that tracking and recognition can be jointly optimized via implicit shape matching where target segmentation is achieved as a by-product without any pre-processing or feature extraction. Experimental results on the recently released SENSIAC ATR database demonstrate the advantages and effectiveness of ATR-Seg over two recent ATR algorithms that involve explicit shape matching.

  8. Segmentation and Analysis of Corpus Callosum in Alzheimer MR Images using Total Variation Based Diffusion Filter and Level Set Method.

    Science.gov (United States)

    Anandh, K R; Sujatha, C M; Ramakrishnan, S

    2015-01-01

    Alzheimer’s Disease (AD) is a common form of dementia that affects gray and white matter structures of brain. Manifestation of AD leads to cognitive deficits such as memory impairment problems, ability to think and difficulties in performing day to day activities. Although the etiology of this disease is unclear, imaging biomarkers are highly useful in the early diagnosis of AD. Magnetic resonance imaging is an indispensible non-invasive imaging modality that reflects both the geometry and pathology of the brain. Corpus Callosum (CC) is the largest white matter structure as well as the main inter-hemispheric fiber connection that undergoes regional alterations due to AD. Therefore, segmentation and feature extraction are predominantly essential to characterize the CC atrophy. In this work, an attempt has been made to segment CC using edge based level set method. Prior to segmentation, the images are pre-processed using Total Variation (TV) based diffusion filtering to enhance the edge information. Shape based geometric features are extracted from the segmented CC images to analyze the CC atrophy. Results show that the edge based level set method is able to segment CC in both the normal and AD images. TV based diffusion filtering has performed uniform region specific smoothing thereby preserving the texture and small scale details of the image. Consequently, the edge map of CC in both the normal and AD are apparently sharp and distinct with continuous boundaries. This facilitates the final contour to correctly segment CC from the nearby structures. The extracted geometric features such as area, perimeter and minor axis are found to have the percentage difference of 5.97%, 22.22% and 9.52% respectively in the demarcation of AD subjects. As callosal atrophy is significant in the diagnosis of AD, this study seems to be clinically useful.

  9. Whole abdominal wall segmentation using augmented active shape models (AASM) with multi-atlas label fusion and level set

    Science.gov (United States)

    Xu, Zhoubing; Baucom, Rebeccah B.; Abramson, Richard G.; Poulose, Benjamin K.; Landman, Bennett A.

    2016-03-01

    The abdominal wall is an important structure differentiating subcutaneous and visceral compartments and intimately involved with maintaining abdominal structure. Segmentation of the whole abdominal wall on routinely acquired computed tomography (CT) scans remains challenging due to variations and complexities of the wall and surrounding tissues. In this study, we propose a slice-wise augmented active shape model (AASM) approach to robustly segment both the outer and inner surfaces of the abdominal wall. Multi-atlas label fusion (MALF) and level set (LS) techniques are integrated into the traditional ASM framework. The AASM approach globally optimizes the landmark updates in the presence of complicated underlying local anatomical contexts. The proposed approach was validated on 184 axial slices of 20 CT scans. The Hausdorff distance against the manual segmentation was significantly reduced using proposed approach compared to that using ASM, MALF, and LS individually. Our segmentation of the whole abdominal wall enables the subcutaneous and visceral fat measurement, with high correlation to the measurement derived from manual segmentation. This study presents the first generic algorithm that combines ASM, MALF, and LS, and demonstrates practical application for automatically capturing visceral and subcutaneous fat volumes.

  10. Loosely coupled level sets for retinal layers and drusen segmentation in subjects with dry age-related macular degeneration

    Science.gov (United States)

    Novosel, Jelena; Wang, Ziyuan; de Jong, Henk; Vermeer, Koenraad A.; van Vliet, Lucas J.

    2016-03-01

    Optical coherence tomography (OCT) is used to produce high-resolution three-dimensional images of the retina, which permit the investigation of retinal irregularities. In dry age-related macular degeneration (AMD), a chronic eye disease that causes central vision loss, disruptions such as drusen and changes in retinal layer thicknesses occur which could be used as biomarkers for disease monitoring and diagnosis. Due to the topology disrupting pathology, existing segmentation methods often fail. Here, we present a solution for the segmentation of retinal layers in dry AMD subjects by extending our previously presented loosely coupled level sets framework which operates on attenuation coefficients. In eyes affected by AMD, Bruch's membrane becomes visible only below the drusen and our segmentation framework is adapted to delineate such a partially discernible interface. Furthermore, the initialization stage, which tentatively segments five interfaces, is modified to accommodate the appearance of drusen. This stage is based on Dijkstra's algorithm and combines prior knowledge on the shape of the interface, gradient and attenuation coefficient in the newly proposed cost function. This prior knowledge is incorporated by varying the weights for horizontal, diagonal and vertical edges. Finally, quantitative evaluation of the accuracy shows a good agreement between manual and automated segmentation.

  11. CUDA Accelerated Multi-domain Volumetric Image Segmentation and Using a Higher Order Level Set Method

    DEFF Research Database (Denmark)

    Sharma, Ojaswa; Anton, François; Zhang, Qin;

    2009-01-01

    -manding in terms of computation and memory space, we employ a CUDA based fast GPU segmentation and provide accuracy measures compared with an equivalent CPU implementation. Our resulting surfaces are C2-smooth resulting from tri-cubic spline interpolation algorithm. We also provide error bounds...

  12. Novel multimodality segmentation using level sets and Jensen-Renyi divergence

    NARCIS (Netherlands)

    Markel, Daniel; Zaidi, Habib; El Naqa, Issam

    2013-01-01

    Purpose: Positron emission tomography (PET) is playing an increasing role in radiotherapy treatment planning. However, despite progress, robust algorithms for PET and multimodal image segmentation are still lacking, especially if the algorithm were extended to image-guided and adaptive radiotherapy

  13. Novel level-set based segmentation method of the lung at HRCT images of diffuse interstitial lung disease (DILD)

    Science.gov (United States)

    Lee, Jeongjin; Seo, Joon Beom; Kim, Namkug; Park, Sang Ok; Lee, Ho; Shin, Yeong Gil; Kim, Soo-Hong

    2009-02-01

    In this paper, we propose an algorithm for reliable segmentation of the lung at HRCT of DILD. Our method consists of four main steps. First, the airway and colon are segmented and excluded by thresholding(-974 HU) and connected component analysis. Second, initial lung is identified by thresholding(-474 HU). Third, shape propagation outward the lung is performed on the initial lung. Actual lung boundaries exist inside the propagated boundaries. Finally, subsequent shape modeling level-set inward the lung from the propagated boundary can identify the lung boundary when the curvature term was highly weighted. To assess the accuracy of the proposed algorithm, the segmentation results of 54 patients are compared with those of manual segmentation done by an expert radiologist. The value of 1 minus volumetric overlap is less than 5% error. Accurate result of our method would be useful in determining the lung parenchyma at HRCT, which is the essential step for the automatic classification and quantification of diffuse interstitial lung disease.

  14. Segmentation of prostate from ultrasound images using level sets on active band and intensity variation across edges.

    Science.gov (United States)

    Li, Xu; Li, Chunming; Fedorov, Andriy; Kapur, Tina; Yang, Xiaoping

    2016-06-01

    In this paper, the authors propose a novel efficient method to segment ultrasound images of the prostate with weak boundaries. Segmentation of the prostate from ultrasound images with weak boundaries widely exists in clinical applications. One of the most typical examples is the diagnosis and treatment of prostate cancer. Accurate segmentation of the prostate boundaries from ultrasound images plays an important role in many prostate-related applications such as the accurate placement of the biopsy needles, the assignment of the appropriate therapy in cancer treatment, and the measurement of the prostate volume. Ultrasound images of the prostate are usually corrupted with intensity inhomogeneities, weak boundaries, and unwanted edges, which make the segmentation of the prostate an inherently difficult task. Regarding to these difficulties, the authors introduce an active band term and an edge descriptor term in the modified level set energy functional. The active band term is to deal with intensity inhomogeneities and the edge descriptor term is to capture the weak boundaries or to rule out unwanted boundaries. The level set function of the proposed model is updated in a band region around the zero level set which the authors call it an active band. The active band restricts the authors' method to utilize the local image information in a banded region around the prostate contour. Compared to traditional level set methods, the average intensities inside∖outside the zero level set are only computed in this banded region. Thus, only pixels in the active band have influence on the evolution of the level set. For weak boundaries, they are hard to be distinguished by human eyes, but in local patches in the band region around prostate boundaries, they are easier to be detected. The authors incorporate an edge descriptor to calculate the total intensity variation in a local patch paralleled to the normal direction of the zero level set, which can detect weak boundaries

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

    Directory of Open Access Journals (Sweden)

    Nakissa Barzegar

    2009-01-01

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

  16. An efficient level set method for simultaneous intensity inhomogeneity correction and segmentation of MR images.

    Science.gov (United States)

    Ivanovska, Tatyana; Laqua, René; Wang, Lei; Schenk, Andrea; Yoon, Jeong Hee; Hegenscheid, Katrin; Völzke, Henry; Liebscher, Volkmar

    2016-03-01

    Intensity inhomogeneity (bias field) is a common artefact in magnetic resonance (MR) images, which hinders successful automatic segmentation. In this work, a novel algorithm for simultaneous segmentation and bias field correction is presented. The proposed energy functional allows for explicit regularization of the bias field term, making the model more flexible, which is crucial in presence of strong inhomogeneities. An efficient minimization procedure, attempting to find the global minimum, is applied to the energy functional. The algorithm is evaluated qualitatively and quantitatively using a synthetic example and real MR images of different organs. Comparisons with several state-of-the-art methods demonstrate the superior performance of the proposed technique. Desirable results are obtained even for images with strong and complicated inhomogeneity fields and sparse tissue structures. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. Weld Inspection Based on Radiography Image Segmentation with Level Set Active Contour Guided Off-Center Saliency Map

    Directory of Open Access Journals (Sweden)

    Mohamed Ben Gharsallah

    2015-01-01

    Full Text Available Radiography is one of the most used techniques in weld defect inspection. Weld defect detection becomes a complex task when uneven illumination and low contrast characterize radiographic images. In this paper we propose a new active contour based level set method for weld defect detection in radiography images. An off-center saliency map exploited as a feature to represent image pixels is embedded into a region energy minimization function to guide the level set active contour to defects boundaries. The aim behind using salient feature is that a small defect can frequently attract attention of human eyes which permits enhancing defects in low contrasted image. Experiment results on different weld radiographic images with various kinds of defects show robustness and good performance of the proposed approach comparing with other segmentation methods.

  18. Autonomous Motion Segmentation of Multiple Objects in Low Resolution Video Using Variational Level Sets

    Energy Technology Data Exchange (ETDEWEB)

    Moelich, M

    2003-11-18

    This report documents research that was done during a ten week internship in the Sapphire research group at the Lawrence Livermore National Laboratory during the Summer of 2003. The goal of the study was to develop an algorithm that is capable of isolating (segmenting) moving objects in low resolution video sequences. This capability is currently being developed by the Sapphire research group as the first stage in a longer term video data mining project. This report gives a chronological account of what ideas were tried in developing the algorithm and what was learned from each attempt. The final version of the algorithm, which is described in detail, gives good results and is fast.

  19. Curve/surface representation and evolution using vector level sets with application to the shape-based segmentation problem.

    Science.gov (United States)

    Abd El Munim, Hossam E; Farag, Aly A

    2007-06-01

    In this paper, we revisit the implicit front representation and evolution using the vector level set function (VLSF) proposed in [1]. Unlike conventional scalar level sets, this function is designed to have a vector form. The distance from any point to the nearest point on the front has components (projections) in the coordinate directions included in the vector function. This kind of representation is used to evolve closed planar curves and 3D surfaces as well. Maintaining the VLSF property as the distance projections through evolution will be considered together with a detailed derivation of the vector partial differential equation (PDE) for such evolution. A shape-based segmentation framework will be demonstrated as an application of the given implicit representation. The proposed level set function system will be used to represent shapes to give a dissimilarity measure in a variational object registration process. This kind of formulation permits us to better control the process of shape registration, which is an important part in the shape-based segmentation framework. The method depends on a set of training shapes used to build a parametric shape model. The color is taken into consideration besides the shape prior information. The shape model is fitted to the image volume by registration through an energy minimization problem. The approach overcomes the conventional methods problems like point correspondences and weighing coefficients tuning of the evolution (PDEs). It is also suitable for multidimensional data and computationally efficient. Results in 2D and 3D of real and synthetic data will demonstrate the efficiency of the framework.

  20. The Three-Dimensional Fast Segmentation Algorithm Based on Level Set Method%基于Level Set的交互式快速分割算法

    Institute of Scientific and Technical Information of China (English)

    孙海鹏; 余伟巍; 席平

    2011-01-01

    三维医学图像数据量大,并且受噪声、边界模糊等原因的影响,致使三维分割过程消耗时间较长,容易产生欠分割或过度分割.针对以上问题,提出一种基于LevelSet的三维快速分割算法,采用Fast Marching获取二维分割区域,优化轮廓边界,利用直线数值微分算法(Digital Differential Analyzer,DDA)提取轮廓像素;进一步引入扫描线种子填充思想,实现医学图像的三维快速分割.实验结果表明,上述算法能够快速准确地分割出感兴趣区域.%Because of the large volume of medical image data, the impact of noise, blurred boundaries and other reasons, the three-dimensional segmentation process is time-consuming, and easily produces less or over segmentation. To solve the above problems, this paper proposes a three-dimensional fast segmentation algorithm based on Level Set, using Level Set Fast Marching Method to obtain two-dimensional segmental region, optimizing the boundary contour, using the Digital Differential Analyzer method to extract contour pixels, finally introducing the idea of the Scan Line Seed-filling to achieve the three-dimensional fast segmentation. The actual clinical CT images of vertebral segmentation experiment result shows that this method can quickly and accurately separate out the interested area.

  1. A hybrid semi-automatic method for liver segmentation based on level-set methods using multiple seed points.

    Science.gov (United States)

    Yang, Xiaopeng; Yu, Hee Chul; Choi, Younggeun; Lee, Wonsup; Wang, Baojian; Yang, Jaedo; Hwang, Hongpil; Kim, Ji Hyun; Song, Jisoo; Cho, Baik Hwan; You, Heecheon

    2014-01-01

    The present study developed a hybrid semi-automatic method to extract the liver from abdominal computerized tomography (CT) images. The proposed hybrid method consists of a customized fast-marching level-set method for detection of an optimal initial liver region from multiple seed points selected by the user and a threshold-based level-set method for extraction of the actual liver region based on the initial liver region. The performance of the hybrid method was compared with those of the 2D region growing method implemented in OsiriX using abdominal CT datasets of 15 patients. The hybrid method showed a significantly higher accuracy in liver extraction (similarity index, SI=97.6 ± 0.5%; false positive error, FPE = 2.2 ± 0.7%; false negative error, FNE=2.5 ± 0.8%; average symmetric surface distance, ASD=1.4 ± 0.5mm) than the 2D (SI=94.0 ± 1.9%; FPE = 5.3 ± 1.1%; FNE=6.5 ± 3.7%; ASD=6.7 ± 3.8mm) region growing method. The total liver extraction time per CT dataset of the hybrid method (77 ± 10 s) is significantly less than the 2D region growing method (575 ± 136 s). The interaction time per CT dataset between the user and a computer of the hybrid method (28 ± 4 s) is significantly shorter than the 2D region growing method (484 ± 126 s). The proposed hybrid method was found preferred for liver segmentation in preoperative virtual liver surgery planning.

  2. Three-dimensional prostate segmentation using level set with shape constraint based on rotational slices for 3D end-firing TRUS guided biopsy.

    Science.gov (United States)

    Qiu, Wu; Yuan, Jing; Ukwatta, Eranga; Tessier, David; Fenster, Aaron

    2013-07-01

    Prostate segmentation is an important step in the planning and treatment of 3D end-firing transrectal ultrasound (TRUS) guided prostate biopsy. In order to improve the accuracy and efficiency of prostate segmentation in 3D TRUS images, an improved level set method is incorporated into a rotational-slice-based 3D prostate segmentation to decrease the accumulated segmentation errors produced by the slice-by-slice segmentation method. A 3D image is first resliced into 2D slices in a rotational manner in both the clockwise and counterclockwise directions. All slices intersect approximately along the rotational scanning axis and have an equal angular spacing. Six to eight boundary points are selected to initialize a level set function to extract the prostate contour within the first slice. The segmented contour is then propagated to the adjacent slice and is used as the initial contour for segmentation. This process is repeated until all slices are segmented. A modified distance regularization level set method is used to segment the prostate in all resliced 2D slices. In addition, shape-constraint and local-region-based energies are imposed to discourage the evolved level set function to leak in regions with weak edges or without edges. An anchor point based energy is used to promote the level set function to pass through the initial selected boundary points. The algorithm's performance was evaluated using distance- and volume-based metrics (sensitivity (Se), Dice similarity coefficient (DSC), mean absolute surface distance (MAD), maximum absolute surface distance (MAXD), and volume difference) by comparison with expert delineations. The validation results using thirty 3D patient images showed that the authors' method can obtain a DSC of 93.1% ± 1.6%, a sensitivity of 93.0% ± 2.0%, a MAD of 1.18 ± 0.36 mm, a MAXD of 3.44 ± 0.8 mm, and a volume difference of 2.6 ± 1.9 cm(3) for the entire prostate. A reproducibility experiment demonstrated that the proposed method

  3. A Computer-Aided Diagnosis System for Dynamic Contrast-Enhanced MR Images Based on Level Set Segmentation and ReliefF Feature Selection

    Directory of Open Access Journals (Sweden)

    Zhiyong Pang

    2015-01-01

    Full Text Available This study established a fully automated computer-aided diagnosis (CAD system for the classification of malignant and benign masses via breast magnetic resonance imaging (BMRI. A breast segmentation method consisting of a preprocessing step to identify the air-breast interfacing boundary and curve fitting for chest wall line (CWL segmentation was included in the proposed CAD system. The Chan-Vese (CV model level set (LS segmentation method was adopted to segment breast mass and demonstrated sufficiently good segmentation performance. The support vector machine (SVM classifier with ReliefF feature selection was used to merge the extracted morphological and texture features into a classification score. The accuracy, sensitivity, and specificity measurements for the leave-half-case-out resampling method were 92.3%, 98.2%, and 76.2%, respectively. For the leave-one-case-out resampling method, the measurements were 90.0%, 98.7%, and 73.8%, respectively.

  4. A New Kernel-Based Fuzzy Level Set Method for Automated Segmentation of Medical Images in the Presence of Intensity Inhomogeneity

    Directory of Open Access Journals (Sweden)

    Maryam Rastgarpour

    2014-01-01

    Full Text Available Researchers recently apply an integrative approach to automate medical image segmentation for benefiting available methods and eliminating their disadvantages. Intensity inhomogeneity is a challenging and open problem in this area, which has received less attention by this approach. It has considerable effects on segmentation accuracy. This paper proposes a new kernel-based fuzzy level set algorithm by an integrative approach to deal with this problem. It can directly evolve from the initial level set obtained by Gaussian Kernel-Based Fuzzy C-Means (GKFCM. The controlling parameters of level set evolution are also estimated from the results of GKFCM. Moreover the proposed algorithm is enhanced with locally regularized evolution based on an image model that describes the composition of real-world images, in which intensity inhomogeneity is assumed as a component of an image. Such improvements make level set manipulation easier and lead to more robust segmentation in intensity inhomogeneity. The proposed algorithm has valuable benefits including automation, invariant of intensity inhomogeneity, and high accuracy. Performance evaluation of the proposed algorithm was carried on medical images from different modalities. The results confirm its effectiveness for medical image segmentation.

  5. A new kernel-based fuzzy level set method for automated segmentation of medical images in the presence of intensity inhomogeneity.

    Science.gov (United States)

    Rastgarpour, Maryam; Shanbehzadeh, Jamshid

    2014-01-01

    Researchers recently apply an integrative approach to automate medical image segmentation for benefiting available methods and eliminating their disadvantages. Intensity inhomogeneity is a challenging and open problem in this area, which has received less attention by this approach. It has considerable effects on segmentation accuracy. This paper proposes a new kernel-based fuzzy level set algorithm by an integrative approach to deal with this problem. It can directly evolve from the initial level set obtained by Gaussian Kernel-Based Fuzzy C-Means (GKFCM). The controlling parameters of level set evolution are also estimated from the results of GKFCM. Moreover the proposed algorithm is enhanced with locally regularized evolution based on an image model that describes the composition of real-world images, in which intensity inhomogeneity is assumed as a component of an image. Such improvements make level set manipulation easier and lead to more robust segmentation in intensity inhomogeneity. The proposed algorithm has valuable benefits including automation, invariant of intensity inhomogeneity, and high accuracy. Performance evaluation of the proposed algorithm was carried on medical images from different modalities. The results confirm its effectiveness for medical image segmentation.

  6. Combining deep learning and level set for the automated segmentation of the left ventricle of the heart from cardiac cine magnetic resonance.

    Science.gov (United States)

    Ngo, Tuan Anh; Lu, Zhi; Carneiro, Gustavo

    2017-01-01

    We introduce a new methodology that combines deep learning and level set for the automated segmentation of the left ventricle of the heart from cardiac cine magnetic resonance (MR) data. This combination is relevant for segmentation problems, where the visual object of interest presents large shape and appearance variations, but the annotated training set is small, which is the case for various medical image analysis applications, including the one considered in this paper. In particular, level set methods are based on shape and appearance terms that use small training sets, but present limitations for modelling the visual object variations. Deep learning methods can model such variations using relatively small amounts of annotated training, but they often need to be regularised to produce good generalisation. Therefore, the combination of these methods brings together the advantages of both approaches, producing a methodology that needs small training sets and produces accurate segmentation results. We test our methodology on the MICCAI 2009 left ventricle segmentation challenge database (containing 15 sequences for training, 15 for validation and 15 for testing), where our approach achieves the most accurate results in the semi-automated problem and state-of-the-art results for the fully automated challenge. Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.

  7. Spatial gradients of protein-level time delays set the pace of the traveling segmentation clock waves.

    Science.gov (United States)

    Ay, Ahmet; Holland, Jack; Sperlea, Adriana; Devakanmalai, Gnanapackiam Sheela; Knierer, Stephan; Sangervasi, Sebastian; Stevenson, Angel; Ozbudak, Ertuğrul M

    2014-11-01

    The vertebrate segmentation clock is a gene expression oscillator controlling rhythmic segmentation of the vertebral column during embryonic development. The period of oscillations becomes longer as cells are displaced along the posterior to anterior axis, which results in traveling waves of clock gene expression sweeping in the unsegmented tissue. Although various hypotheses necessitating the inclusion of additional regulatory genes into the core clock network at different spatial locations have been proposed, the mechanism underlying traveling waves has remained elusive. Here, we combined molecular-level computational modeling and quantitative experimentation to solve this puzzle. Our model predicts the existence of an increasing gradient of gene expression time delays along the posterior to anterior direction to recapitulate spatiotemporal profiles of the traveling segmentation clock waves in different genetic backgrounds in zebrafish. We validated this prediction by measuring an increased time delay of oscillatory Her1 protein production along the unsegmented tissue. Our results refuted the need for spatial expansion of the core feedback loop to explain the occurrence of traveling waves. Spatial regulation of gene expression time delays is a novel way of creating dynamic patterns; this is the first report demonstrating such a control mechanism in any tissue and future investigations will explore the presence of analogous examples in other biological systems.

  8. Rotational-slice-Based prostate segmentation using level set with shape constraint for 3D end-firing TRUS guided biopsy.

    Science.gov (United States)

    Qiu, Wu; Yuan, Jing; Ukwatta, Eranga; Tessier, David; Fenster, Aaron

    2012-01-01

    Prostate segmentation in 3D ultrasound images is an important step in the planning and treatment of 3D end-firing transrectal ultrasound (TRUS) guided prostate biopsy. A semi-automatic prostate segmentation method is presented in this paper, which integrates a modified distance regularization level set formulation with shape constraint to a rotational-slice-based 3D prostate segmentation method. Its performance, using different metrics, has been evaluated on a set of twenty 3D patient prostate images by comparison with expert delineations. The volume overlap ratio of 93.39 +/- 1.26% and the mean absolute surface distance of 1.16 +/- 0.34 mm were found in the quantitative validation result.

  9. A level-set method for pathology segmentation in fluorescein angiograms and en face retinal images of patients with age-related macular degeneration

    Science.gov (United States)

    Mohammad, Fatimah; Ansari, Rashid; Shahidi, Mahnaz

    2013-03-01

    The visibility and continuity of the inner segment outer segment (ISOS) junction layer of the photoreceptors on spectral domain optical coherence tomography images is known to be related to visual acuity in patients with age-related macular degeneration (AMD). Automatic detection and segmentation of lesions and pathologies in retinal images is crucial for the screening, diagnosis, and follow-up of patients with retinal diseases. One of the challenges of using the classical level-set algorithms for segmentation involves the placement of the initial contour. Manually defining the contour or randomly placing it in the image may lead to segmentation of erroneous structures. It is important to be able to automatically define the contour by using information provided by image features. We explored a level-set method which is based on the classical Chan-Vese model and which utilizes image feature information for automatic contour placement for the segmentation of pathologies in fluorescein angiograms and en face retinal images of the ISOS layer. This was accomplished by exploiting a priori knowledge of the shape and intensity distribution allowing the use of projection profiles to detect the presence of pathologies that are characterized by intensity differences with surrounding areas in retinal images. We first tested our method by applying it to fluorescein angiograms. We then applied our method to en face retinal images of patients with AMD. The experimental results included demonstrate that the proposed method provided a quick and improved outcome as compared to the classical Chan-Vese method in which the initial contour is randomly placed, thus indicating the potential to provide a more accurate and detailed view of changes in pathologies due to disease progression and treatment.

  10. Anisotropic diffusion filter based edge enhancement for the segmentation of carotid intima-media layer in ultrasound images using variational level set method without re-initialisation.

    Science.gov (United States)

    Sumathi, K; Anandh, K R; Mahesh, V; Ramakrishnan, S

    2014-01-01

    In this work an attempt has been made to enhance the edges and segment the boundary of intima-media layer of Common Carotid Artery (CCA) using anisotropic diffusion filter and level set method. Ultrasound B mode longitudinal images of normal and abnormal images of common carotid arteries are used in this study. The images are subjected to anisotropic diffusion filter to generate edge map. This edge map is used as a stopping boundary in variational level set method without re-initialisation to segment the intima-media layer. Geometric features are extracted from this layer and analyzed statistically. Results show that anisotropic diffusion filtering is able to extract the edges in both normal and abnormal images. The obtained edge maps are found to have high contrast and sharp edges. The edge based variational level set method is able to segment the intima-media layer precisely from common carotid artery. The extracted geometrical features such as major axis and extent are found to be statistically significant in differentiating normal and abnormal images. Thus this study seems to be clinically useful in diagnosis of cardiovascular disease.

  11. Segmentation of Oil Spill Images Based on SFCM and Level Set Methods%基于SFCM及水平集方法的溢油图像分割

    Institute of Scientific and Technical Information of China (English)

    邵桢; 翟宏宇; 刘雪岩

    2013-01-01

      传统的单一模糊聚类算法(FCM)适用于无噪声图像的分割,而对于具有噪声、特殊点值及瑕疵的图像分割则无能为力。本文提出了应用嵌入空间信息的模糊聚类算法(SFCM)与水平集方法的结合,对海洋溢油污染的合成孔径雷达(SAR)图像进行分割处理,得到了优于其它算法的分割图像。通过对SAR溢油图像分割的数据分析,验证了算法的有效性。%In this paper a robust method for oil spill SAR image segmentation is explored. The unique FCM algorithm yields better results for segmenting noise free images, but it fails to segment images degraded by noise, outliers and other imaging defects,an integrated method of spatial based FCM (SFCM) and level set method for oil spill segmen-tation is discussed.By analysing segmentation of Oil spill SAR image,it verify the effectiveness of the algorithm.

  12. Improved Fuzzy C-Means based Particle Swarm Optimization (PSO) initialization and outlier rejection with level set methods for MR brain image segmentation.

    Science.gov (United States)

    Mekhmoukh, Abdenour; Mokrani, Karim

    2015-11-01

    In this paper, a new image segmentation method based on Particle Swarm Optimization (PSO) and outlier rejection combined with level set is proposed. A traditional approach to the segmentation of Magnetic Resonance (MR) images is the Fuzzy C-Means (FCM) clustering algorithm. The membership function of this conventional algorithm is sensitive to the outlier and does not integrate the spatial information in the image. The algorithm is very sensitive to noise and in-homogeneities in the image, moreover, it depends on cluster centers initialization. To improve the outlier rejection and to reduce the noise sensitivity of conventional FCM clustering algorithm, a novel extended FCM algorithm for image segmentation is presented. In general, in the FCM algorithm the initial cluster centers are chosen randomly, with the help of PSO algorithm the clusters centers are chosen optimally. Our algorithm takes also into consideration the spatial neighborhood information. These a priori are used in the cost function to be optimized. For MR images, the resulting fuzzy clustering is used to set the initial level set contour. The results confirm the effectiveness of the proposed algorithm.

  13. Continuation of Sets of Constrained Orbit Segments

    DEFF Research Database (Denmark)

    Schilder, Frank; Brøns, Morten; Chamoun, George Chaouki

    Sets of constrained orbit segments of time continuous flows are collections of trajectories that represent a whole or parts of an invariant set. A non-trivial but simple example is a homoclinic orbit. A typical representation of this set consists of an equilibrium point of the flow and a trajecto...... orbit segments, this is very disadvantageous in practice. In this talk we will present an algorithm that allows the efficient continuation of sets of constrained orbit segments together with the solution of the full variational problem.......Sets of constrained orbit segments of time continuous flows are collections of trajectories that represent a whole or parts of an invariant set. A non-trivial but simple example is a homoclinic orbit. A typical representation of this set consists of an equilibrium point of the flow and a trajectory...

  14. Shape-intensity prior level set combining probabilistic atlas and probability map constrains for automatic liver segmentation from abdominal CT images.

    Science.gov (United States)

    Wang, Jinke; Cheng, Yuanzhi; Guo, Changyong; Wang, Yadong; Tamura, Shinichi

    2016-05-01

    Propose a fully automatic 3D segmentation framework to segment liver on challenging cases that contain the low contrast of adjacent organs and the presence of pathologies from abdominal CT images. First, all of the atlases are weighted in the selected training datasets by calculating the similarities between the atlases and the test image to dynamically generate a subject-specific probabilistic atlas for the test image. The most likely liver region of the test image is further determined based on the generated atlas. A rough segmentation is obtained by a maximum a posteriori classification of probability map, and the final liver segmentation is produced by a shape-intensity prior level set in the most likely liver region. Our method is evaluated and demonstrated on 25 test CT datasets from our partner site, and its results are compared with two state-of-the-art liver segmentation methods. Moreover, our performance results on 10 MICCAI test datasets are submitted to the organizers for comparison with the other automatic algorithms. Using the 25 test CT datasets, average symmetric surface distance is [Formula: see text] mm (range 0.62-2.12 mm), root mean square symmetric surface distance error is [Formula: see text] mm (range 0.97-3.01 mm), and maximum symmetric surface distance error is [Formula: see text] mm (range 12.73-26.67 mm) by our method. Our method on 10 MICCAI test data sets ranks 10th in all the 47 automatic algorithms on the site as of July 2015. Quantitative results, as well as qualitative comparisons of segmentations, indicate that our method is a promising tool to improve the efficiency of both techniques. The applicability of the proposed method to some challenging clinical problems and the segmentation of the liver are demonstrated with good results on both quantitative and qualitative experimentations. This study suggests that the proposed framework can be good enough to replace the time-consuming and tedious slice-by-slice manual

  15. A new fuzzy level set method for SAR image segmentation%基于模糊水平集的SAR图像分割方法

    Institute of Scientific and Technical Information of China (English)

    毛万峰; 张红; 张波; 王超

    2013-01-01

    We present a new method which integrates fuzzy c-means cluttering and region-based level set evolution for SAR image segmentation. Benefited by spatial fuzzy clustering, the initial level set segmentation approximates the component of interest. The controlling parameters are also estimated on the basis of the results of the spatial fuzzy clustering. The proposed method was evaluated on synthetic and real SAR images, and the results show that the new method is more robust, fast, and accurate in segmentation and does not need manual intervention.%提出一种SAR图像分割方法,即整合了模糊C均值聚类和基于区域水平集演化的分割方法.该方法通过模糊聚类的结果计算水平集演化的初始化条件及控制参数,从而克服了水平集演化依赖于初始化条件和控制参数且需要较多人工干预的缺陷,增强了方法的鲁棒性.模拟图像及真实SAR图像的实验表明,该方法在不需要人工干预的情况下,能够快速、准确地分割出感兴趣区域.

  16. A fast and robust level set method for image segmentation using fuzzy clustering and lattice Boltzmann method.

    Science.gov (United States)

    Balla-Arabé, Souleymane; Gao, Xinbo; Wang, Bin

    2013-06-01

    In the last decades, due to the development of the parallel programming, the lattice Boltzmann method (LBM) has attracted much attention as a fast alternative approach for solving partial differential equations. In this paper, we first designed an energy functional based on the fuzzy c-means objective function which incorporates the bias field that accounts for the intensity inhomogeneity of the real-world image. Using the gradient descent method, we obtained the corresponding level set equation from which we deduce a fuzzy external force for the LBM solver based on the model by Zhao. The method is fast, robust against noise, independent to the position of the initial contour, effective in the presence of intensity inhomogeneity, highly parallelizable and can detect objects with or without edges. Experiments on medical and real-world images demonstrate the performance of the proposed method in terms of speed and efficiency.

  17. Continuation of Sets of Constrained Orbit Segments

    DEFF Research Database (Denmark)

    Schilder, Frank; Brøns, Morten; Chamoun, George Chaouki;

    Sets of constrained orbit segments of time continuous flows are collections of trajectories that represent a whole or parts of an invariant set. A non-trivial but simple example is a homoclinic orbit. A typical representation of this set consists of an equilibrium point of the flow and a trajectory...... that starts close and returns close to this fixed point within finite time. More complicated examples are hybrid periodic orbits of piecewise smooth systems or quasi-periodic invariant tori. Even though it is possible to define generalised two-point boundary value problems for computing sets of constrained...... orbit segments, this is very disadvantageous in practice. In this talk we will present an algorithm that allows the efficient continuation of sets of constrained orbit segments together with the solution of the full variational problem....

  18. 3D MR ventricle segmentation in pre-term infants with post-hemorrhagic ventricle dilatation (PHVD) using multi-phase geodesic level-sets.

    Science.gov (United States)

    Qiu, Wu; Yuan, Jing; Rajchl, Martin; Kishimoto, Jessica; Chen, Yimin; de Ribaupierre, Sandrine; Chiu, Bernard; Fenster, Aaron

    2015-09-01

    Intraventricular hemorrhage (IVH) or bleed within the cerebral ventricles is a common condition among very low birth weight pre-term neonates. The prognosis for these patients is worsened should they develop progressive ventricular dilatation, i.e., post-hemorrhagic ventricle dilatation (PHVD), which occurs in 10-30% of IVH patients. Accurate measurement of ventricular volume would be valuable information and could be used to predict PHVD and determine whether that specific patient with ventricular dilatation requires treatment. While the monitoring of PHVD in infants is typically done by repeated transfontanell 2D ultrasound (US) and not MRI, once the patient's fontanels have closed around 12-18months of life, the follow-up patient scans are done by MRI. Manual segmentation of ventricles from MR images is still seen as a gold standard. However, it is extremely time- and labor-consuming, and it also has observer variability. This paper proposes an accurate multiphase geodesic level-set segmentation algorithm for the extraction of the cerebral ventricle system of pre-term PHVD neonates from 3D T1 weighted MR images. The proposed segmentation algorithm makes use of multi-region segmentation technique associated with spatial priors built from a multi-atlas registration scheme. The leave-one-out cross validation with 19 patients with mild enlargement of ventricles and 7 hydrocephalus patients shows that the proposed method is accurate, suggesting that the proposed approach could be potentially used for volumetric and morphological analysis of the ventricle system of IVH neonatal brains in clinical practice. Copyright © 2015 Elsevier Inc. All rights reserved.

  19. Computer-aided measurement of liver volumes in CT by means of geodesic active contour segmentation coupled with level-set algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Suzuki, Kenji; Kohlbrenner, Ryan; Epstein, Mark L.; Obajuluwa, Ademola M.; Xu Jianwu; Hori, Masatoshi [Department of Radiology, University of Chicago, 5841 South Maryland Avenue, Chicago, Illinois 60637 (United States)

    2010-05-15

    Purpose: Computerized liver extraction from hepatic CT images is challenging because the liver often abuts other organs of a similar density. The purpose of this study was to develop a computer-aided measurement of liver volumes in hepatic CT. Methods: The authors developed a computerized liver extraction scheme based on geodesic active contour segmentation coupled with level-set contour evolution. First, an anisotropic diffusion filter was applied to portal-venous-phase CT images for noise reduction while preserving the liver structure, followed by a scale-specific gradient magnitude filter to enhance the liver boundaries. Then, a nonlinear grayscale converter enhanced the contrast of the liver parenchyma. By using the liver-parenchyma-enhanced image as a speed function, a fast-marching level-set algorithm generated an initial contour that roughly estimated the liver shape. A geodesic active contour segmentation algorithm coupled with level-set contour evolution refined the initial contour to define the liver boundaries more precisely. The liver volume was then calculated using these refined boundaries. Hepatic CT scans of 15 prospective liver donors were obtained under a liver transplant protocol with a multidetector CT system. The liver volumes extracted by the computerized scheme were compared to those traced manually by a radiologist, used as ''gold standard.''Results: The mean liver volume obtained with our scheme was 1504 cc, whereas the mean gold standard manual volume was 1457 cc, resulting in a mean absolute difference of 105 cc (7.2%). The computer-estimated liver volumetrics agreed excellently with the gold-standard manual volumetrics (intraclass correlation coefficient was 0.95) with no statistically significant difference (F=0.77; p(F{<=}f)=0.32). The average accuracy, sensitivity, specificity, and percent volume error were 98.4%, 91.1%, 99.1%, and 7.2%, respectively. Computerized CT liver volumetry would require substantially less

  20. From MIP image to MRA segmentation using fuzzy set theory.

    Science.gov (United States)

    Vermandel, Maximilien; Betrouni, Nacim; Taschner, Christian; Vasseur, Christian; Rousseau, Jean

    2007-04-01

    The aim of this paper is to describe a semi-automatic method of segmentation in magnetic resonance angiography (MRA). This method, based on fuzzy set theory, uses the information (gray levels) contained in the maximum intensity projection (MIP) image to segment the 3D vascular structure from slices. Tests have been carried out on vascular phantom and on clinical MRA images. This 3D segmentation method has proved to be satisfactory for the detection of vascular structures even for very complex shapes. Finally, this MIP-based approach is semi-automatic and produces a robust segmentation thanks to the contrast-to-noise ratio and to the slice profile which are taken into account to determine the membership of a voxel to the vascular structure.

  1. Research on Fast Level Set Segmentation Method based on Gauss Distribution Estimation%基于高斯分布估计的快速水平集分割方法研究

    Institute of Scientific and Technical Information of China (English)

    张思维

    2012-01-01

    传统的CV模型只能用于分割灰度分布比较均匀、目标与背景灰度均值差异较大的图像,且因需要求解偏微分方程导致分割速度很慢.文章在传统快速水平集分割模型的基础上,将高斯分布估计引入速度项,使得快速水平集可以分割复杂的目标,并将HIS空间中的色调分量与强度分量进行融合,得到了一种彩色高斯快速模型.新算法具有分割速度快、可分割复杂目标的优点.%The traditional CV model can only be used for the segmentation of the image whose gray distribution is uniform and whose targets and background have a big difference in gray level.The segmentation speed is very slow due to the need of solving partial differential equations during the segmentation process.On the base of the traditional fast level-set segmentation model,Gauss distribution estimation is introduced into a fast level-set method and a new fast level-set method segmentation algorithm is developed.The new algorithm has the advantages of fast segmentation speed and the segmentation of complex targets.

  2. Efficient Algorithms for Segmentation of Item-Set Time Series

    Science.gov (United States)

    Chundi, Parvathi; Rosenkrantz, Daniel J.

    We propose a special type of time series, which we call an item-set time series, to facilitate the temporal analysis of software version histories, email logs, stock market data, etc. In an item-set time series, each observed data value is a set of discrete items. We formalize the concept of an item-set time series and present efficient algorithms for segmenting a given item-set time series. Segmentation of a time series partitions the time series into a sequence of segments where each segment is constructed by combining consecutive time points of the time series. Each segment is associated with an item set that is computed from the item sets of the time points in that segment, using a function which we call a measure function. We then define a concept called the segment difference, which measures the difference between the item set of a segment and the item sets of the time points in that segment. The segment difference values are required to construct an optimal segmentation of the time series. We describe novel and efficient algorithms to compute segment difference values for each of the measure functions described in the paper. We outline a dynamic programming based scheme to construct an optimal segmentation of the given item-set time series. We use the item-set time series segmentation techniques to analyze the temporal content of three different data sets—Enron email, stock market data, and a synthetic data set. The experimental results show that an optimal segmentation of item-set time series data captures much more temporal content than a segmentation constructed based on the number of time points in each segment, without examining the item set data at the time points, and can be used to analyze different types of temporal data.

  3. Image Segmentation Method Research Based on Improved Variational Level Set and Region Growth%基于改进的变分水平集和区域生长的图像分割方法的研究

    Institute of Scientific and Technical Information of China (English)

    姜慧研; 冯锐杰

    2012-01-01

    针对水平集和区域生长方法都存在对噪声和初始边界敏感以及容易从弱边缘处泄露等不稳定的问题,提出了结合待分割目标灰度统计信息和图像梯度信息的水平集演化函数对水平集方法进行改进,并利用区域生长方法解决水平集方法对初始边界敏感的问题.分别用传统区域生长方法、阈值方法、GAC模型、C-V模型、Snake模型以及本文方法进行从腹部CT图像分割肝脏区域的实验比较,实验结果表明:本文方法不仅可以减少图像分割的时间,而且显著地提高了分割质量.%To address the instability problems of level set and region growth, for example, they are sensitive to noises and initial boundaries as well as they will easily leak from the weak boundaries, an improved image segmentation method based on level set is proposed. Our model consists of an external energy term that involves the image gray-scale statistical information and gradient information. And we use region growth method to solve the problem that level set method is sensitive to initial boundaries, we contrast our improved method with region growth method, threshold method, GAC model, C-V model, Snake model to segment livers from abdominal CT images. The experiment results show that our method can not only be efficient for image segmentation,but also greatly improve the quality of segmentation.

  4. A Variational Level Set Method of Image Segmentation Based on Thresholding Initial Contour%一种基于阈值初始化的变分水平集牙菌斑图像分割方法

    Institute of Scientific and Technical Information of China (English)

    兰红; 陈凌; 张璐

    2011-01-01

    将变分水平集和图像阀值化两种图像分割方法相结合,在分析灰度图像直方图分布的基础上提出利用图像阈值设定C-V模型的初始化轮廓的新方法,改变了原有C-V模型的初始轮廓线设置中存在的不足.新方法应用于牙菌斑图像分割中能够较好的识别牙齿图像边缘信息,为下一步对牙菌斑进行量化分析提供了良好的数据基础.%Variational level set method is a quite hot research point in image processing. C-V model is a classic approach to segment image based on variational level set. It is especially helpful for medical images analysis ,which has complex topology constructions, strong noises and lower contrast. But C-V model depends on initial contour. Image thresholding is also a simple and popular image segmentation method, which separates an image into two parts, and gets the target sub-image from background image. In the article, these two methods are integrated together. By analyzing the distribution of image gray level histogram , the authors propose a new method which initializes contour using threshold. It solves the shortages about how to set initial contours in C-V model . The novel C-V model used in dental plaque image segmentation and experiments illustrates that the method proposed can help segment images. It provides a preliminary work to further analyze dental plaque.

  5. 基于变分水平集模型的虹膜图像分割方法%Iris Image Segmentation Method Based on Variational Level Set Model

    Institute of Scientific and Technical Information of China (English)

    张荷萍; 徐效文

    2013-01-01

    Segmenting the iris accurately is a main problem for iris recognition, due to the impact of the eyelids, eyelashes and deformation. This paper presents an iris segmentation method based on variational level set model. It uses gray projection algorithm to locate the pupil, applies a least square fitting algorithm to estimate the boundary between the pupil and the iris, and employs a variational level set model to accurately segment the iris. Experimental results demonstrate the segmentation accuracy of 98.59%for outer edge of the iris is better than using Daugman method, Hough transformation method and improved Hough transformation method.%当虹膜图像受眼睑、睫毛及变形等影响时,会造成分割不准确,如何有效地分割虹膜是虹膜识别面临的主要问题。为此,提出一种基于变分水平集模型的虹膜图像分割方法。采用灰度投影法粗略确定瞳孔,使用最小二乘拟合得到瞳孔与虹膜边界,通过变分水平集模型精确分割虹膜。实验结果表明,该方法对虹膜外边缘分割的准确率为98.59%,高于Daugman、Hough变换及改进Hough变换等常用方法。

  6. Automatic segmentation of coronary morphology using transmittance-based lumen intensity-enhanced intravascular optical coherence tomography images and applying a localized level-set-based active contour method.

    Science.gov (United States)

    Joseph, Shiju; Adnan, Asif; Adlam, David

    2016-10-01

    Lumen segmentation from clinical intravascular optical coherence tomography (IV-OCT) images has clinical relevance as it provides a full three-dimensional perspective of diseased coronary artery sections. Inaccurate segmentation may occur when there are artifacts in the image, resulting from issues such as inadequate blood clearance. This study proposes a transmittance-based lumen intensity enhancement method that ensures only lumen regions are highlighted. A level-set-based active contour method that utilizes the local speckle distribution properties of the image is then employed to drive an image-specific active contour toward the true lumen boundaries. By utilizing local speckle properties, the intensity variation issues within the image are resolved. This combined approach has been successfully applied to challenging clinical IV-OCT datasets that contains multiple lumens, residual blood flow, and its shadowing artifact. A method to identify the guide-wire and interpolate the lost lumen segments has been implemented. This approach is fast and can be performed even when guide-wire boundaries are not easily identified. Lumen enhancement also makes it easy to identify vessel side branches. This automated approach is not only able to extract the arterial lumen, but also the smaller microvascular lumens that are associated with the vasa vasorum and with atherosclerotic plaque.

  7. 面向B超图像分割的动态权重因子水平集方法%Level set method reconciled with a dynamic weighting factor for B-mode ultrasound image segmentation

    Institute of Scientific and Technical Information of China (English)

    杨谊; 喻德旷; 申洪; 刘民锋

    2015-01-01

    目的:研究和改进水平集方法,实现B超图像中病灶区域的准确快速分割。方法分析已有水平集方法在B超图像处理中的局限,基于区域水平集的优点,将信息论中的熵引入图像处理,定义动态权重因子,准确反映局部灰度阶梯变化状况,定量度量轮廓线像素点分别受到趋向目标、背景区域的两种作用力的动态权重,将其融合到区域水平集中,迭代引导曲线形变和位移。由于B超图像病灶分割属于指定区域的局部分割,所以将计算约束到局部范围,从而明显降低运算代价。结果动态权重因子水平集方法能够较好分割B超图像中的病灶区域,与几种主流水平集方法相比,本文方法精度更高,时间复杂度更小。结论动态权重因子方法能够更合理准确地判断病灶边界像素点,局部计算策略有效地提高了分割效率。%Objective To modify the level set method for precise and fast segmentation of B-type ultrasound image lesions. Methods Based on the best of region level set method, entropy in the information theory was introduced into image processing to define a dynamic weighting factor that responded to the gradient change of the local gray levels to evaluate the dynamic degree of driven force on each pixel on the contour to the target and background areas. The dynamic weighting factors were reconciled into the regional level set model and led the contour to deform and move during the iterations. As lesion segmentation was classified as local segmentation of a specific area, the calculation was restrained to the local sphere abide by the contour, which greatly reduced the calculation complex. Results Experiments on B-type ultrasound images showed improved results of the proposed method with a better accuracy and less time consumption compared with several current level set methods. Conclusion Level set method reconciled with dynamic weighting factor allows a

  8. Abdominal CT Image Segmentation Based on Graph Cuts and Fast Level Set%基于图割与快速水平集的腹部CT图像分割

    Institute of Scientific and Technical Information of China (English)

    杨昌俊; 杨新

    2011-01-01

    An interactive segmentation method based on graph cuts and improved fast level set is proposed to segment abdominal CT image.In our approach,an initial contour is sketched and dilated,a graph for graph cuts method is constructed while inner contour vertices based on morphologic dilation are identified as source and outer contour vertices as sink,the Pre-CT image segmentation is achieved by graph cuts method roughly,and then with the initial inner contour of dilation,the fast level set algorithm based on the Region Competition Based Active Contour(RCAC)model is applied to re-segment the result image by graph cuts.Thus,the low speed and leakage error in traditional level set methods are avoided.Furthermore,we extend this segmentation method to three dimensions,and several 3-D abdominal organs are segmented.Doctors could straightforwardly visualize the organs'relationship and structure topologically after 3-D reconstruction.Experimental results show that the proposed method is with interactive simply,robustness and high accuracy,and can support doctors for diagnosis and surgical planning effectively.%针对腹部CT图像中组织分割的问题,提出了一种基于图割与改进的快速水平集的交互式分割方法。首先对人工给定的一个待分割目标的初始轮廓作膨胀运算,将所得内部边界所有像素点作为源点、外部边界像素点作为汇点构造图,并通过图割方法对CT图像进行初步分割,然后以膨胀所得内部边界作为初始轮廓,通过基于区域竞争主动轮廓模型(RCAC)的快速水平集算法对初步分割后的图像进行精确分割,克服了传统水平集方法运算速度较慢及易产生边界泄漏的问题。在此基础上将二维分割推广到三维分割,最终完成腹部不同器官的完整三维分割。进行三维重建,使医生能直观地观测到各器官的三维相对位置和拓扑结构。实验结果表明,该方法交互简单、鲁棒性强、准确性

  9. AUTOMATIC RETINA EXUDATES SEGMENTATION WITHOUT A MANUALLY LABELLED TRAINING SET

    Energy Technology Data Exchange (ETDEWEB)

    Giancardo, Luca [ORNL; Meriaudeau, Fabrice [ORNL; Karnowski, Thomas Paul [ORNL; Li, Yaquin [University of Tennessee, Knoxville (UTK); Tobin Jr, Kenneth William [ORNL; Chaum, Edward [University of Tennessee, Knoxville (UTK)

    2011-01-01

    Diabetic macular edema (DME) is a common vision threatening complication of diabetic retinopathy which can be assessed by detecting exudates (a type of bright lesion) in fundus images. In this work, two new methods for the detection of exudates are presented which do not use a supervised learning step and therefore do not require ground-truthed lesion training sets which are time consuming to create, difficult to obtain, and prone to human error. We introduce a new dataset of fundus images from various ethnic groups and levels of DME which we have made publicly available. We evaluate our algorithm with this dataset and compare our results with two recent exudate segmentation algorithms. In all of our tests, our algorithms perform better or comparable with an order of magnitude reduction in computational time.

  10. Robust level set method for computer vision

    Science.gov (United States)

    Si, Jia-rui; Li, Xiao-pei; Zhang, Hong-wei

    2005-12-01

    Level set method provides powerful numerical techniques for analyzing and solving interface evolution problems based on partial differential equations. It is particularly appropriate for image segmentation and other computer vision tasks. However, there exists noise in every image and the noise is the main obstacle to image segmentation. In level set method, the propagation fronts are apt to leak through the gaps at locations of missing or fuzzy boundaries that are caused by noise. The robust level set method proposed in this paper is based on the adaptive Gaussian filter. The fast marching method provides a fast implementation for level set method and the adaptive Gaussian filter can adapt itself to the local characteristics of an image by adjusting its variance. Thus, the different parts of an image can be smoothed in different way according to the degree of noisiness and the type of edges. Experiments results demonstrate that the adaptive Gaussian filter can greatly reduce the noise without distorting the image and made the level set methods more robust and accurate.

  11. WEB DOCUMENT SEGMENTATION USING FREQUENT TERM SETS FOR SUMMARIZATION

    Directory of Open Access Journals (Sweden)

    Sarukesi Karunakaran

    2012-01-01

    Full Text Available Query sensitive summarization aims at extracting the query relevant contents from web documents. Web page segmentation focuses on reducing the run time overhead of the summarization systems by grouping the related contents of a web page into segments. At query time, query relevant segments of the web page are identified and important sentences from these segments are extracted to compose the summary. DOM tree structures of the web documents are utilized to perform the segmentation of the contents. Leaf nodes of DOM tress are merged to form segments according to the statistical and linguistic similarity measure. The proposed system has been evaluated by intrinsic approach making use of user satisfaction index. The performance of the system is compared with summarization without using preprocessed segments. Performance of this system is more promising than the other measures like cosine similarity, jaccard measure which make use of sparse term-frequent vectors, since the most frequent term sets are considered to measure the relevance. Relevant segments alone need to be processed at run time for summarization which reduces the time complexity of the summarization process.

  12. 3D Medical Image Segmentation Based on Rough Set Theory

    Institute of Scientific and Technical Information of China (English)

    CHEN Shi-hao; TIAN Yun; WANG Yi; HAO Chong-yang

    2007-01-01

    This paper presents a method which uses multiple types of expert knowledge together in 3D medical image segmentation based on rough set theory. The focus of this paper is how to approximate a ROI (region of interest) when there are multiple types of expert knowledge. Based on rough set theory, the image can be split into three regions:positive regions; negative regions; boundary regions. With multiple knowledge we refine ROI as an intersection of all of the expected shapes with single knowledge. At last we show the results of implementing a rough 3D image segmentation and visualization system.

  13. Variational level set model integrated with fuzzy clustering for image segmentation%融合模糊聚类的变分水平集图像分割模型

    Institute of Scientific and Technical Information of China (English)

    张虎重; 康志伟

    2011-01-01

    Variational level set and fuzzy clustering both have the characteristic that extracts the target objects by minimizing the objective function in image segmentation. This paper presents a method which integrates with the advantages of two methods. The new method establishes a variational level set energy function model by using the subordinate property of the membership function in fuzzy clustering. The extraction of target object is implemented by Partial Difference Equation (PDE) derived from minimizing the energy functional. The results show that the rationality and effectiveness of the proposed model are demonstrated by the good segmentation quality and efficiency.%针对在图像分割中变分水平集与模糊聚类都具有通过最小化目标函数来提取目标物体这一特征,提出了汲取两种方法优势、实现融合的新方法.该方法利用模糊聚类中隶属度函数的从属性质,建立了新的变分水平集能量函数模型,通过极小化能量泛函,获得了水平集函数演化的偏微分方程,实现了目标物体的提取.实验结果表明,该方法具有良好的分割质量与分割效率,验证了新模型的合理性与有效性.

  14. 水平集分层分割遥感图像中的建筑物%Automatic building segmentation from remote sensing images using multi-layer level set framework

    Institute of Scientific and Technical Information of China (English)

    郭靖; 江洁; 曹世翔

    2014-01-01

    Towards high resolution remote sensing images, combining with features of buildings, a novel method to extract buildings based on multi-layer level set framework was proposed. Firstly, as far as the impact of shadow and vegetation was concerned, it should be removed on the basis of the separation of gray value thresh and the joint distribution of hue and saturation. Then, an improved C-V level set segmentation algorithm combining with building features of roof′s gray and obvious boundaries was applied to extract building regions of similar gray-scales on each gray layer, and thus all building regions of different gray-scales could be extracted layer by layer, followed by layers of segmented regions integration. Finally, the non-building regions were excluded by using normal areas of buildings and related position between buildings and shadows. The experiment results demonstrate that, compared with the traditional level set methods, this one can detect each single building of gray heterogeneity and buildings of multiple shapes and different gray-scales. Meanwhile, compared to the traditional C-V method, it largely reduces the leakage segmentation ratio by 25% and over-segmentation by 22%.%针对高分辨率遥感图像,结合建筑物特征,提出水平集分层模型分割图像中的建筑物。首先,学习植被样本得到其在HSV空间中色调与饱和度的联合分布函数,利用阴影灰度方差通常小于非阴影区域的特点,将植被和阴影剔除以简化背景利于后续分割。然后,根据灰度级高低将一幅图像看作多层图像层,把建筑物的屋顶灰度特征和边缘特征融合到传统Chan-Vese(C-V)水平集算法中,分割出每层中灰度级相似的建筑物候选区域,从而将不同灰度级建筑物候选区域分层分割出来再整合。最后利用建筑物面积、建筑物与阴影位置关系等先验知识排除误分割,得到最终结果。实验表明:该方法能更好地分割

  15. Research on the application of distant preserving level set algorithm in car door lock image segment%距离保持水平集在汽车门锁图像分割中的应用研究

    Institute of Scientific and Technical Information of China (English)

    王瑶; 安伟; 尤丽华

    2015-01-01

    This paper focus on the research of image segment algorithm based on distant preserving level set, which is used in rocker distance measurement in the car door lock assembly detection system, which is based on machine vision. The algorithm regard profile as a sign function, and the zero horizontal contour of a sign function is in correspondence with the actual outline, more over, the algorithm add a internal energy functional to the energy functional, which represents the difference between the two functions. Experiments show that compared with the general image segmentation algorithm based on edge detection, the algorithm can solve the problem of image segmentation in car door lock's rocker outside arc, and improve the accuracy of car door lock auto detection system. Moreover, the algorithm can also be applied to other similar industrial product image segmentation.%针对基于机器视觉的汽车门锁装配尺寸检测系统中摇臂距离的检测问题,研究了距离保持水平集的图像分割算法。该算法是将轮廓表示为一个符号函数,符号函数的零水平面与实际轮廓相对应,并在能量泛函中加入了内部能量泛函,表示两个函数之间的差异。实验表明,与一般的基于边缘检测的图像分割算法相比较,该算法能够很好的解决汽车门锁图像中摇臂外弧线分割问题,提高了汽车门锁检测系统的精度。同时,该算法也可应用到其他类似工业装配件局部图像分割中。

  16. Model of the variational level set image segmentation based on visual attention features%视觉注意特征的变分水平集图像分割模型

    Institute of Scientific and Technical Information of China (English)

    王徐民; 张晓光

    2013-01-01

    针对传统主动轮廓模型较低的鲁棒性能和对先验知识融合能力的不足,基于视觉注意机制的先验知识和曲线演化的理论框架,首先建立图像底层视觉显著性特征的数学模型,在此基础上提出新的曲线演化能量泛函模型,然后对该能量泛函采用变分水平集方法进行推导,得到曲线演化的偏微分方程,数值实验表明该模型相对于经典主动轮廓模型具有更强的抗噪性与分割效率.该模型的提出为进一步在主动轮廓模型中引入更高层次视觉显著性特征、得到更优越的分割模型打下了基础.%The robust and fusion capacity of the traditional active contour models is poor. The mathematical model of rock-bottom visual attention characteristics in image was first established based on a priori knowledge of mechanism of visual attention and theoretical framework of curve evolution, a new curve evolution energy functional model was put forward, then partial differential equations to guide the curve evolution were established according to variational level set to this energy functional. The numerical experiments showed that the model was more robust and had higher segmentation efficiency than classical active contour model. The model laid the foundation for higher level visual significant features and getting better segmentation.

  17. Side scan sonar image segmentation based on neutrosophic set and quantum-behaved particle swarm optimization algorithm

    Science.gov (United States)

    Zhao, Jianhu; Wang, Xiao; Zhang, Hongmei; Hu, Jun; Jian, Xiaomin

    2016-09-01

    To fulfill side scan sonar (SSS) image segmentation accurately and efficiently, a novel segmentation algorithm based on neutrosophic set (NS) and quantum-behaved particle swarm optimization (QPSO) is proposed in this paper. Firstly, the neutrosophic subset images are obtained by transforming the input image into the NS domain. Then, a co-occurrence matrix is accurately constructed based on these subset images, and the entropy of the gray level image is described to serve as the fitness function of the QPSO algorithm. Moreover, the optimal two-dimensional segmentation threshold vector is quickly obtained by QPSO. Finally, the contours of the interested target are segmented with the threshold vector and extracted by the mathematic morphology operation. To further improve the segmentation efficiency, the single threshold segmentation, an alternative algorithm, is recommended for the shadow segmentation by considering the gray level characteristics of the shadow. The accuracy and efficiency of the proposed algorithm are assessed with experiments of SSS image segmentation.

  18. Multiregion level-set partitioning of synthetic aperture radar images.

    Science.gov (United States)

    Ben Ayed, Ismail; Mitiche, Amar; Belhadj, Ziad

    2005-05-01

    The purpose of this study is to investigate Synthetic Aperture Radar (SAR) image segmentation into a given but arbitrary number of gamma homogeneous regions via active contours and level sets. The segmentation of SAR images is a difficult problem due to the presence of speckle which can be modeled as strong, multiplicative noise. The proposed algorithm consists of evolving simple closed planar curves within an explicit correspondence between the interiors of curves and regions of segmentation to minimize a criterion containing a term of conformity of data to a speckle model of noise and a term of regularization. Results are shown on both synthetic and real images.

  19. Object-level Segmentation of RGBD Data

    Science.gov (United States)

    Huang, H.; Jiang, H.; Brenner, C.; Mayer, H.

    2014-08-01

    We propose a novel method to segment Microsoft™Kinect data of indoor scenes with the emphasis on freeform objects. We use the full 3D information for the scene parsing and the segmentation of potential objects instead of treating the depth values as an additional channel of the 2D image. The raw RGBD image is first converted to a 3D point cloud with color. We then group the points into patches, which are derived from a 2D superpixel segmentation. With the assumption that every patch in the point cloud represents (a part of) the surface of an underlying solid body, a hypothetical quasi-3D model - the "synthetic volume primitive" (SVP) is constructed by extending the patch with a synthetic extrusion in 3D. The SVPs vote for a common object via intersection. By this means, a freeform object can be "assembled" from an unknown number of SVPs from arbitrary angles. Besides the intersection, two other criteria, i.e., coplanarity and color coherence, are integrated in the global optimization to improve the segmentation. Experiments demonstrate the potential of the proposed method.

  20. 结合快速步进法的Level Set人体足部图像分割%Human foot medical image segmentation based on level set algorithm with fast marching

    Institute of Scientific and Technical Information of China (English)

    蒋爱; 李晓宁

    2010-01-01

    针对Level set算法运算速度较慢和易产生边缘泄露的不足,引入了结合快速步进的Level Set算法,提出了一套完整的分割人体足部骨骼图像技术路线.修正了原始"光切片"图像噪声多的不足,通过预处理去除噪声,增强边缘;设定分割初始点和运算参数,运行改进的Level set算法提取骨骼区域;运行形态学开操作进行边缘断裂和毛刺修复.实验结果表明,该处理流程具有较好的准确度和鲁棒性,与经典Level Set算法相比,改进的算法能提高19%~36%的运行速度.

  1. Quantitative evaluation of six graph based semi-automatic liver tumor segmentation techniques using multiple sets of reference segmentation

    Science.gov (United States)

    Su, Zihua; Deng, Xiang; Chefd'hotel, Christophe; Grady, Leo; Fei, Jun; Zheng, Dong; Chen, Ning; Xu, Xiaodong

    2011-03-01

    Graph based semi-automatic tumor segmentation techniques have demonstrated great potential in efficiently measuring tumor size from CT images. Comprehensive and quantitative validation is essential to ensure the efficacy of graph based tumor segmentation techniques in clinical applications. In this paper, we present a quantitative validation study of six graph based 3D semi-automatic tumor segmentation techniques using multiple sets of expert segmentation. The six segmentation techniques are Random Walk (RW), Watershed based Random Walk (WRW), LazySnapping (LS), GraphCut (GHC), GrabCut (GBC), and GrowCut (GWC) algorithms. The validation was conducted using clinical CT data of 29 liver tumors and four sets of expert segmentation. The performance of the six algorithms was evaluated using accuracy and reproducibility. The accuracy was quantified using Normalized Probabilistic Rand Index (NPRI), which takes into account of the variation of multiple expert segmentations. The reproducibility was evaluated by the change of the NPRI from 10 different sets of user initializations. Our results from the accuracy test demonstrated that RW (0.63) showed the highest NPRI value, compared to WRW (0.61), GWC (0.60), GHC (0.58), LS (0.57), GBC (0.27). The results from the reproducibility test indicated that GBC is more sensitive to user initialization than the other five algorithms. Compared to previous tumor segmentation validation studies using one set of reference segmentation, our evaluation methods use multiple sets of expert segmentation to address the inter or intra rater variability issue in ground truth annotation, and provide quantitative assessment for comparing different segmentation algorithms.

  2. Global segmentation and curvature analysis of volumetric data sets using trivariate B-spline functions.

    Science.gov (United States)

    Soldea, Octavian; Elber, Gershon; Rivlin, Ehud

    2006-02-01

    This paper presents a method to globally segment volumetric images into regions that contain convex or concave (elliptic) iso-surfaces, planar or cylindrical (parabolic) iso-surfaces, and volumetric regions with saddle-like (hyperbolic) iso-surfaces, regardless of the value of the iso-surface level. The proposed scheme relies on a novel approach to globally compute, bound, and analyze the Gaussian and mean curvatures of an entire volumetric data set, using a trivariate B-spline volumetric representation. This scheme derives a new differential scalar field for a given volumetric scalar field, which could easily be adapted to other differential properties. Moreover, this scheme can set the basis for more precise and accurate segmentation of data sets targeting the identification of primitive parts. Since the proposed scheme employs piecewise continuous functions, it is precise and insensitive to aliasing.

  3. Level Sets and Voronoi based Feature Extraction from any Imagery

    DEFF Research Database (Denmark)

    Sharma, O.; Anton, François; Mioc, Darka

    2012-01-01

    Polygon features are of interest in many GEOProcessing applications like shoreline mapping, boundary delineation, change detection, etc. This paper presents a unique new GPU-based methodology to automate feature extraction combining level sets, or mean shift based segmentation together with Voronoi...

  4. APLIKASI SEGMENTASI GAMBAR DENGAN MENGGUNAKAN METODE LEVEL SET

    Directory of Open Access Journals (Sweden)

    Kartika Gunadi

    2007-01-01

    Full Text Available Today, manipulating an image become easier because of the advance of image processing technology. These technologies include segmentation on digital image which allows users to extract a particular object from an image to be processed individually. One of image segmentation methods is Level Set which track propagating curve. Curve will evolve until it stops at the border of an object in a image. The experiments in this research has validated that Level Set method can be used in image segmentation and the result will be better in images that have solid colors. Abstract in Bahasa Indonesia : Saat ini, manipulasi gambar menjadi semakin mudah dilakukan, salah satu penyebabnya adalah segmentasi pada gambar digital. Dengan segmentasi gambar maka di dalam suatu gambar setiap obyek dapat dibedakan satu sama lain , sehingga memudahkan untuk mengolah masing-masing obyek. Level Set adalah metode untuk mendeteksi pergerakan kurva yang dapat digunakan untuk melakukan segmentasi gambar. Kurva akan bergerak sampai pada akhirnya berhenti pada border dari obyek dalam sebuah gambar. Pengujian yang telah dilakukan dalam karya ilmiah ini membuktikan bahwa Metode Level Set dapat digunakan untuk segmentasi gambar dalam berbagai bentuk, baik itu cembung maupun cekung, dan hasilnya akan jauh lebih baik apabila gambar yang digunakan tidak memiliki variasi warna yang banyak (solid, seperti gambar kartun. Kata kunci: level set, active contour, segmentasi gambar

  5. Multi-level segment analysis: definition and applications in turbulence

    Science.gov (United States)

    Wang, Lipo

    2015-11-01

    The interaction of different scales is among the most interesting and challenging features in turbulence research. Existing approaches used for scaling analysis such as structure-function and Fourier spectrum method have their respective limitations, for instance scale mixing, i.e. the so-called infrared and ultraviolet effects. For a given function, by specifying different window sizes, the local extremal point set will be different. Such window size dependent feature indicates multi-scale statistics. A new method, multi-level segment analysis (MSA) based on the local extrema statistics, has been developed. The part of the function between two adjacent extremal points is defined as a segment, which is characterized by the functional difference and scale difference. The structure function can be differently derived from these characteristic parameters. Data test results show that MSA can successfully reveal different scaling regimes in turbulence systems such as Lagrangian and two-dimensional turbulence, which have been remaining controversial in turbulence research. In principle MSA can generally be extended for various analyses.

  6. A word level segmentation for off-line Arabic characters

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Segmentation of cursive text has been one of the major problems in Arabic writing. The problem is the shape of the letter which is context sensitive, depending on it' s location within a word. Many text recognition systems recognize text imagery at the character level and assemble words from the recognized characters.Unfortunately this approach does not work with Arabic text. In this paper we describe a new approach to segment Arabic text imagery at a word level, without analyzing individual characters. This approach avoids the problem of individual characters segmentation, and can overcome local errors in character recognition.

  7. On reinitializing level set functions

    Science.gov (United States)

    Min, Chohong

    2010-04-01

    In this paper, we consider reinitializing level functions through equation ϕt+sgn(ϕ0)(‖∇ϕ‖-1)=0[16]. The method of Russo and Smereka [11] is taken in the spatial discretization of the equation. The spatial discretization is, simply speaking, the second order ENO finite difference with subcell resolution near the interface. Our main interest is on the temporal discretization of the equation. We compare the three temporal discretizations: the second order Runge-Kutta method, the forward Euler method, and a Gauss-Seidel iteration of the forward Euler method. The fact that the time in the equation is fictitious makes a hypothesis that all the temporal discretizations result in the same result in their stationary states. The fact that the absolute stability region of the forward Euler method is not wide enough to include all the eigenvalues of the linearized semi-discrete system of the second order ENO spatial discretization makes another hypothesis that the forward Euler temporal discretization should invoke numerical instability. Our results in this paper contradict both the hypotheses. The Runge-Kutta and Gauss-Seidel methods obtain the second order accuracy, and the forward Euler method converges with order between one and two. Examining all their properties, we conclude that the Gauss-Seidel method is the best among the three. Compared to the Runge-Kutta, it is twice faster and requires memory two times less with the same accuracy.

  8. Low-Level Hierarchical Multiscale Segmentation Statistics of Natural Images.

    Science.gov (United States)

    Akbas, Emre; Ahuja, Narendra

    2014-09-01

    This paper is aimed at obtaining the statistics as a probabilistic model pertaining to the geometric, topological and photometric structure of natural images. The image structure is represented by its segmentation graph derived from the low-level hierarchical multiscale image segmentation. We first estimate the statistics of a number of segmentation graph properties from a large number of images. Our estimates confirm some findings reported in the past work, as well as provide some new ones. We then obtain a Markov random field based model of the segmentation graph which subsumes the observed statistics. To demonstrate the value of the model and the statistics, we show how its use as a prior impacts three applications: image classification, semantic image segmentation and object detection.

  9. A geometric level set model for ultrasounds analysis

    Energy Technology Data Exchange (ETDEWEB)

    Sarti, A.; Malladi, R.

    1999-10-01

    We propose a partial differential equation (PDE) for filtering and segmentation of echocardiographic images based on a geometric-driven scheme. The method allows edge-preserving image smoothing and a semi-automatic segmentation of the heart chambers, that regularizes the shapes and improves edge fidelity especially in presence of distinct gaps in the edge map as is common in ultrasound imagery. A numerical scheme for solving the proposed PDE is borrowed from level set methods. Results on human in vivo acquired 2D, 2D+time,3D, 3D+time echocardiographic images are shown.

  10. Fast Sparse Level Sets on Graphics Hardware.

    Science.gov (United States)

    Jalba, Andrei C; van der Laan, Wladimir J; Roerdink, Jos B T M

    2013-01-01

    The level-set method is one of the most popular techniques for capturing and tracking deformable interfaces. Although level sets have demonstrated great potential in visualization and computer graphics applications, such as surface editing and physically based modeling, their use for interactive simulations has been limited due to the high computational demands involved. In this paper, we address this computational challenge by leveraging the increased computing power of graphics processors, to achieve fast simulations based on level sets. Our efficient, sparse GPU level-set method is substantially faster than other state-of-the-art, parallel approaches on both CPU and GPU hardware. We further investigate its performance through a method for surface reconstruction, based on GPU level sets. Our novel multiresolution method for surface reconstruction from unorganized point clouds compares favorably with recent, existing techniques and other parallel implementations. Finally, we point out that both level-set computations and rendering of level-set surfaces can be performed at interactive rates, even on large volumetric grids. Therefore, many applications based on level sets can benefit from our sparse level-set method.

  11. Fast Sparse Level Sets on Graphics Hardware

    NARCIS (Netherlands)

    Jalba, Andrei C.; Laan, Wladimir J. van der; Roerdink, Jos B.T.M.

    2013-01-01

    The level-set method is one of the most popular techniques for capturing and tracking deformable interfaces. Although level sets have demonstrated great potential in visualization and computer graphics applications, such as surface editing and physically based modeling, their use for interactive sim

  12. Efficient algorithm for level set method preserving distance function.

    Science.gov (United States)

    Estellers, Virginia; Zosso, Dominique; Lai, Rongjie; Osher, Stanley; Thiran, Jean-Philippe; Bresson, Xavier

    2012-12-01

    The level set method is a popular technique for tracking moving interfaces in several disciplines, including computer vision and fluid dynamics. However, despite its high flexibility, the original level set method is limited by two important numerical issues. First, the level set method does not implicitly preserve the level set function as a distance function, which is necessary to estimate accurately geometric features, s.a. the curvature or the contour normal. Second, the level set algorithm is slow because the time step is limited by the standard Courant-Friedrichs-Lewy (CFL) condition, which is also essential to the numerical stability of the iterative scheme. Recent advances with graph cut methods and continuous convex relaxation methods provide powerful alternatives to the level set method for image processing problems because they are fast, accurate, and guaranteed to find the global minimizer independently to the initialization. These recent techniques use binary functions to represent the contour rather than distance functions, which are usually considered for the level set method. However, the binary function cannot provide the distance information, which can be essential for some applications, s.a. the surface reconstruction problem from scattered points and the cortex segmentation problem in medical imaging. In this paper, we propose a fast algorithm to preserve distance functions in level set methods. Our algorithm is inspired by recent efficient l(1) optimization techniques, which will provide an efficient and easy to implement algorithm. It is interesting to note that our algorithm is not limited by the CFL condition and it naturally preserves the level set function as a distance function during the evolution, which avoids the classical re-distancing problem in level set methods. We apply the proposed algorithm to carry out image segmentation, where our methods prove to be 5-6 times faster than standard distance preserving level set techniques. We

  13. LEVEL SET METHODS BASED ON DISTANCE FUNCTION

    Institute of Scientific and Technical Information of China (English)

    王德军; 唐云; 于洪川; 唐泽圣

    2003-01-01

    Some basic problems on the level set methods were discussed, such as the method used to preserve the distance function, the existence and uniqueness of solution for the level set equations. The main contribution is to prove that in a neighborhood of the initial zero level set, the level set equations with the restriction of the distance function have a unique solution, which must be the signed distance function with respect to the evolving surface. Some skillful approaches were used: Noticing that any solution for the original equation was a distance function, the original level set equations were transformed into a simpler alternative form. Moreover, since the new system was not a classical one, the system was transforned into an ordinary one, for which the implicit function method was adopted.

  14. Segmentation of electron tomographic data sets using fuzzy set theory principles.

    Science.gov (United States)

    Garduño, Edgar; Wong-Barnum, Mona; Volkmann, Niels; Ellisman, Mark H

    2008-06-01

    In electron tomography the reconstructed density function is typically corrupted by noise and artifacts. Under those conditions, separating the meaningful regions of the reconstructed density function is not trivial. Despite development efforts that specifically target electron tomography manual segmentation continues to be the preferred method. Based on previous good experiences using a segmentation based on fuzzy logic principles (fuzzy segmentation) where the reconstructed density functions also have low signal-to-noise ratio, we applied it to electron tomographic reconstructions. We demonstrate the usefulness of the fuzzy segmentation algorithm evaluating it within the limits of segmenting electron tomograms of selectively stained, plastic embedded spiny dendrites. The results produced by the fuzzy segmentation algorithm within the framework presented are encouraging.

  15. Candidate Smoke Region Segmentation of Fire Video Based on Rough Set Theory

    OpenAIRE

    Yaqin Zhao

    2015-01-01

    Candidate smoke region segmentation is the key link of smoke video detection; an effective and prompt method of candidate smoke region segmentation plays a significant role in a smoke recognition system. However, the interference of heavy fog and smoke-color moving objects greatly degrades the recognition accuracy. In this paper, a novel method of candidate smoke region segmentation based on rough set theory is presented. First, Kalman filtering is used to update video background in order to ...

  16. 结合Gabor纹理特征的局域化多通道水平集分割方法%Localized Multi-Channel Level Set Segmentation Combined with Gabor Texture Feature

    Institute of Scientific and Technical Information of China (English)

    张立和; 朱莉莉; 米晓莉

    2011-01-01

    本文提出了一种局域化多通道主动轮廓模型的图像分割算法.针对纹理特征比较明显的图像,通过Gabor滤波提取纹理特征,与图像灰度信息构成多通道.考虑到演化过程中曲线内部和外部特征属性不均匀,引入局域化思想,通过计算各像素在局部区域的最小能量得到图像分割结果.最后算法结合先验形状对有遮挡目标进行分割,并能得到理想结果.大量实验验证了该方法具有良好的分割性能,优于同类算法.%An new algorithm based on localized Multi-Channel active contour model is proposed for image segmentation. For the images with obvious texture, Gabor texture features ate constituted multiple channels of active contour model together with image intensity information. Considering that intensity and texture characteristics are inconsistent in the interior and exterior of the evolution curve, localized energy idea is introduced, the minimum energy is calculated in the specific local area around each pixel on the evolution curve. Our model combined with the shape prior is used to segment the shadowed objects. The proposed algorithm is exemplified on various images objects and its superiority over state of the art variations] segmentation techniques is demonstrated.

  17. Level sets of multiple ergodic averages

    CERN Document Server

    Ai-Hua, Fan; Ma, Ji-Hua

    2011-01-01

    We propose to study multiple ergodic averages from multifractal analysis point of view. In some special cases in the symbolic dynamics, Hausdorff dimensions of the level sets of multiple ergodic average limit are determined by using Riesz products.

  18. A Lagrangian particle level set method

    Science.gov (United States)

    Hieber, Simone E.; Koumoutsakos, Petros

    2005-11-01

    We present a novel particle level set method for capturing interfaces. The level set equation is solved in a Lagrangian frame using particles that carry the level set information. A key aspect of the method involves a consistent remeshing procedure for the regularization of the particle locations when the particle map gets distorted by the advection field. The Lagrangian description of the level set method is inherently adaptive and exact in the case of solid body motions. The efficiency and accuracy of the method is demonstrated in several benchmark problems in two and three dimensions involving pure advection and curvature induced motion of the interface. The simplicity of the particle description is shown to be well suited for real time simulations of surfaces involving cutting and reconnection as in virtual surgery environments.

  19. Research on iris segmentation based on level set method with keeping circular%基于圆形保持水平集方法的虹膜分割研究

    Institute of Scientific and Technical Information of China (English)

    FAN Li-nan; OU Wen-jie; SUN Shen-shen; ZHAO Zhi-chao

    2014-01-01

    Iris segmentation is one of the most important part of iris recognition system, the good or bad of its segmentation will affect the accuracy in iris recognition, and which is one of the most reliable human biological identification for life. This paper pr%虹膜分割是虹膜识别系统中最重要的环节,其分割的好坏将影响虹膜识别的准确率,而虹膜识别也是最可靠的人体生物终身身份标志之一。因此,提出了基于水平集算法的虹膜分割算法。此算法是利用水平集隐式特点与圆形形状方程显式的特点相融合确保了演化曲线在演化过程中仍保持圆形,利用其思想分割内边缘。引入自适应面积项到形状约束的CV模型中用来约束外边缘。实验结果表明,尽管眼睛睁开有限、眼镜和睫毛及眼睑等遮挡以及成像设备形成图像的角度等问题,此模型仍能取得很好的分割效果。选用区域相互重叠度——DICE作为分割算法的评价指标,由实

  20. A NEW DEFORMABLE MODEL USING LEVEL SETS FOR SHAPE SEGMENTALTION

    Institute of Scientific and Technical Information of China (English)

    He Ning; Zhang Peng; Lu Ke

    2009-01-01

    In this paper,we present a new deformable model for shape segmentation,which makes two modifications to the original level set implementation of deformable models.The modifications are motivated by difficulties that we have encountered in applying deformable models to segmentation of medical images.The level set algorithm has some advantages over the classical snake deformable models.However,it could develop large gaps in the boundary and holes within the objects.Such boundary gaps and holes of objects can cause inaccurate segmentation that requires manual correction.The proposed method in this paper possesses an inherent property to detect gaps and holes within the object with a single initial contour and also does not require specific initialization.The first modification is to replace the edge detector by some area constraint,and the second modification utilizes weighted length constraint to regularize the curve under evolution.The proposed method has been applied to both synthetic and real images with promising results.

  1. Subcortical brain segmentation of two dimensional T1-weighted data sets with FMRIB's Integrated Registration and Segmentation Tool (FIRST

    Directory of Open Access Journals (Sweden)

    Michael Amann

    2015-01-01

    Full Text Available Brain atrophy has been identified as an important contributing factor to the development of disability in multiple sclerosis (MS. In this respect, more and more interest is focussing on the role of deep grey matter (DGM areas. Novel data analysis pipelines are available for the automatic segmentation of DGM using three-dimensional (3D MRI data. However, in clinical trials, often no such high-resolution data are acquired and hence no conclusions regarding the impact of new treatments on DGM atrophy were possible so far. In this work, we used FMRIB's Integrated Registration and Segmentation Tool (FIRST to evaluate the possibility of segmenting DGM structures using standard two-dimensional (2D T1-weighted MRI. In a cohort of 70 MS patients, both 2D and 3D T1-weighted data were acquired. The thalamus, putamen, pallidum, nucleus accumbens, and caudate nucleus were bilaterally segmented using FIRST. Volumes were calculated for each structure and for the sum of basal ganglia (BG as well as for the total DGM. The accuracy and reliability of the 2D data segmentation were compared with the respective results of 3D segmentations using volume difference, volume overlap and intra-class correlation coefficients (ICCs. The mean differences for the individual substructures were between 1.3% (putamen and −25.2% (nucleus accumbens. The respective values for the BG were −2.7% and for DGM 1.3%. Mean volume overlap was between 89.1% (thalamus and 61.5% (nucleus accumbens; BG: 84.1%; DGM: 86.3%. Regarding ICC, all structures showed good agreement with the exception of the nucleus accumbens. The results of the segmentation were additionally validated through expert manual delineation of the caudate nucleus and putamen in a subset of the 3D data. In conclusion, we demonstrate that subcortical segmentation of 2D data are feasible using FIRST. The larger subcortical GM structures can be segmented with high consistency. This forms the basis for the application of

  2. Accurate segmentation of leukocyte in blood cell images using Atanassov's intuitionistic fuzzy and interval Type II fuzzy set theory.

    Science.gov (United States)

    Chaira, Tamalika

    2014-06-01

    In this paper automatic leukocyte segmentation in pathological blood cell images is proposed using intuitionistic fuzzy and interval Type II fuzzy set theory. This is done to count different types of leukocytes for disease detection. Also, the segmentation should be accurate so that the shape of the leukocytes is preserved. So, intuitionistic fuzzy set and interval Type II fuzzy set that consider either more number of uncertainties or a different type of uncertainty as compared to fuzzy set theory are used in this work. As the images are considered fuzzy due to imprecise gray levels, advanced fuzzy set theories may be expected to give better result. A modified Cauchy distribution is used to find the membership function. In intuitionistic fuzzy method, non-membership values are obtained using Yager's intuitionistic fuzzy generator. Optimal threshold is obtained by minimizing intuitionistic fuzzy divergence. In interval type II fuzzy set, a new membership function is generated that takes into account the two levels in Type II fuzzy set using probabilistic T co norm. Optimal threshold is selected by minimizing a proposed Type II fuzzy divergence. Though fuzzy techniques were applied earlier but these methods failed to threshold multiple leukocytes in images. Experimental results show that both interval Type II fuzzy and intuitionistic fuzzy methods perform better than the existing non-fuzzy/fuzzy methods but interval Type II fuzzy thresholding method performs little bit better than intuitionistic fuzzy method. Segmented leukocytes in the proposed interval Type II fuzzy method are observed to be distinct and clear.

  3. Automated ventricular systems segmentation in brain CT images by combining low-level segmentation and high-level template matching

    Directory of Open Access Journals (Sweden)

    Ward Kevin R

    2009-11-01

    Full Text Available Abstract Background Accurate analysis of CT brain scans is vital for diagnosis and treatment of Traumatic Brain Injuries (TBI. Automatic processing of these CT brain scans could speed up the decision making process, lower the cost of healthcare, and reduce the chance of human error. In this paper, we focus on automatic processing of CT brain images to segment and identify the ventricular systems. The segmentation of ventricles provides quantitative measures on the changes of ventricles in the brain that form vital diagnosis information. Methods First all CT slices are aligned by detecting the ideal midlines in all images. The initial estimation of the ideal midline of the brain is found based on skull symmetry and then the initial estimate is further refined using detected anatomical features. Then a two-step method is used for ventricle segmentation. First a low-level segmentation on each pixel is applied on the CT images. For this step, both Iterated Conditional Mode (ICM and Maximum A Posteriori Spatial Probability (MASP are evaluated and compared. The second step applies template matching algorithm to identify objects in the initial low-level segmentation as ventricles. Experiments for ventricle segmentation are conducted using a relatively large CT dataset containing mild and severe TBI cases. Results Experiments show that the acceptable rate of the ideal midline detection is over 95%. Two measurements are defined to evaluate ventricle recognition results. The first measure is a sensitivity-like measure and the second is a false positive-like measure. For the first measurement, the rate is 100% indicating that all ventricles are identified in all slices. The false positives-like measurement is 8.59%. We also point out the similarities and differences between ICM and MASP algorithms through both mathematically relationships and segmentation results on CT images. Conclusion The experiments show the reliability of the proposed algorithms. The

  4. Probabilistic multiscale image segmentation: set-up and first results (Proceedings Only)

    Science.gov (United States)

    Vincken, Koen L.; Koster, Andre S.; Viergever, Max A.

    1992-09-01

    We have developed a method to segment two- and three-dimensional images using a multiscale (hyperstack) approach with probabilistic linking. A hyperstack is a voxel-based multiscale data structure containing linkages between voxels at different scales. The scale-space is constructed by repeatedly applying a discrete convolution with a Gaussian kernel to the original input image. Between these levels of increasing scale we establish child-parent linkages according to a linkage scheme that is based on affection. In the resulting tree-like data structure roots are formed to indicate the most plausible locations in scale-space where objects (of different sizes) are actually defined by a single voxel. Tracing the linkages back from every root to the ground level produces a segmented image. The present paper deals with probabilistic linking, i.e., a set-up in which a child voxel can be linked to more than one parent voxel. The output of the thus constructed hyperstack -- a list of object probabilities per voxel -- can be directly related to the opacities used in volume renderers.

  5. A two-level approach towards semantic colon segmentation: removing extra-colonic findings.

    Science.gov (United States)

    Lu, Le; Wolf, Matthias; Liang, Jianming; Dundar, Murat; Bi, Jinbo; Salganicoff, Marcos

    2009-01-01

    Computer aided detection (CAD) of colonic polyps in computed tomographic colonography has tremendously impacted colorectal cancer diagnosis using 3D medical imaging. It is a prerequisite for all CAD systems to extract the air-distended colon segments from 3D abdomen computed tomography scans. In this paper, we present a two-level statistical approach of first separating colon segments from small intestine, stomach and other extra-colonic parts by classification on a new geometric feature set; then evaluating the overall performance confidence using distance and geometry statistics over patients. The proposed method is fully automatic and validated using both the classification results in the first level and its numerical impacts on false positive reduction of extra-colonic findings in a CAD system. It shows superior performance than the state-of-art knowledge or anatomy based colon segmentation algorithms.

  6. Innovative group-decoupling design of a segment erector based on G F set theory

    Science.gov (United States)

    Guo, Wentao; Guo, Weizhong; Gao, Feng; Mo, Pinxi

    2013-03-01

    The segment erector is a key part of the shield machines for tunnel engineering. The available segment erectors are all of serial configuration which is suffering from the problems of low rigidity and accumulative motion errors. The current research mainly focuses on improving assembly accuracy and control performance of serial segment erectors. An innovative design method is proposed featuring motion group-decoupling, based on which a new type of segment erector is developed and investigated. Firstly, the segment installation manipulation is analyzed and decomposed into three motion groups that are decoupled. Then the type synthesis for the 4-DOF motion group is performed based on the general function( G F ) set theory and a new configuration of (1T⊕1R⊕1PS&3UPS) is attained according to the segment manipulation requirements. Consequently, the kinematic models are built and the reducibility and accuracy are analyzed. The dexterity is verified though numerical simulation and no singular points appear in the workspace. Finally, a positioning experiment is carried out by using the prototype developed in the lab that demonstrates a 13.1% improvement of positioning accuracy and the feasibility of the new segment erector. The presented group-decoupling design method is able to invent new type of hybrid segment erectors that avoid the accumulative motion error of erecting.

  7. Level Set Modeling of Transient Electromigration Grooving

    OpenAIRE

    Khenner, M.; Averbuch, A.; Israeli, M.; Nathan, M; Glickman, E.

    2000-01-01

    A numerical investigation of grain-boundary (GB) grooving by means of the Level Set (LS) method is carried out. GB grooving is emerging as a key element of electromigration drift in polycrystalline microelectronic interconnects, as evidenced by a number of recent studies. The purpose of the present study is to provide an efficient numerical simulation, allowing a parametric study of the effect of key physical parameters (GB and surface diffusivities, grain size, current density, etc) on the e...

  8. Adopting level set theory based algorithms to segment human ear

    OpenAIRE

    2013-01-01

    Human identification has always been a topic that interested researchers around the world. Biometric methods are found to be more effective and much easier for the users than the traditional identification methods like keys, smart cards and passwords. Unlike with the traditional methods, with biometric methods the data acquisition is most of the times passive, which means the users do not take active part in data acquisition. Data acquisition can be performed using cameras, scanners or sensor...

  9. Segmentation of hand radiographs by using multi-level connected active appearance models

    Science.gov (United States)

    Kauffman, Joost A.; Slump, Cornelis H.; Bernelot Moens, Hein J.

    2005-04-01

    Robust and accurate segmentation methods are important for the computerized evaluation of medical images. For treatment of rheumatoid arthritis, joint damage assessment in radiographs of hands is frequently used for monitoring disease progression. Current clinical scoring methods are based on visual measurements that are time-consuming and subject to intra and inter-reader variance. A solution may be found in the development of partially automated assessment procedures. This requires reliable segmentation algorithms. Our work demonstrates a segmentation method based on multiple connected active appearance models (AAM) with multiple search steps using different quality levels. The quality level can be regulated by setting the image resolution and the number of landmarks in the AAMs. We performed experiments using two models of different quality levels for shape and texture information. Both models included AAMs for the carpal region, the metacarpals, and all phalanges. By starting an iterative search with the faster, low-quality model, we were able to determine the initial parameters of the second, high-quality model. After the second search, the results showed successful segmentation for 22 of 30 test images. For these images, 70% of the landmarks were found within 1.3 mm difference from manual placement by an expert. The multi-level search approach resulted in a reduction of 50% in calculation time compared to a search using a single model. Results are expected to improve when the model is refined by increasing the number of training examples and the resolution of the models.

  10. Applying rough sets in word segmentation disambiguation based on maximum entropy model

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    To solve the complicated feature extraction and long distance dependency problem in Word Segmentation Disambiguation ( WSD), this paper proposes to apply rough sets in WSD based on the Maximum Entropy model. Firstly, rough set theory is applied to extract the complicated features and long distance features, even from noise or inconsistent corpus. Secondly, these features are added into the Maximum Entropy model, and consequently, the feature weights can be assigned according to the performance of the whole disambiguation model. Finally, the semantic lexicon is adopted to build class-based rough set features to overcome data sparseness. The experiment indicated that our method performed better than previous models, which got top rank in WSD in 863 Evaluation in 2003. This system ranked first and second respectively in MSR and PKU open test in the Second International Chinese Word Segmentation Bakeoff held in 2005.

  11. Candidate Smoke Region Segmentation of Fire Video Based on Rough Set Theory

    Directory of Open Access Journals (Sweden)

    Yaqin Zhao

    2015-01-01

    Full Text Available Candidate smoke region segmentation is the key link of smoke video detection; an effective and prompt method of candidate smoke region segmentation plays a significant role in a smoke recognition system. However, the interference of heavy fog and smoke-color moving objects greatly degrades the recognition accuracy. In this paper, a novel method of candidate smoke region segmentation based on rough set theory is presented. First, Kalman filtering is used to update video background in order to exclude the interference of static smoke-color objects, such as blue sky. Second, in RGB color space smoke regions are segmented by defining the upper approximation, lower approximation, and roughness of smoke-color distribution. Finally, in HSV color space small smoke regions are merged by the definition of equivalence relation so as to distinguish smoke images from heavy fog images in terms of V component value variety from center to edge of smoke region. The experimental results on smoke region segmentation demonstrated the effectiveness and usefulness of the proposed scheme.

  12. A Rough Set Bounded Spatially Constrained Asymmetric Gaussian Mixture Model for Image Segmentation.

    Science.gov (United States)

    Ji, Zexuan; Huang, Yubo; Sun, Quansen; Cao, Guo; Zheng, Yuhui

    2017-01-01

    Accurate image segmentation is an important issue in image processing, where Gaussian mixture models play an important part and have been proven effective. However, most Gaussian mixture model (GMM) based methods suffer from one or more limitations, such as limited noise robustness, over-smoothness for segmentations, and lack of flexibility to fit data. In order to address these issues, in this paper, we propose a rough set bounded asymmetric Gaussian mixture model with spatial constraint for image segmentation. First, based on our previous work where each cluster is characterized by three automatically determined rough-fuzzy regions, we partition the target image into three rough regions with two adaptively computed thresholds. Second, a new bounded indicator function is proposed to determine the bounded support regions of the observed data. The bounded indicator and posterior probability of a pixel that belongs to each sub-region is estimated with respect to the rough region where the pixel lies. Third, to further reduce over-smoothness for segmentations, two novel prior factors are proposed that incorporate the spatial information among neighborhood pixels, which are constructed based on the prior and posterior probabilities of the within- and between-clusters, and considers the spatial direction. We compare our algorithm to state-of-the-art segmentation approaches in both synthetic and real images to demonstrate the superior performance of the proposed algorithm.

  13. Consumer segmentation based on the level of environmental responsibility

    OpenAIRE

    Marija Ham

    2009-01-01

    Doubtless, there is an environmentally responsible segment of consumers in the market. However, with an increasing number of suppliers entering the green market, it is no longer sufficient to be aware of this fact. What is needed now are complex strategies of segmentation, targeting and positioning. The aim of this paper was to provide a theoretical framework for understanding the key concepts related to the green consumer segment and to help create a clearer picture of Croatia’s green consum...

  14. Distance regularized level set evolution in magnetic resonance image segmention based on bi-dimensional ensemble empirical mo de decomp osition%基于二维集合经验模式分解的距离正则化水平集磁共振图像分割∗

    Institute of Scientific and Technical Information of China (English)

    范虹; 韦文瑾; 朱艳春

    2016-01-01

    针对现有磁共振(MR)图像分割算法大多直接在原图像上进行处理,分割效果受噪声影响较大的问题,本文引入二维集合经验模式分解(BEEMD)算法,提高距离正则化水平集(DRLSE)方法对MR图像的分割精度。算法中首先使用 BEEMD将待分割MR图像分解为多个二维固有模式函数(BIMF),通过对各BIMF赋予不同加权系数重构待分割图像,从而增强分割目标;然后在DRLSE的边界指示函数中添加部分BIMF分量,恢复因高斯平滑被模糊的目标轮廓,并使用DRLSE方法对重构图像进行分割。通过对仿真图像和临床MR图像分割验证,表明本文算法具有较高的分割精度和鲁棒性,能有效实现对临床MR图像的分割。%Original image is directly processed by the existing image segmentation algorithms, which is easily affected by noise. A bi-dimensional ensemble empirical mode decomposition (BEEMD) method is introduced to improve the accuracy of MR image segmentation by distance regularized level set (DRLSE) method. The BEEMD method is the extension of one-dimensional noise assisted data analysis from ensemble empirical mode decomposition (EEMD). The key points of BEEMD are as follows. four-neighborhood optimization is used to find extermum; three-spline interpolation is used to obtain the envelope;amplitude standard of added white noise is restricted;a certain time of integration is used to avoid modality aliasing problem. The main steps of the proposed method are as follows. Firstly, the MR image is decomposed into a number of two-dimensional intrinsic mode functions (BIMF) by BEEMD method;different weighting coefficients are endued to BIMF for image reconstruction to enhance the segmentation target. Secondly, part of BIMF components are added into edge indicator function of DRLSE to recover the blurring boundary caused by Gauss smooth operation. Then DRLSE is used to segment the reconstructed MR image. High accuracy and

  15. An automatic fractional coefficient setting method of FODPSO for hyperspectral image segmentation

    Science.gov (United States)

    Xie, Weiying; Li, Yunsong

    2015-05-01

    In this paper, an automatic fractional coefficient setting method of fractional-order Darwinian particle swarm optimization (FODPSO) is proposed for hyperspectral image segmentation. The spectrum has been already taken into consideration by integrating various types of band selection algorithms, firstly. We provide a short overview of the hyperspectral image to select an appropriate set of bands by combining supervised, semi-supervised and unsupervised band selection algorithms. Some approaches are not limited in regards to their spectral dimension, but are limited with respect to their spatial dimension owing to low spatial resolution. The addition of spatial information will be focused on improving the performance of hyperspectral image segmentation for later fusion or classification. Many researchers have advocated that a large fractional coefficient should be in the exploration state while a small fractional coefficient should be in the exploitation, which does not mean the coefficient purely decrease with time. Due to such reasons, we propose an adaptive FODPSO by setting the fractional coefficient adaptively for the application of final hyperspectral image segmentation. In fact, the paper introduces an evolutionary factor to automatically control the fractional coefficient by using a sigmoid function. Therefore, fractional coefficient with large value will benefit the global search in the exploration state. Conversely, when the fractional coefficient has a small value, the exploitation state is detected. Hence, it can avoid optimization process get trapped into the local optima. Ultimately, the experimental segmentation results prove the validity and efficiency of our proposed automatic fractional coefficient setting method of FODPSO compared with traditional PSO, DPSO and FODPSO.

  16. A Benchmark Data Set to Evaluate the Illumination Robustness of Image Processing Algorithms for Object Segmentation and Classification.

    Science.gov (United States)

    Khan, Arif Ul Maula; Mikut, Ralf; Reischl, Markus

    2015-01-01

    Developers of image processing routines rely on benchmark data sets to give qualitative comparisons of new image analysis algorithms and pipelines. Such data sets need to include artifacts in order to occlude and distort the required information to be extracted from an image. Robustness, the quality of an algorithm related to the amount of distortion is often important. However, using available benchmark data sets an evaluation of illumination robustness is difficult or even not possible due to missing ground truth data about object margins and classes and missing information about the distortion. We present a new framework for robustness evaluation. The key aspect is an image benchmark containing 9 object classes and the required ground truth for segmentation and classification. Varying levels of shading and background noise are integrated to distort the data set. To quantify the illumination robustness, we provide measures for image quality, segmentation and classification success and robustness. We set a high value on giving users easy access to the new benchmark, therefore, all routines are provided within a software package, but can as well easily be replaced to emphasize other aspects.

  17. Rough Sets and Stomped Normal Distribution for Simultaneous Segmentation and Bias Field Correction in Brain MR Images.

    Science.gov (United States)

    Banerjee, Abhirup; Maji, Pradipta

    2015-12-01

    The segmentation of brain MR images into different tissue classes is an important task for automatic image analysis technique, particularly due to the presence of intensity inhomogeneity artifact in MR images. In this regard, this paper presents a novel approach for simultaneous segmentation and bias field correction in brain MR images. It integrates judiciously the concept of rough sets and the merit of a novel probability distribution, called stomped normal (SN) distribution. The intensity distribution of a tissue class is represented by SN distribution, where each tissue class consists of a crisp lower approximation and a probabilistic boundary region. The intensity distribution of brain MR image is modeled as a mixture of finite number of SN distributions and one uniform distribution. The proposed method incorporates both the expectation-maximization and hidden Markov random field frameworks to provide an accurate and robust segmentation. The performance of the proposed approach, along with a comparison with related methods, is demonstrated on a set of synthetic and real brain MR images for different bias fields and noise levels.

  18. Consumer segmentation based on the level of environmental responsibility

    Directory of Open Access Journals (Sweden)

    Marija Ham

    2009-12-01

    Full Text Available Doubtless, there is an environmentally responsible segment of consumers in the market. However, with an increasing number of suppliers entering the green market, it is no longer sufficient to be aware of this fact. What is needed now are complex strategies of segmentation, targeting and positioning. The aim of this paper was to provide a theoretical framework for understanding the key concepts related to the green consumer segment and to help create a clearer picture of Croatia’s green consumers by gathering secondary data from the available literature, previous research and primary data from own research. Primary research was conducted by means of a structured questionnaire on a sample of 552 respondents. The questionnaire was divided into three parts, each measuring, respectively, attitudes, knowledge and activities undertaken. After the segmentation (three segments: green, neutral and brown consumers, a chi-square test was used in an attempt to prove statistically significant differences when comparing the given segment structure with the respondents’ demographic characteristics. The results of this research describe the average green consumer in the Republic of Croatia as a person who is 55 and older, with higher or university education, who is married, who responds to the advertising claims about eco-friendliness of products and is influenced by those claims, who occasionally or frequently makes purchasing decisions and shows readiness to pay a 20 percent mark-up for an environmentally friendly product.

  19. Two-level evaluation on sensor interoperability of features in fingerprint image segmentation.

    Science.gov (United States)

    Yang, Gongping; Li, Ying; Yin, Yilong; Li, Ya-Shuo

    2012-01-01

    Features used in fingerprint segmentation significantly affect the segmentation performance. Various features exhibit different discriminating abilities on fingerprint images derived from different sensors. One feature which has better discriminating ability on images derived from a certain sensor may not adapt to segment images derived from other sensors. This degrades the segmentation performance. This paper empirically analyzes the sensor interoperability problem of segmentation feature, which refers to the feature's ability to adapt to the raw fingerprints captured by different sensors. To address this issue, this paper presents a two-level feature evaluation method, including the first level feature evaluation based on segmentation error rate and the second level feature evaluation based on decision tree. The proposed method is performed on a number of fingerprint databases which are obtained from various sensors. Experimental results show that the proposed method can effectively evaluate the sensor interoperability of features, and the features with good evaluation results acquire better segmentation accuracies of images originating from different sensors.

  20. Improved Segmented All-Electron Relativistically Contracted Basis Sets for the Lanthanides.

    Science.gov (United States)

    Aravena, Daniel; Neese, Frank; Pantazis, Dimitrios A

    2016-03-08

    Improved versions of the segmented all-electron relativistically contracted (SARC) basis sets for the lanthanides are presented. The second-generation SARC2 basis sets maintain efficient construction of their predecessors and their individual adaptation to the DKH2 and ZORA Hamiltonians, but feature exponents optimized with a completely new orbital shape fitting procedure and a slightly expanded f space that results in sizable improvement in CASSCF energies and in significantly more accurate prediction of spin-orbit coupling parameters. Additionally, an extended set of polarization/correlation functions is constructed that is appropriate for multireference correlated calculations and new auxiliary basis sets for use in resolution-of-identity (density-fitting) approximations in combination with both DFT and wave function based treatments. Thus, the SARC2 basis sets extend the applicability of the first-generation DFT-oriented basis sets to routine all-electron wave function-based treatments of lanthanide complexes. The new basis sets are benchmarked with respect to excitation energies, radial distribution functions, optimized geometries, orbital eigenvalues, ionization potentials, and spin-orbit coupling parameters of lanthanide systems and are shown to be suitable for the description of magnetic and spectroscopic properties using both DFT and multireference wave function-based methods.

  1. Neighborhood Supported Model Level Fuzzy Aggregation for Moving Object Segmentation.

    Science.gov (United States)

    Chiranjeevi, Pojala; Sengupta, Somnath

    2014-02-01

    We propose a new algorithm for moving object detection in the presence of challenging dynamic background conditions. We use a set of fuzzy aggregated multifeature similarity measures applied on multiple models corresponding to multimodal backgrounds. The algorithm is enriched with a neighborhood-supported model initialization strategy for faster convergence. A model level fuzzy aggregation measure driven background model maintenance ensures more robustness. Similarity functions are evaluated between the corresponding elements of the current feature vector and the model feature vectors. Concepts from Sugeno and Choquet integrals are incorporated in our algorithm to compute fuzzy similarities from the ordered similarity function values for each model. Model updating and the foreground/background classification decision is based on the set of fuzzy integrals. Our proposed algorithm is shown to outperform other multi-model background subtraction algorithms. The proposed approach completely avoids explicit offline training to initialize background model and can be initialized with moving objects also. The feature space uses a combination of intensity and statistical texture features for better object localization and robustness. Our qualitative and quantitative studies illustrate the mitigation of varieties of challenging situations by our approach.

  2. Setting the stage for master's level success

    Science.gov (United States)

    Roberts, Donna

    Comprehensive reading, writing, research, and study skills play a critical role in a graduate student's success and ability to contribute to a field of study effectively. The literature indicated a need to support graduate student success in the areas of mentoring, navigation, as well as research and writing. The purpose of this two-phased mixed methods explanatory study was to examine factors that characterize student success at the Master's level in the fields of education, sociology and social work. The study was grounded in a transformational learning framework which focused on three levels of learning: technical knowledge, practical or communicative knowledge, and emancipatory knowledge. The study included two data collection points. Phase one consisted of a Master's Level Success questionnaire that was sent via Qualtrics to graduate level students at three colleges and universities in the Central Valley of California: a California State University campus, a University of California campus, and a private college campus. The results of the chi-square indicated that seven questionnaire items were significant with p values less than .05. Phase two in the data collection included semi-structured interview questions that resulted in three themes emerged using Dedoose software: (1) the need for more language and writing support at the Master's level, (2) the need for mentoring, especially for second-language learners, and (3) utilizing the strong influence of faculty in student success. It is recommended that institutions continually assess and strengthen their programs to meet the full range of learners and to support students to degree completion.

  3. An efficient, scalable, and adaptable framework for solving generic systems of level-set PDEs

    Directory of Open Access Journals (Sweden)

    Kishore R. Mosaliganti

    2013-12-01

    Full Text Available In the last decade, level-set methods have been actively developed for applications in image registration, segmentation, tracking, and reconstruction. However, the development of a wide variety of level-set PDEs and their numerical discretization schemes, coupled with hybrid combinations of PDE terms, stopping criteria, and reinitialization strategies, has created a software logistics problem. In the absence of an integrative design, current toolkits support only specific types of level-set implementations which restrict future algorithm development since extensions require significant code duplication and effort. In the new NIH/NLM Insight Toolkit (ITK v4 architecture, we implemented a level-set software design that is flexible to different numerical (continuous, discrete, and sparse and grid representations (point, mesh, and image-based. Given that a generic PDE is a summation of different terms, we used a set of linked containers to which level-set terms can be added or deleted at any point in the evolution process. This container-based approach allows the user to explore and customize terms in the level-set equation at compile-time in a flexible manner. The framework is optimized so that repeated computations of common intensity functions (e.g. gradient and Hessians across multiple terms is eliminated. The framework further enables the evolution of multiple level-sets for multi-object segmentation and processing of large datasets. For doing so, we restrict level-set domains to subsets of the image domain and use multithreading strategies to process groups of subdomains or level-set functions. Users can also select from a variety of reinitialization policies and stopping criteria. Finally, we developed a visualization framework that shows the evolution of a level-set in real-time to help guide algorithm development and parameter optimization. We demonstrate the power of our new framework using confocal microscopy images of cells in a

  4. A fast SVM training algorithm based on the set segmentation and k-means clustering

    Institute of Scientific and Technical Information of China (English)

    YANG Xiaowei; LIN Daying; HAO Zhifeng; LIANG Yanchun; LIU Guirong; HAN Xu

    2003-01-01

    At present, studies on training algorithms for support vector machines (SVM) are important issues in the field of machine learning. It is a challenging task to improve the efficiency of the algorithm without reducing the generalization performance of SVM. To face this challenge, a new SVM training algorithm based on the set segmentation and k-means clustering is presented in this paper. The new idea is to divide all the original training data into many subsets, followed by clustering each subset using k-means clustering and finally train SVM using the new data set obtained from clustering centroids. Considering that the decomposition algorithm such as SVMlight is one of the major methods for solving support vector machines, the SVMlight is used in our experiments. Simulations on different types of problems show that the proposed method can solve efficiently not only large linear classification problems but also large nonlinear ones.

  5. Memory based active contour algorithm using pixel-level classified images for colon crypt segmentation.

    Science.gov (United States)

    Cohen, Assaf; Rivlin, Ehud; Shimshoni, Ilan; Sabo, Edmond

    2015-07-01

    In this paper, we introduce a novel method for detection and segmentation of crypts in colon biopsies. Most of the approaches proposed in the literature try to segment the crypts using only the biopsy image without understanding the meaning of each pixel. The proposed method differs in that we segment the crypts using an automatically generated pixel-level classification image of the original biopsy image and handle the artifacts due to the sectioning process and variance in color, shape and size of the crypts. The biopsy image pixels are classified to nuclei, immune system, lumen, cytoplasm, stroma and goblet cells. The crypts are then segmented using a novel active contour approach, where the external force is determined by the semantics of each pixel and the model of the crypt. The active contour is applied for every lumen candidate detected using the pixel-level classification. Finally, a false positive crypt elimination process is performed to remove segmentation errors. This is done by measuring their adherence to the crypt model using the pixel level classification results. The method was tested on 54 biopsy images containing 4944 healthy and 2236 cancerous crypts, resulting in 87% detection of the crypts with 9% of false positive segments (segments that do not represent a crypt). The segmentation accuracy of the true positive segments is 96%.

  6. Confidence sets for optimal factor levels of a response surface.

    Science.gov (United States)

    Wan, Fang; Liu, Wei; Bretz, Frank; Han, Yang

    2016-12-01

    Construction of confidence sets for the optimal factor levels is an important topic in response surfaces methodology. In Wan et al. (2015), an exact (1-α) confidence set has been provided for a maximum or minimum point (i.e., an optimal factor level) of a univariate polynomial function in a given interval. In this article, the method has been extended to construct an exact (1-α) confidence set for the optimal factor levels of response surfaces. The construction method is readily applied to many parametric and semiparametric regression models involving a quadratic function. A conservative confidence set has been provided as an intermediate step in the construction of the exact confidence set. Two examples are given to illustrate the application of the confidence sets. The comparison between confidence sets indicates that our exact confidence set is better than the only other confidence set available in the statistical literature that guarantees the (1-α) confidence level. © 2016, The International Biometric Society.

  7. Fusion set selection with surrogate metric in multi-atlas based image segmentation

    Science.gov (United States)

    Zhao, Tingting; Ruan, Dan

    2016-02-01

    Multi-atlas based image segmentation sees unprecedented opportunities but also demanding challenges in the big data era. Relevant atlas selection before label fusion plays a crucial role in reducing potential performance loss from heterogeneous data quality and high computation cost from extensive data. This paper starts with investigating the image similarity metric (termed ‘surrogate’), an alternative to the inaccessible geometric agreement metric (termed ‘oracle’) in atlas relevance assessment, and probes into the problem of how to select the ‘most-relevant’ atlases and how many such atlases to incorporate. We propose an inference model to relate the surrogates and the oracle geometric agreement metrics. Based on this model, we quantify the behavior of the surrogates in mimicking oracle metrics for atlas relevance ordering. Finally, analytical insights on the choice of fusion set size are presented from a probabilistic perspective, with the integrated goal of including the most relevant atlases and excluding the irrelevant ones. Empirical evidence and performance assessment are provided based on prostate and corpus callosum segmentation.

  8. Multi-emissivity setting in thermal imaging based on visible-light image segmentation

    Directory of Open Access Journals (Sweden)

    Cui Dai-jun

    2013-07-01

    Full Text Available Emissivity is an accuracy influencing factor during infrared temperature measurement which focusing on regular geometry in laboratory under the condition of single emissivity. But in practical application, the target is often irregular with multi-emissivity,, and if following "idealized" method in laboratory, it will lead to inevitable error. This paper presents a method for a complex target object with the collection of multiple emissivities in infrared image after measurement. Both visible and infrared images were collected in the same field of view at the same time using binocular video to segment target regionally through visible image. The emission rate in corresponding region was set based on regional growing algorithm. Heat conduction equation was used as a reference to smooth the boundary area. After testing image evaluation parameters accordingly, results obtained via this infrared temperature measurement method are closer to the true value and precise compared with conventional ones judged from objective measurements.

  9. Optimal production policy for multi-product with inventory-level-dependent demand in segmented market

    Directory of Open Access Journals (Sweden)

    Singh Yogender

    2013-01-01

    Full Text Available Market segmentation has emerged as the primary means by which firms achieve optimal production policy. In this paper, we use market segmentation approach in multi-product inventory system with inventory-level-dependent demand. The objective is to make use of optimal control theory to solve the inventory-production problem and develop an optimal production policy that minimizes the total cost associated with inventory and production rate in segmented market. First, we consider a single production and inventory problem with multi-destination demand that vary from segment to segment. Further, we describe a single source production and multi destination inventory and demand problem under the assumption that firm may choose independently the inventory directed to each segment. The optimal control is applied to study and solve the proposed problem.

  10. Multi-level Threshold Image Segmentation Based on PSNR using Artificial Bee Colony Algorithm

    Directory of Open Access Journals (Sweden)

    Cao Yun-Fei

    2012-01-01

    Full Text Available Image segmentation is still a crucial problem in image processing. It hasn yet been solved very well. In this study, we propose a novel multi-level thresholding image segmentation method based on PSNR using artificial bee colony algorithm (ABCA. PSNR is considered as an objective function of ABCA. The multi-level thresholds (t*1, t*2 ,...., t*n-1, t*n are those maximizing the PSNR. We compare entropy and PSNR in segmenting gray-level images. The experiments results demonstrate proposed method is effective and efficient.

  11. Complexity of genome evolution by segmental rearrangement in Brassica rapa revealed by sequence-level analysis

    Directory of Open Access Journals (Sweden)

    Paterson Andrew H

    2009-11-01

    Full Text Available Abstract Background The Brassica species, related to Arabidopsis thaliana, include an important group of crops and represent an excellent system for studying the evolutionary consequences of polyploidy. Previous studies have led to a proposed structure for an ancestral karyotype and models for the evolution of the B. rapa genome by triplication and segmental rearrangement, but these have not been validated at the sequence level. Results We developed computational tools to analyse the public collection of B. rapa BAC end sequence, in order to identify candidates for representing collinearity discontinuities between the genomes of B. rapa and A. thaliana. For each putative discontinuity, one of the BACs was sequenced and analysed for collinearity with the genome of A. thaliana. Additional BAC clones were identified and sequenced as part of ongoing efforts to sequence four chromosomes of B. rapa. Strikingly few of the 19 inter-chromosomal rearrangements corresponded to the set of collinearity discontinuities anticipated on the basis of previous studies. Our analyses revealed numerous instances of newly detected collinearity blocks. For B. rapa linkage group A8, we were able to develop a model for the derivation of the chromosome from the ancestral karyotype. We were also able to identify a rearrangement event in the ancestor of B. rapa that was not shared with the ancestor of A. thaliana, and is represented in triplicate in the B. rapa genome. In addition to inter-chromosomal rearrangements, we identified and analysed 32 BACs containing the end points of segmental inversion events. Conclusion Our results show that previous studies of segmental collinearity between the A. thaliana, Brassica and ancestral karyotype genomes, although very useful, represent over-simplifications of their true relationships. The presence of numerous cryptic collinear genome segments and the frequent occurrence of segmental inversions mean that inference of the positions

  12. Automated Brain Tumor Segmentation on MR Images Based on Neutrosophic Set Approach

    OpenAIRE

    Mohan J; Krishnaveni V; Yanhui Huo

    2015-01-01

    Brain tumor segmentation for MR images is a difficult and challenging task due to variation in type, size, location and shape of tumors. This paper presents an efficient and fully automatic brain tumor segmentation technique. This proposed technique includes non local preprocessing, fuzzy intensification to enhance the quality of the MR images, k - means clustering method for brain tumor segmentation.

  13. Iris segmentation using an edge detector based on fuzzy sets theory and cellular learning automata.

    Science.gov (United States)

    Ghanizadeh, Afshin; Abarghouei, Amir Atapour; Sinaie, Saman; Saad, Puteh; Shamsuddin, Siti Mariyam

    2011-07-01

    Iris-based biometric systems identify individuals based on the characteristics of their iris, since they are proven to remain unique for a long time. An iris recognition system includes four phases, the most important of which is preprocessing in which the iris segmentation is performed. The accuracy of an iris biometric system critically depends on the segmentation system. In this paper, an iris segmentation system using edge detection techniques and Hough transforms is presented. The newly proposed edge detection system enhances the performance of the segmentation in a way that it performs much more efficiently than the other conventional iris segmentation methods.

  14. A hybrid method for pancreas extraction from CT image based on level set methods.

    Science.gov (United States)

    Jiang, Huiyan; Tan, Hanqing; Fujita, Hiroshi

    2013-01-01

    This paper proposes a novel semiautomatic method to extract the pancreas from abdominal CT images. Traditional level set and region growing methods that request locating initial contour near the final boundary of object have problem of leakage to nearby tissues of pancreas region. The proposed method consists of a customized fast-marching level set method which generates an optimal initial pancreas region to solve the problem that the level set method is sensitive to the initial contour location and a modified distance regularized level set method which extracts accurate pancreas. The novelty in our method is the proper selection and combination of level set methods, furthermore an energy-decrement algorithm and an energy-tune algorithm are proposed to reduce the negative impact of bonding force caused by connected tissue whose intensity is similar with pancreas. As a result, our method overcomes the shortages of oversegmentation at weak boundary and can accurately extract pancreas from CT images. The proposed method is compared to other five state-of-the-art medical image segmentation methods based on a CT image dataset which contains abdominal images from 10 patients. The evaluated results demonstrate that our method outperforms other methods by achieving higher accuracy and making less false segmentation in pancreas extraction.

  15. Robust boundary detection of left ventricles on ultrasound images using ASM-level set method.

    Science.gov (United States)

    Zhang, Yaonan; Gao, Yuan; Li, Hong; Teng, Yueyang; Kang, Yan

    2015-01-01

    Level set method has been widely used in medical image analysis, but it has difficulties when being used in the segmentation of left ventricular (LV) boundaries on echocardiography images because the boundaries are not very distinguish, and the signal-to-noise ratio of echocardiography images is not very high. In this paper, we introduce the Active Shape Model (ASM) into the traditional level set method to enforce shape constraints. It improves the accuracy of boundary detection and makes the evolution more efficient. The experiments conducted on the real cardiac ultrasound image sequences show a positive and promising result.

  16. Identifying Heterogeneities in Subsurface Environment using the Level Set Method

    Energy Technology Data Exchange (ETDEWEB)

    Lei, Hongzhuan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Lu, Zhiming [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Vesselinov, Velimir Valentinov [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-08-25

    These are slides from a presentation on identifying heterogeneities in subsurface environment using the level set method. The slides start with the motivation, then explain Level Set Method (LSM), the algorithms, some examples are given, and finally future work is explained.

  17. Two-Level Evaluation on Sensor Interoperability of Features in Fingerprint Image Segmentation

    Directory of Open Access Journals (Sweden)

    Ya-Shuo Li

    2012-03-01

    Full Text Available Features used in fingerprint segmentation significantly affect the segmentation performance. Various features exhibit different discriminating abilities on fingerprint images derived from different sensors. One feature which has better discriminating ability on images derived from a certain sensor may not adapt to segment images derived from other sensors. This degrades the segmentation performance. This paper empirically analyzes the sensor interoperability problem of segmentation feature, which refers to the feature’s ability to adapt to the raw fingerprints captured by different sensors. To address this issue, this paper presents a two-level feature evaluation method, including the first level feature evaluation based on segmentation error rate and the second level feature evaluation based on decision tree. The proposed method is performed on a number of fingerprint databases which are obtained from various sensors. Experimental results show that the proposed method can effectively evaluate the sensor interoperability of features, and the features with good evaluation results acquire better segmentation accuracies of images originating from different sensors.

  18. A new level set model for multimaterial flows

    Energy Technology Data Exchange (ETDEWEB)

    Starinshak, David P. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Karni, Smadar [Univ. of Michigan, Ann Arbor, MI (United States). Dept. of Mathematics; Roe, Philip L. [Univ. of Michigan, Ann Arbor, MI (United States). Dept. of AerospaceEngineering

    2014-01-08

    We present a new level set model for representing multimaterial flows in multiple space dimensions. Instead of associating a level set function with a specific fluid material, the function is associated with a pair of materials and the interface that separates them. A voting algorithm collects sign information from all level sets and determines material designations. M(M ₋1)/2 level set functions might be needed to represent a general M-material configuration; problems of practical interest use far fewer functions, since not all pairs of materials share an interface. The new model is less prone to producing indeterminate material states, i.e. regions claimed by more than one material (overlaps) or no material at all (vacuums). It outperforms existing material-based level set models without the need for reinitialization schemes, thereby avoiding additional computational costs and preventing excessive numerical diffusion.

  19. A LEVEL SET METHOD FOR MICROSTRUCTURE DESIGN OF COMPOSITE MATERIALS

    Institute of Scientific and Technical Information of China (English)

    MeiYnlin; WangXiaoming

    2004-01-01

    Based on a level set model and the homogenization theory, an optimization algorithm for finding the optimal configuration of the microstructure with specified properties is proposed, which extends current research on the level set method for structure topology optimization. The method proposed employs a level set model to implicitly describe the material interfaces of the microstructure and a Hamilton-Jacobi equation to continuously evolve the material interfaces until an optimal design is achieved. Meanwhile, the moving velocities of level set are obtained by conducting sensitivity analysis and gradient projection. Besides, how to handle the violated constraints is also discussed in the level set method for topological optimization, and a return-mapping algorithm is constructed. Numerical examples show that the method exhibits outstanding flexibility of handling topological changes and fidelity of material interface representation as compared with other conventional methods in literatures.

  20. Influence of segmenting fluids on efficiency, crossing point and fluorescence level in real time quantitative PCR.

    Science.gov (United States)

    Walsh, E J; King, C; Grimes, R; Gonzalez, A

    2006-03-01

    The two-phase segmented flow approach to the processing and quantitative analysis of biological samples in microdevices offers significant advantages over the single-phase continuous flow methodology. Despite this, little is known about the compatibility of samples and reactants with segmenting fluids, although a number of investigators have reported reduced yield and inhibition of enzymatic reactions depending on the segmenting fluid employed. The current study addresses the compatibility of various segmenting fluids with real time quantitative PCR to understand the physicochemical requirements of this important reaction in biotechnology. The results demonstrate that creating a static segmenting fluid/PCR mix interface has a negligible impact on the reaction efficiency, crossing threshold and end fluorescence levels using a variety of segmenting fluids. The implication is then that the previously reported inhibitory effects are the result of the dynamic motion between the segmenting fluid and the sample in continuously flowing systems. The results presented here are a first step towards understanding the limitations of the segmented flow methodology, which are necessary to bring this approach into mainstream use.

  1. A fast level set method for reservoir simulation

    Energy Technology Data Exchange (ETDEWEB)

    Karlsen, K. Hvistendahl; Lie, K.-A.; Risebro, N.H.

    1999-10-01

    We present a level set method for reservoir simulation based on a fractional flow formulation of two-phase, incompressible, immiscible flow in two or three space dimensions. The method uses a fast marching level set approach and is therefore considerable faster than conventional finite difference methods. The level set approach compares favourably with a front tracking method as regards to both efficiency and accuracy but maintains the advantage of being able to handle changing topologies of the front structure. 8 figs., 1 tab., 32 refs.

  2. Volume Sculpting Using the Level-Set Method

    DEFF Research Database (Denmark)

    Bærentzen, Jakob Andreas; Christensen, Niels Jørgen

    2002-01-01

    In this paper, we propose the use of the Level--Set Method as the underlying technology of a volume sculpting system. The main motivation is that this leads to a very generic technique for deformation of volumetric solids. In addition, our method preserves a distance field volume representation....... A scaling window is used to adapt the Level--Set Method to local deformations and to allow the user to control the intensity of the tool. Level--Set based tools have been implemented in an interactive sculpting system, and we show sculptures created using the system....

  3. Parallel Computation of the Topology of Level Sets

    Energy Technology Data Exchange (ETDEWEB)

    Pascucci, V; Cole-McLaughlin, K

    2004-12-16

    This paper introduces two efficient algorithms that compute the Contour Tree of a 3D scalar field F and its augmented version with the Betti numbers of each isosurface. The Contour Tree is a fundamental data structure in scientific visualization that is used to preprocess the domain mesh to allow optimal computation of isosurfaces with minimal overhead storage. The Contour Tree can also be used to build user interfaces reporting the complete topological characterization of a scalar field, as shown in Figure 1. Data exploration time is reduced since the user understands the evolution of level set components with changing isovalue. The Augmented Contour Tree provides even more accurate information segmenting the range space of the scalar field in portion of invariant topology. The exploration time for a single isosurface is also improved since its genus is known in advance. Our first new algorithm augments any given Contour Tree with the Betti numbers of all possible corresponding isocontours in linear time with the size of the tree. Moreover we show how to extend the scheme introduced in [3] with the Betti number computation without increasing its complexity. Thus, we improve on the time complexity from our previous approach [10] from O(m log m) to O(n log n + m), where m is the number of cells and n is the number of vertices in the domain of F. Our second contribution is a new divide-and-conquer algorithm that computes the Augmented Contour Tree with improved efficiency. The approach computes the output Contour Tree by merging two intermediate Contour Trees and is independent of the interpolant. In this way we confine any knowledge regarding a specific interpolant to an independent function that computes the tree for a single cell. We have implemented this function for the trilinear interpolant and plan to replace it with higher order interpolants when needed. The time complexity is O(n + t log n), where t is the number of critical points of F. For the first time

  4. A set of Level 3 Basic Linear Algebra Subprograms

    Energy Technology Data Exchange (ETDEWEB)

    Dongarra, J.J. (Univ. of Tennessee, Knoxville, TN (United States) Oak Ridge National Lab., TN (United States)); Du Croz, J.; Hammarling, S. (Numerical Algorithms Group Ltd., Oxford (United Kingdom)); Duff, I. (Harwell Lab., Oxfordshire (United Kingdom))

    1990-03-01

    This paper describes a set of Level 3 Basic Linear Algebra Subprograms (Level 3 BLAS). The Level 3 BLAS are targeted at matrix-matrix operations, with the aim of providing more efficient, but portable, implementations of algorithms on high-performance computers, especially those with hierarchical memory and parallel processing capability.

  5. Magnification of label maps with a topology-preserving level-set method.

    Science.gov (United States)

    Trede, Dennis; Alexandrov, Theodore; Sagiv, Chen; Maass, Peter

    2012-09-01

    Image segmentation aims at partitioning an image into multiple segments. The application of this procedure produces a label map (also referred to as segmentation map) that classifies the pixels of the original image. In contrast to "natural" images, label maps are nominal-scale images, typically represented as integer-valued images. Nominal-scaled label maps can also appear as a representation of the raw data in areas, such as in geostatistics. In some applications, the original resolution of a label map does not suffice and a larger size map has to be generated. In this paper, we present a magnification algorithm for label maps and nominal images. The main property of our method is that it preserves the topology during the magnification process, which means that no isolated pixel vanishes. To the best of our knowledge, apart from nearest-neighbor interpolation, the problem of label map magnification has not previously been addressed in the literature. The main idea of the proposed method is to accomplish a boundary refinement by smoothing the regions' boundaries on a finer grid. The method relies on well known methods, namely, the fundamental operations of morphological image processing-erosion and dilation-and the level-set method. The level-set method is well suited for our purposes since it does not depend on a parametrization and it is numerically stable. The topological flexibility of the level-set method-often found to be an advantage in applications-is a drawback here, since the topology of the original label map should be preserved. However, using the so-called simple point criterion from digital topology, one can adapt the conventional level-set method so that the topology will not be modified throughout the magnification procedure.

  6. Mapping topographic structure in white matter pathways with level set trees.

    Directory of Open Access Journals (Sweden)

    Brian P Kent

    Full Text Available Fiber tractography on diffusion imaging data offers rich potential for describing white matter pathways in the human brain, but characterizing the spatial organization in these large and complex data sets remains a challenge. We show that level set trees--which provide a concise representation of the hierarchical mode structure of probability density functions--offer a statistically-principled framework for visualizing and analyzing topography in fiber streamlines. Using diffusion spectrum imaging data collected on neurologically healthy controls (N = 30, we mapped white matter pathways from the cortex into the striatum using a deterministic tractography algorithm that estimates fiber bundles as dimensionless streamlines. Level set trees were used for interactive exploration of patterns in the endpoint distributions of the mapped fiber pathways and an efficient segmentation of the pathways that had empirical accuracy comparable to standard nonparametric clustering techniques. We show that level set trees can also be generalized to model pseudo-density functions in order to analyze a broader array of data types, including entire fiber streamlines. Finally, resampling methods show the reliability of the level set tree as a descriptive measure of topographic structure, illustrating its potential as a statistical descriptor in brain imaging analysis. These results highlight the broad applicability of level set trees for visualizing and analyzing high-dimensional data like fiber tractography output.

  7. Construal level mind-sets moderate self- and social stereotyping.

    Science.gov (United States)

    McCrea, Sean M; Wieber, Frank; Myers, Andrea L

    2012-01-01

    Construal level theory suggests that events and objects can be represented at either a higher, more abstract level involving consideration of superordinate goals, desirability, global processing, and broad categorizations or a lower, more concrete level involving consideration of subordinate goals, feasibility, local processing, and narrow categorizations. Analogously, social targets (including the self) can be represented more broadly, as members of a group, or more narrowly, as individuals. Because abstract construals induce a similarity focus, they were predicted to increase the perceived fit between social targets and a salient social category. Accordingly, placing individuals into a more abstract construal mind-set via an unrelated task increased the activation and use of stereotypes of salient social groups, stereotype-consistent trait ratings of the self, group identification, and stereotype-consistent performance relative to more concrete construal mind-sets. Thus, nonsocial contextual influences (construal level mind-sets) affect stereotyping of self and others.

  8. Ventral midline blanching in the setting of segmental infantile hemangiomas: clinical observations and pathogenetic implications.

    Science.gov (United States)

    Feigenbaum, Dana F; Sybert, Virginia P; Vanderhooft, Sheryll L; Siegel, Dawn; Drolet, Beth A; Frieden, Ilona J; Mathes, Erin F D

    2015-01-01

    Areas of blanched skin in children may be seen as an independent finding or in association with vascular birthmarks. We performed a retrospective chart review to identify and describe infants with areas of ventral midline blanching in the presence of segmental infantile hemangiomas. We identified nine full-term infants with partial or full segmental hemangiomas and areas of midline ventral blanching. Additional ventral wall defects were seen in five patients. Six had cardiac anomalies and six had intracranial anomalies. Five were diagnosed with definite PHACE (posterior fossa, hemangioma, arterial, cardiac, and eye abnormalities) syndrome and three had possible PHACE syndrome. Eight were complicated by ulceration. Treatment varied according to the case. Ventral blanching, even in the absence of overt midline defects, can be seen in infants with segmental hemangiomas at risk for PHACE syndrome. We hypothesize that midline blanching may represent a minor manifestation of a developmental ventral defect.

  9. 3D Surface Editing Based on Level-Sets

    Institute of Scientific and Technical Information of China (English)

    Lin Maosong; Zhang Dianhua

    2005-01-01

    A novel method which integrates the topological flexibility of the level-set approach and the simphcity of point-sampled surfaces is proposed. The grid structure resulted from the level-set approach not only offers a wide range of powerful surface editing techniques for the point set surface editing, but also facilitates the topological change with ease. With the aid of point-based resampling,the method updates the surface shape of the point-based geometry quickly without worrying about point connectivity at all. The point set surface can also change its topology properly whenever a collision with other parts of itself is detected. The experiment demonstrates their effectiveness on several scanned objects and scan-converted models. Four examples of surface editing operations: smoothing, tapering, deforming, and Boolean operations, are presented.

  10. Characterization of Drosophila larval crawling at the level of organism, segment, and somatic body wall musculature.

    Science.gov (United States)

    Heckscher, Ellie S; Lockery, Shawn R; Doe, Chris Q

    2012-09-05

    Understanding rhythmic behavior at the developmental and genetic levels has important implications for neurobiology, medicine, evolution, and robotics. We studied rhythmic behavior--larval crawling--in the genetically and developmentally tractable organism, Drosophila melanogaster. We used narrow-diameter channels to constrain behavior to simple, rhythmic crawling. We quantified crawling at the organism, segment, and muscle levels. We showed that Drosophila larval crawling is made up of a series of periodic strides. Each stride consists of two phases. First, while most abdominal segments remain planted on the substrate, the head, tail, and gut translocate; this "visceral pistoning" moves the center of mass. The movement of the center of mass is likely powered by muscle contractions in the head and tail. Second, the head and tail anchor while a body wall wave moves each abdominal segment in the direction of the crawl. These two phases can be observed occurring independently in embryonic stages before becoming coordinated at hatching. During forward crawls, abdominal body wall movements are powered by simultaneous contraction of dorsal and ventral muscle groups, which occur concurrently with contraction of lateral muscles of the adjacent posterior segment. During reverse crawls, abdominal body wall movements are powered by phase-shifted contractions of dorsal and ventral muscles; and ventral muscle contractions occur concurrently with contraction of lateral muscles in the adjacent anterior segment. This work lays a foundation for use of Drosophila larva as a model system for studying the genetics and development of rhythmic behavior.

  11. Capturing Moving Interfaces by Level Set Method with Ghost Technique

    Institute of Scientific and Technical Information of China (English)

    Wang Xueyao; Liu Shi; Liu Changchun; Jiang Fan; Li Zhihong; Ma Zhengzhong

    2007-01-01

    SMAC method is adopted to solve Navier-Stokes equations, by using fifth-order WENO scheme and TVD R-K scheme, LevelSet methods are used to capture moving interfaces with improved Ghost techniques. Some examples, e.g. the incompressible inviscid flame interfaces of one and two dimensions and the rising-merging of oil bubbles in water, are computed and the comparison with the result of commercial CFD software Fluent has been done. The rationality of LevelSet methods with Ghost technique in capturing moving interfaces with jump conditions is affirmed. It is shown that Level Set method can capture interfaces sharply without complicated reconstruction and can be easily programmed.

  12. Level-Set Topology Optimization with Aeroelastic Constraints

    Science.gov (United States)

    Dunning, Peter D.; Stanford, Bret K.; Kim, H. Alicia

    2015-01-01

    Level-set topology optimization is used to design a wing considering skin buckling under static aeroelastic trim loading, as well as dynamic aeroelastic stability (flutter). The level-set function is defined over the entire 3D volume of a transport aircraft wing box. Therefore, the approach is not limited by any predefined structure and can explore novel configurations. The Sequential Linear Programming (SLP) level-set method is used to solve the constrained optimization problems. The proposed method is demonstrated using three problems with mass, linear buckling and flutter objective and/or constraints. A constraint aggregation method is used to handle multiple buckling constraints in the wing skins. A continuous flutter constraint formulation is used to handle difficulties arising from discontinuities in the design space caused by a switching of the critical flutter mode.

  13. 3D Multiphase Piecewise Constant Level Set Method Based on Graph Cut Minimization

    Institute of Scientific and Technical Information of China (English)

    Tiril P.Gurholt; Xuecheng Tai

    2009-01-01

    Segmentation of three-dimensional (3D) complicated structures is of great importance for many real applications. In this work we combine graph cut minimization method with a variant of the level set idea for 3D segmentation based on the Mumford-Shah model. Compared with the traditional approach for solving the Euler-Lagrange equation we do not need to solve any partial differential equations. Instead, the minimum cut on a special designed graph need to be computed. The method is tested on data with complicated structures. It is rather stable with respect to initial value and the algorithm is nearly parameter free. Experiments show that it can solve large problems much faster than traditional approaches.

  14. Level Set interface treatment and its application in Euler method

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Level Set interface treatment method is introduced into Euler method,which is employed for interface treatment method for multi-materials. Combined with the ghost fluid method,the moving interface is tracked. Fifth-order WENO spatial discretization and third-order TVD Runge-Kutta time discretization methods are used. Shock-wave action on bubble,implosion and velocity field Shock effect bubbles; implosion and velocity field are simulated by means of LS-MMIC3D programmed by C++. Nu-merical results show that the Level Set interface treatment method is effective and feasible for multi-material interface treatment in comparison with the WENO method.

  15. Towards better segmentation of large floating point 3D astronomical data sets : first results

    NARCIS (Netherlands)

    Moschini, Ugo; Teeninga, Paul; Wilkinson, Michael; Giese, Nadine; Punzo, Davide; van der Hulst, Jan M.; Trager, Scott

    2014-01-01

    In any image segmentation task, noise must be separated from the actual information and the relevant pixels grouped into objects of interest, on which measures can later be applied. This should be done efficiently on large astronomical surveys with floating point datasets with resolution of the orde

  16. Effects of Segmented Animated Graphics among Students of Different Spatial Ability Levels: A Cognitive Load Perspective

    Science.gov (United States)

    Fong, Soon Fook

    2013-01-01

    This study investigated the effects of segmented animated graphics utilized to facilitate learning of electrolysis of aqueous solution. A total of 171 Secondary Four chemistry students with two different spatial ability levels were randomly assigned to one of the experimental conditions: (a) text with multiple static graphics (MSG), (b) text with…

  17. A Memory and Computation Efficient Sparse Level-Set Method

    NARCIS (Netherlands)

    Laan, Wladimir J. van der; Jalba, Andrei C.; Roerdink, Jos B.T.M.

    2011-01-01

    Since its introduction, the level set method has become the favorite technique for capturing and tracking moving interfaces, and found applications in a wide variety of scientific fields. In this paper we present efficient data structures and algorithms for tracking dynamic interfaces through the le

  18. A Memory and Computation Efficient Sparse Level-Set Method

    NARCIS (Netherlands)

    Laan, Wladimir J. van der; Jalba, Andrei C.; Roerdink, Jos B.T.M.

    Since its introduction, the level set method has become the favorite technique for capturing and tracking moving interfaces, and found applications in a wide variety of scientific fields. In this paper we present efficient data structures and algorithms for tracking dynamic interfaces through the

  19. Conceptual design of compliant mechanisms using level set method

    Institute of Scientific and Technical Information of China (English)

    Shi-kui CHEN; Michael Yu WANG

    2006-01-01

    We propose a level set method-based framework for the conceptual design of compliant mechanisms.In this method,the compliant mechanism design problem is recast as an infinite dimensional optimization problem,where the design variable is the geometric shape of the compliant mechanism and the goal is to find a suitable shape in the admissible design space so that the objective functional can reach a minimum.The geometric shape of the compliant mechanism is represented as the zero level set of a one-higher dimensional level set function,and the dynamic variations of the shape are governed by the Hamilton-Jacobi partial differential equation.The application of level set methods endows the optimization process with the particular quality that topological changes of the boundary,such as merging or splitting,can be handled in a natural fashion.By making a connection between the velocity field in the Hamilton-Jacobi partial differential equation with the shape gradient of the objective functional,we go further to transform the optimization problem into that of finding a steady-state solution of the partial differential equation.Besides the above-mentioned methodological issues,some numerical examples together with prototypes are presented to validate the performance of the method.

  20. Estimating the concentration of gold nanoparticles incorporated on natural rubber membranes using multi-level starlet optimal segmentation

    Energy Technology Data Exchange (ETDEWEB)

    Siqueira, A. F. de, E-mail: siqueiraaf@gmail.com; Cabrera, F. C., E-mail: flavioccabrera@yahoo.com.br [UNESP – Univ Estadual Paulista, Dep de Física, Química e Biologia (Brazil); Pagamisse, A., E-mail: aylton@fct.unesp.br [UNESP – Univ Estadual Paulista, Dep de Matemática e Computação (Brazil); Job, A. E., E-mail: job@fct.unesp.br [UNESP – Univ Estadual Paulista, Dep de Física, Química e Biologia (Brazil)

    2014-12-15

    This study consolidates multi-level starlet segmentation (MLSS) and multi-level starlet optimal segmentation (MLSOS) techniques for photomicrograph segmentation, based on starlet wavelet detail levels to separate areas of interest in an input image. Several segmentation levels can be obtained using MLSS; after that, Matthews correlation coefficient is used to choose an optimal segmentation level, giving rise to MLSOS. In this paper, MLSOS is employed to estimate the concentration of gold nanoparticles with diameter around 47  nm, reduced on natural rubber membranes. These samples were used for the construction of SERS/SERRS substrates and in the study of the influence of natural rubber membranes with incorporated gold nanoparticles on the physiology of Leishmania braziliensis. Precision, recall, and accuracy are used to evaluate the segmentation performance, and MLSOS presents an accuracy greater than 88 % for this application.

  1. 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.

  2. RESERVOIR DESCRIPTION BY USING A PIECEWISE CONSTANT LEVEL SET METHOD

    Institute of Scientific and Technical Information of China (English)

    Hongwei Li; Xuecheng Tai; Sigurd Ivar Aanonsen

    2008-01-01

    We consider the permeability estimation problem in two-phase porous media flow. We try to identify the permeability field by utilizing both the production data from wells as well as inverted seismic data. The permeability field is assumed to be piecewise constant, or can be approximated well by a piecewise constant function. A variant of the level set method, called Piecewise Constant Level Set Method is used to represent the interfaces between the regions with different permeability levels. The inverse problem is solved by minimizing a functional, and TV norm regularization is used to deal with the ill-posedness. We also use the operator-splitting technique to decompose the constraint term from the fidelity term. This gives us more flexibility to deal with the constraint and helps to stabilize the algorithm.

  3. Analysis of gene expression levels in individual bacterial cells without image segmentation

    Energy Technology Data Exchange (ETDEWEB)

    Kwak, In Hae; Son, Minjun [Physics Department, University of Florida, P.O. Box 118440, Gainesville, FL 32611-8440 (United States); Hagen, Stephen J., E-mail: sjhagen@ufl.edu [Physics Department, University of Florida, P.O. Box 118440, Gainesville, FL 32611-8440 (United States)

    2012-05-11

    Highlights: Black-Right-Pointing-Pointer We present a method for extracting gene expression data from images of bacterial cells. Black-Right-Pointing-Pointer The method does not employ cell segmentation and does not require high magnification. Black-Right-Pointing-Pointer Fluorescence and phase contrast images of the cells are correlated through the physics of phase contrast. Black-Right-Pointing-Pointer We demonstrate the method by characterizing noisy expression of comX in Streptococcus mutans. -- Abstract: Studies of stochasticity in gene expression typically make use of fluorescent protein reporters, which permit the measurement of expression levels within individual cells by fluorescence microscopy. Analysis of such microscopy images is almost invariably based on a segmentation algorithm, where the image of a cell or cluster is analyzed mathematically to delineate individual cell boundaries. However segmentation can be ineffective for studying bacterial cells or clusters, especially at lower magnification, where outlines of individual cells are poorly resolved. Here we demonstrate an alternative method for analyzing such images without segmentation. The method employs a comparison between the pixel brightness in phase contrast vs fluorescence microscopy images. By fitting the correlation between phase contrast and fluorescence intensity to a physical model, we obtain well-defined estimates for the different levels of gene expression that are present in the cell or cluster. The method reveals the boundaries of the individual cells, even if the source images lack the resolution to show these boundaries clearly.

  4. A Multi-Point, Boundary-Value Problem, Collocation Toolbox for the Continuation of sets of Constrained Orbit Segments

    DEFF Research Database (Denmark)

    Dankowicz, Harry; Schilder, Frank

    This paper presents a collocation toolbox for multi-point, boundary-value problems. This toolbox has been recently developed by the authors to support general-purpose parameter continuation of sets of constrained orbit segments, such as i) segmented trajectories in hybrid dynamical systems......, for example, mechanical systems with impacts, friction, and switching control, ii) homoclinic orbits represented by an equilibrium point and a finite-time trajectory that starts and ends near this equilibrium point, and iii) collections of trajectories that represent quasi-periodic invariant tori...... the continuation of families of periodic orbits in a hybrid dynamical system with impacts and friction as well as detection and constrained continuation of selected degeneracies characteristic of such systems, such as grazing and switching-sliding bifurcations....

  5. Level sets and extrema of random processes and fields

    CERN Document Server

    Azais, Jean-Marc

    2009-01-01

    A timely and comprehensive treatment of random field theory with applications across diverse areas of study Level Sets and Extrema of Random Processes and Fields discusses how to understand the properties of the level sets of paths as well as how to compute the probability distribution of its extremal values, which are two general classes of problems that arise in the study of random processes and fields and in related applications. This book provides a unified and accessible approach to these two topics and their relationship to classical theory and Gaussian processes and fields, and the most modern research findings are also discussed. The authors begin with an introduction to the basic concepts of stochastic processes, including a modern review of Gaussian fields and their classical inequalities. Subsequent chapters are devoted to Rice formulas, regularity properties, and recent results on the tails of the distribution of the maximum. Finally, applications of random fields to various areas of mathematics a...

  6. Bayesian inversion for facies detection: An extensible level set framework

    Science.gov (United States)

    Cardiff, M.; Kitanidis, P. K.

    2009-10-01

    In many cases, it has been assumed that the variability in hydrologic parameters can be adequately described through a simple geostatistical model with a given variogram. In other cases, variability may be best described as a series of "jumps" in parameter behavior, e.g., those that occur at geologic facies contacts. When using indirect measurements such as pump tests to try to map such heterogeneity (during inverse modeling), the resulting images of the subsurface are always affected by the assumptions invoked. In this paper, we discuss inversion for parameter fields where prior information has suggested that major variability can be described by boundaries between geologic units or facies. In order to identify such parameter fields, we propose a Bayesian level set inversion protocol framework, which allows for flexible zones of any shape, size, and number. We review formulas for defining facies locations using the level set method and for moving the boundaries between zones using a gradient-based technique that improves fit through iterative deformation of the boundaries. We describe the optimization algorithm employed when multiple level set functions are used to represent a field with more than two facies. We extend these formulas to the investigation of the inverse problem in a Bayesian context in which prior information is taken into account and through which measures of uncertainty can be derived. We also demonstrate that the level set method is well suited for joint inversion problems and present a strategy for integrating different data types (such as hydrologic and geophysical) without assuming strict petrophysical relations. Our framework for joint inversion also contrasts with many previous methods in that all data sources (e.g., both hydrologic and geophysical) contribute to boundary delineation at once.

  7. A Level Set Filter for Speckle Reduction in SAR Images

    OpenAIRE

    Huang Bo; Li Hongga; Huang Xiaoxia

    2010-01-01

    Despite much effort and significant progress in recent years, speckle removal for Synthetic Aperture Radar (SAR) image still is a challenging problem in image processing. Unlike the traditional noise filters, which are mainly based on local neighborhood statistical average or frequencies transform, in this paper, we propose a speckle reduction method based on the theory of level set, one form of curvature flow propagation. Firstly, based on partial differential equation, the Lee filter can b...

  8. Comparison of adjacent segment degeneration five years after single level cervical fusion and cervical arthroplasty:a retrospective controlled study

    Institute of Scientific and Technical Information of China (English)

    SUN Yu; ZHAO Yan-bin; PAN Sheng-fa; ZHOU Fei-fei; CHEN Zhong-qiang; LIU Zhong-jun

    2012-01-01

    Background Cervical arthroplasty is indicated to preserve cervical motion and prevent accelerated adjacent segment degeneration.Whether accelerated adjacent segment degeneration is prevented in the long term is unclear.This trial compared adjacent segment degeneration in Bryan disc arthroplasty with that in anterior cervical decompression and fusion five years after the surgery.Methods We studied patients with single level degenerative cervical disc disease.The extent of adjacent segment degeneration was estimated from lateral X-rays.Results Twenty-six patients underwent single level Bryan disc arthroplasty and twenty-four patients underwent single level anterior cervical decompression and fusion.All patients were followed up for an average of sixty months.In the Bryan arthroplasty group,nine(17.6%)segments developed adjacent segment degeneration,which was significantly lower than that(60.4%)in the anterior cervical decompression and fusion group.Eleven segments in the Bryan arthroplasty group developed heterotopic ossification according to McAfee's classification and two segments had range of motion less than 2°.In the heterotopic ossification group,four(19.5%)segments developed adjacent segment degeneration,similar to the number in the non-heterotopic ossification group(16.7%).Adjacent segment degeneration rate was 50% in gradeⅣ?group but 11.8% in gradeⅡ?to Ⅲ.Conclusions Adjacent segment degeneration was accelerated after anterior cervical decompression and fusion.However,Bryan disc arthroplasty avoided accelerated adjacent segment degeneration by preserving motion.Patients with gradeⅣ?heterotopic ossification lost motion,and the rate of adjacent segment degeneration was higher than that in patients without heterotopic ossification.

  9. A Level Set Filter for Speckle Reduction in SAR Images

    Directory of Open Access Journals (Sweden)

    Xiaoxia Huang

    2010-01-01

    Full Text Available Despite much effort and significant progress in recent years, speckle removal for Synthetic Aperture Radar (SAR image still is a challenging problem in image processing. Unlike the traditional noise filters, which are mainly based on local neighborhood statistical average or frequencies transform, in this paper, we propose a speckle reduction method based on the theory of level set, one form of curvature flow propagation. Firstly, based on partial differential equation, the Lee filter can be cast as a formulation of anisotropic diffusion function; furthermore, we continued to deduce it into a level set formulation. Level set flow into the method allows the front interface to propagate naturally with topological changes, where the speed is proportional to the curvature of the intensity contours in an image. Hence, small speckle will disappear quickly, while large scale interfaces will be slow to evolve. Secondly, for preserving finer detailed structures in images when smoothing the speckle, the evolution is switched between minimum or maximum curvature speed depending on the scale of speckle. The proposed method has been illustrated by experiments on simulation image and ERS-2 SAR images under different circumstances. Its advantages over the traditional speckle reduction filter approaches have also been demonstrated.

  10. A Level Set Filter for Speckle Reduction in SAR Images

    Science.gov (United States)

    Li, Hongga; Huang, Bo; Huang, Xiaoxia

    2010-12-01

    Despite much effort and significant progress in recent years, speckle removal for Synthetic Aperture Radar (SAR) image still is a challenging problem in image processing. Unlike the traditional noise filters, which are mainly based on local neighborhood statistical average or frequencies transform, in this paper, we propose a speckle reduction method based on the theory of level set, one form of curvature flow propagation. Firstly, based on partial differential equation, the Lee filter can be cast as a formulation of anisotropic diffusion function; furthermore, we continued to deduce it into a level set formulation. Level set flow into the method allows the front interface to propagate naturally with topological changes, where the speed is proportional to the curvature of the intensity contours in an image. Hence, small speckle will disappear quickly, while large scale interfaces will be slow to evolve. Secondly, for preserving finer detailed structures in images when smoothing the speckle, the evolution is switched between minimum or maximum curvature speed depending on the scale of speckle. The proposed method has been illustrated by experiments on simulation image and ERS-2 SAR images under different circumstances. Its advantages over the traditional speckle reduction filter approaches have also been demonstrated.

  11. Segmentation pattern and structural complexities in seismogenic extensional settings: The North Matese Fault System (Central Italy)

    Science.gov (United States)

    Ferrarini, Federica; Boncio, Paolo; de Nardis, Rita; Pappone, Gerardo; Cesarano, Massimo; Aucelli, Pietro P. C.; Lavecchia, Giusy

    2017-02-01

    We investigated the northern slope of the Matese Mts. (Molise, Central Italy) with the aim of characterizing the N- to NE-dipping active normal fault system in the Bojano basin, a sector of primary importance from a seismic hazard perspective. We collected field data to define the geometry and segmentation pattern of two sub-systems (Patalecchia-Colle di Mezzo and Bojano-Campochiaro). New evidence of late Quaternary faulting was obtained by exploiting well log interpretations. Kinematic analysis revealed the interaction of pre-Quaternary inherited (mainly E-W-striking) and newly formed (NW-SE-striking) normal faults. Slip accommodation through linkage was clearly noted in the case of the Patalecchia-Colle di Mezzo sub-system. Detailed topographic profiles across the active fault segments provided post-LGM (15 ± 3 kyr) slip rates up to ∼2 mm/yr which agree with the high deformation rates based on different approaches in the literature. Finally, the instrumental seismicity analysis constrained the bottom of the seismogenic layer to depths of 13-14 km, and the gathered information allowed us to reconstruct the North Matese seismogenic source. Its 3D geometry and dimensions agree with both the dimension-magnitude relationships and macroseismic information available for the 1805 earthquake (Mw 6.6), the main historical earthquake to have struck the Bojano basin.

  12. Automatic segmentation of the fetal cerebellum using spherical harmonics and gray level profiles

    Science.gov (United States)

    Velásquez-Rodríguez, Gustavo; Arámbula Cosío, Fernando; Escalate Ramírez, Boris

    2015-12-01

    The cerebellum is an important structure to determine the gestational age, cerebellar diameter obtained by ultrasound volumes of the fetal brain has shown a high correlation with gestational age, therefore is useful to determine fetal growth restrictions. The manual annotation of 3D surfaces from the fetal brain is time consuming and needs to be done by a highly trained expert. To help with the annotation in the evaluation of cerebellar diameter, we developed a new automatic scheme for the segmentation of the 3D surface of the cerebellum in ultrasound volumes, using a spherical harmonics model and the optimization of an objective function based on gray level voxel profiles. The results on 10 ultrasound volumes of the fetal brain show an accuracy in the segmentation of the cerebellum (mean Dice coefficient of 0.7544). The method reported shows potential to effectively assist the experts in the assessment of fetal growth in ultrasound volumes. We consider the proposed cerebellum segmentation method a contribution for the SPHARM segmentations models, because it is capable to run without hardware restriction, (GPU), and gives adequate results in a reasonable amount of time.

  13. Method to Determine Pedestrian Level of Service for the Overall Unsignalized Midblock Crossings of Road Segments

    Directory of Open Access Journals (Sweden)

    Lin Zhao

    2014-11-01

    Full Text Available This paper aims at developing a pedestrian level of service (LOS model for the overall unsignalized midblock crossings of road segments from the perspective of the pedestrian's perception of safety and convenience in Chinese midblock crossing environment. Firstly, the potential primary factors influencing pedestrian LOS at unsignalized midblock crosswalks were summarized from four respects: traffic conflicts, the distance between crosswalks, crossing facilities, and delay. Secondly, 948 participants’ real-time sense of safety and convenience when they were crossing the 30 selected unsignalized midblock crosswalks and the design and operational characteristics of the selected road segments were collected. The selected midblock crosswalks were typical of those prevalent in the medium-sized urban areas of China, and the participants of questionnaire survey covered a broad cross section of Chinese population of pedestrians. Finally, Pearson correlation analysis and stepwise regression analysis were carried out to develop pedestrian LOS model for the overall unsignalized midblock crossings of road segments. The results revealed that the factors significantly influencing pedestrian LOS of the overall unsignalized midblock crossings of road segments included volume of two-way motor vehicle, the distance between marked midblock crosswalks, and the distance between unmarked crosswalks. A reliable, statistically calibrated pedestrian LOS model was developed (R2 = 0.80.

  14. Multichannel loudness compensation method based on segmented sound pressure level for digital hearing aids

    Science.gov (United States)

    Liang, Ruiyu; Xi, Ji; Bao, Yongqiang

    2017-07-01

    To improve the performance of gain compensation based on three-segment sound pressure level (SPL) in hearing aids, an improved multichannel loudness compensation method based on eight-segment SPL was proposed. Firstly, the uniform cosine modulated filter bank was designed. Then, the adjacent channels which have low or gradual slopes were adaptively merged to obtain the corresponding non-uniform cosine modulated filter according to the audiogram of hearing impaired persons. Secondly, the input speech was decomposed into sub-band signals and the SPL of every sub-band signal was computed. Meanwhile, the audible SPL range from 0 dB SPL to 120 dB SPL was equally divided into eight segments. Based on these segments, a different prescription formula was designed to compute more detailed gain to compensate according to the audiogram and the computed SPL. Finally, the enhanced signal was synthesized. Objective experiments showed the decomposed signals after cosine modulated filter bank have little distortion. Objective experiments showed that the hearing aids speech perception index (HASPI) and hearing aids speech quality index (HASQI) increased 0.083 and 0.082 on average, respectively. Subjective experiments showed the proposed algorithm can effectively improve the speech recognition of six hearing impaired persons.

  15. Radiographic results of single level transforaminal lumbar interbody fusion in degenerative lumbar spine disease: focusing on changes of segmental lordosis in fusion segment.

    Science.gov (United States)

    Kim, Sang-Bum; Jeon, Taek-Soo; Heo, Youn-Moo; Lee, Woo-Suk; Yi, Jin-Woong; Kim, Tae-Kyun; Hwang, Cheol-Mog

    2009-12-01

    To assess the radiographic results in patients who underwent transforaminal lumbar interbody fusion (TLIF), particularly the changes in segmental lordosis in the fusion segment, whole lumbar lordosis and disc height. Twenty six cases of single-level TLIF in degenerative lumbar diseases were analyzed. The changes in segmental lordosis, whole lumbar lordosis, and disc height were evaluated before surgery, after surgery and at the final follow-up. The segmental lordosis increased significantly after surgery but decreased at the final follow-up. Compared to the preoperative values, the segmental lordosis did not change significantly at the final follow-up. Whole lumbar lordosis at the final follow-up was significantly higher than the preoperative values. The disc height was significantly higher in after surgery than before surgery (p = 0.000) and the disc height alter surgery and at the final follow-up was similar. When performing TLIF, careful surgical techniques and attention are needed to restore and maintain the segmental lordosis at the fusion level.

  16. Short Segment Fixation Versus Short Segment Fixation With Pedicle Screws at the Fracture Level for Thoracolumbar Burst Fracture

    Directory of Open Access Journals (Sweden)

    Anghel S

    2014-04-01

    Full Text Available Objective: The most prevailing surgical procedure in the treatment of thoracolumbar burst fractures, Short Segment Fixation (SSF, is often followed by loss of correction or hardware failure which may be significant enough to require another surgical intervention. In order to take advantage of its benefits but to avoid or diminish the risk and impact of associated drawbacks, some other alternatives have been lately developed among which we refer to short segment fixation with intermediate screws (SSF+IS. This article provides a comparative picture over the effectiveness of the two above-mentioned surgical treatments, focusing on their potential to prevent the loss of correction.

  17. Image Segmentation Parameter Optimization Considering Within- and Between-Segment Heterogeneity at Multiple Scale Levels: Test Case for Mapping Residential Areas Using Landsat Imagery

    Directory of Open Access Journals (Sweden)

    Brian A. Johnson

    2015-10-01

    Full Text Available Multi-scale/multi-level geographic object-based image analysis (MS-GEOBIA methods are becoming widely-used in remote sensing because single-scale/single-level (SS-GEOBIA methods are often unable to obtain an accurate segmentation and classification of all land use/land cover (LULC types in an image. However, there have been few comparisons between SS-GEOBIA and MS-GEOBIA approaches for the purpose of mapping a specific LULC type, so it is not well understood which is more appropriate for this task. In addition, there are few methods for automating the selection of segmentation parameters for MS-GEOBIA, while manual selection (i.e., trial-and-error approach of parameters can be quite challenging and time-consuming. In this study, we examined SS-GEOBIA and MS-GEOBIA approaches for extracting residential areas in Landsat 8 imagery, and compared naïve and parameter-optimized segmentation approaches to assess whether unsupervised segmentation parameter optimization (USPO could improve the extraction of residential areas. Our main findings were: (i the MS-GEOBIA approaches achieved higher classification accuracies than the SS-GEOBIA approach, and (ii USPO resulted in more accurate MS-GEOBIA classification results while reducing the number of segmentation levels and classification variables considerably.

  18. A Level Set Discontinuous Galerkin Method for Free Surface Flows

    DEFF Research Database (Denmark)

    Grooss, Jesper; Hesthaven, Jan

    2006-01-01

    We present a discontinuous Galerkin method on a fully unstructured grid for the modeling of unsteady incompressible fluid flows with free surfaces. The surface is modeled by embedding and represented by a levelset. We discuss the discretization of the flow equations and the level set equation...... as well a various ways of advancing the equations in time using velocity projection techniques. The efficacy of the method for the representation of the levelset and its reinitialization is discussed and several numerical tests confirm the robustness and versatility of the proposed scheme....

  19. An Automatic Optic Disk Detection and Segmentation System using Multi-level Thresholding

    Directory of Open Access Journals (Sweden)

    KARASULU, B.

    2014-05-01

    Full Text Available Optic disk (OD boundary localization is a substantial problem in ophthalmic image processing research area. In order to segment the region of OD, we developed an automatic system which involves a multi-level thresholding. The OD segmentation results of the system in terms of average precision, recall and accuracy for DRIVE database are 98.88%, 99.91%, 98.83%, for STARE database are 98.62%, 97.38%, 96.11%, and for DIARETDB1 database are 99.29%, 99.90%, 99.20%, respectively. The experimental results show that our system works properly on retinal image databases with diseased retinas, diabetic signs, and a large degree of quality variability.

  20. Online monitoring of oil film using electrical capacitance tomography and level set method

    Energy Technology Data Exchange (ETDEWEB)

    Xue, Q., E-mail: xueqian@tju.edu.cn; Ma, M. [College of Aeronautical Automation, Civil Aviation University of China, Tianjin 300300 (China); Sun, B. Y.; Cui, Z. Q.; Wang, H. X. [School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China)

    2015-08-15

    In the application of oil-air lubrication system, electrical capacitance tomography (ECT) provides a promising way for monitoring oil film in the pipelines by reconstructing cross sectional oil distributions in real time. While in the case of small diameter pipe and thin oil film, the thickness of the oil film is hard to be observed visually since the interface of oil and air is not obvious in the reconstructed images. And the existence of artifacts in the reconstructions has seriously influenced the effectiveness of image segmentation techniques such as level set method. Besides, level set method is also unavailable for online monitoring due to its low computation speed. To address these problems, a modified level set method is developed: a distance regularized level set evolution formulation is extended to image two-phase flow online using an ECT system, a narrowband image filter is defined to eliminate the influence of artifacts, and considering the continuity of the oil distribution variation, the detected oil-air interface of a former image can be used as the initial contour for the detection of the subsequent frame; thus, the propagation from the initial contour to the boundary can be greatly accelerated, making it possible for real time tracking. To testify the feasibility of the proposed method, an oil-air lubrication facility with 4 mm inner diameter pipe is measured in normal operation using an 8-electrode ECT system. Both simulation and experiment results indicate that the modified level set method is capable of visualizing the oil-air interface accurately online.

  1. Online monitoring of oil film using electrical capacitance tomography and level set method

    Science.gov (United States)

    Xue, Q.; Sun, B. Y.; Cui, Z. Q.; Ma, M.; Wang, H. X.

    2015-08-01

    In the application of oil-air lubrication system, electrical capacitance tomography (ECT) provides a promising way for monitoring oil film in the pipelines by reconstructing cross sectional oil distributions in real time. While in the case of small diameter pipe and thin oil film, the thickness of the oil film is hard to be observed visually since the interface of oil and air is not obvious in the reconstructed images. And the existence of artifacts in the reconstructions has seriously influenced the effectiveness of image segmentation techniques such as level set method. Besides, level set method is also unavailable for online monitoring due to its low computation speed. To address these problems, a modified level set method is developed: a distance regularized level set evolution formulation is extended to image two-phase flow online using an ECT system, a narrowband image filter is defined to eliminate the influence of artifacts, and considering the continuity of the oil distribution variation, the detected oil-air interface of a former image can be used as the initial contour for the detection of the subsequent frame; thus, the propagation from the initial contour to the boundary can be greatly accelerated, making it possible for real time tracking. To testify the feasibility of the proposed method, an oil-air lubrication facility with 4 mm inner diameter pipe is measured in normal operation using an 8-electrode ECT system. Both simulation and experiment results indicate that the modified level set method is capable of visualizing the oil-air interface accurately online.

  2. Segmental and global lordosis changes with two-level axial lumbar interbody fusion and posterior instrumentation

    Science.gov (United States)

    Melgar, Miguel A; Tobler, William D; Ernst, Robert J; Raley, Thomas J; Anand, Neel; Miller, Larry E; Nasca, Richard J

    2014-01-01

    Background Loss of lumbar lordosis has been reported after lumbar interbody fusion surgery and may portend poor clinical and radiographic outcome. The objective of this research was to measure changes in segmental and global lumbar lordosis in patients treated with presacral axial L4-S1 interbody fusion and posterior instrumentation and to determine if these changes influenced patient outcomes. Methods We performed a retrospective, multi-center review of prospectively collected data in 58 consecutive patients with disabling lumbar pain and radiculopathy unresponsive to nonsurgical treatment who underwent L4-S1 interbody fusion with the AxiaLIF two-level system (Baxano Surgical, Raleigh NC). Main outcomes included back pain severity, Oswestry Disability Index (ODI), Odom's outcome criteria, and fusion status using flexion and extension radiographs and computed tomography scans. Segmental (L4-S1) and global (L1-S1) lumbar lordosis measurements were made using standing lateral radiographs. All patients were followed for at least 24 months (mean: 29 months, range 24-56 months). Results There was no bowel injury, vascular injury, deep infection, neurologic complication or implant failure. Mean back pain severity improved from 7.8±1.7 at baseline to 3.3±2.6 at 2 years (p lordosis, defined as a change in Cobb angle ≤ 5°, was identified in 84% of patients at L4-S1 and 81% of patients at L1-S1. Patients with loss or gain in segmental or global lordosis experienced similar 2-year outcomes versus those with less than a 5° change. Conclusions/Clinical Relevance Two-level axial interbody fusion supplemented with posterior fixation does not alter segmental or global lordosis in most patients. Patients with postoperative change in lordosis greater than 5° have similarly favorable long-term clinical outcomes and fusion rates compared to patients with less than 5° lordosis change. PMID:25694920

  3. An in vivo MRI template set for morphometry, tissue segmentation and fMRI localization in rats

    Directory of Open Access Journals (Sweden)

    Pedro Antonio Valdes Hernandez

    2011-11-01

    Full Text Available Over the last decade, several papers have focused on the construction of highly detailed mouse high field MRI templates via nonlinear registration to unbiased reference spaces, allowing for a variety of neuroimaging applications such as robust morphometric analyses. However, work in rats has only provided medium field MRI averages based on linear registration to biased spaces with the sole purpose of approximate fMRI localization. This precludes any morphometric analysis in spite of the need of exploring in detail the neuroanatomical substrates of diseases in a recent advent of rat models. In this paper we present a new in vivo rat T2 MRI template set, comprising average images of both intensity and shape, obtained via nonlinear registration. Also, unlike previous rat template sets, we include white and gray matter probabilistic segmentations, expanding its use to those applications demanding prior-based tissue segmentation, e.g. SPM voxel-based morphometry. We also provide a preliminary digitalization of latest Paxinos & Watson atlas for anatomical and functional interpretations within the cerebral cortex. We confirmed that, like with previous templates, forepaw and hindpaw fMRI activations can be correctly localized in the expected atlas structure. To exemplify the use of our new MRI template set, we reported the volumes of brain tissues and cortical structures and probed their relationships with ontogenetic development. Other in vivo applications in the near future can be tensor-, deformation- or voxel-based morphometry, morphological connectivity and diffusion tensor-based anatomical connectivity. Our template set, freely available through the SPM extension website, could be an important tool for future longitudinal and/or functional extensive preclinical studies.

  4. An in vivo MRI Template Set for Morphometry, Tissue Segmentation, and fMRI Localization in Rats.

    Science.gov (United States)

    Valdés-Hernández, Pedro Antonio; Sumiyoshi, Akira; Nonaka, Hiroi; Haga, Risa; Aubert-Vásquez, Eduardo; Ogawa, Takeshi; Iturria-Medina, Yasser; Riera, Jorge J; Kawashima, Ryuta

    2011-01-01

    Over the last decade, several papers have focused on the construction of highly detailed mouse high field magnetic resonance image (MRI) templates via non-linear registration to unbiased reference spaces, allowing for a variety of neuroimaging applications such as robust morphometric analyses. However, work in rats has only provided medium field MRI averages based on linear registration to biased spaces with the sole purpose of approximate functional MRI (fMRI) localization. This precludes any morphometric analysis in spite of the need of exploring in detail the neuroanatomical substrates of diseases in a recent advent of rat models. In this paper we present a new in vivo rat T2 MRI template set, comprising average images of both intensity and shape, obtained via non-linear registration. Also, unlike previous rat template sets, we include white and gray matter probabilistic segmentations, expanding its use to those applications demanding prior-based tissue segmentation, e.g., statistical parametric mapping (SPM) voxel-based morphometry. We also provide a preliminary digitalization of latest Paxinos and Watson atlas for anatomical and functional interpretations within the cerebral cortex. We confirmed that, like with previous templates, forepaw and hindpaw fMRI activations can be correctly localized in the expected atlas structure. To exemplify the use of our new MRI template set, were reported the volumes of brain tissues and cortical structures and probed their relationships with ontogenetic development. Other in vivo applications in the near future can be tensor-, deformation-, or voxel-based morphometry, morphological connectivity, and diffusion tensor-based anatomical connectivity. Our template set, freely available through the SPM extension website, could be an important tool for future longitudinal and/or functional extensive preclinical studies.

  5. Setting Inventory Levels of CONWIP Flow Lines via Linear Programming

    Directory of Open Access Journals (Sweden)

    Stefan Helber

    2011-04-01

    Full Text Available This paper treats the problem of setting the inventory level and optimizing the buffer allocation of closed-loop flow lines operating under the constant-work-in-process (CONWIP protocol. We solve a very large but simple linear program that models an entire simulation run of a closed-loop flow line in discrete time to determine a production rate estimate of the system. This approach introduced in Helber, Schimmelpfeng, Stolletz, and Lagershausen (2011 for open flow lines with limited buffer capacities is extended to closed-loop CONWIP flow lines. Via this method, both the CONWIP level and the buffer allocation can be optimized simultaneously. The first part of a numerical study deals with the accuracy of the method. In the second part, we focus on the relationship between the CONWIP inventory level and the short-term profit. The accuracy of the method turns out to be best for such configurations that maximize production rate and/or short-term profit.

  6. Accurate level set method for simulations of liquid atomization☆

    Institute of Scientific and Technical Information of China (English)

    Changxiao Shao; Kun Luo; Jianshan Yang; Song Chen; Jianren Fan

    2015-01-01

    Computational fluid dynamics is an efficient numerical approach for spray atomization study, but it is chal enging to accurately capture the gas–liquid interface. In this work, an accurate conservative level set method is intro-duced to accurately track the gas–liquid interfaces in liquid atomization. To validate the capability of this method, binary drop collision and drop impacting on liquid film are investigated. The results are in good agreement with experiment observations. In addition, primary atomization (swirling sheet atomization) is studied using this method. To the swirling sheet atomization, it is found that Rayleigh–Taylor instability in the azimuthal direction causes the primary breakup of liquid sheet and complex vortex structures are clustered around the rim of the liq-uid sheet. The effects of central gas velocity and liquid–gas density ratio on atomization are also investigated. This work lays a solid foundation for further studying the mechanism of spray atomization.

  7. Gray Cerebrovascular Image Skeleton Extraction Algorithm Using Level Set Model

    Directory of Open Access Journals (Sweden)

    Jian Wu

    2010-06-01

    Full Text Available The ambiguity and complexity of medical cerebrovascular image makes the skeleton gained by conventional skeleton algorithm discontinuous, which is sensitive at the weak edges, with poor robustness and too many burrs. This paper proposes a cerebrovascular image skeleton extraction algorithm based on Level Set model, using Euclidean distance field and improved gradient vector flow to obtain two different energy functions. The first energy function controls the  obtain of topological nodes for the beginning of skeleton curve. The second energy function controls the extraction of skeleton surface. This algorithm avoids the locating and classifying of the skeleton connection points which guide the skeleton extraction. Because all its parameters are gotten by the analysis and reasoning, no artificial interference is needed.

  8. Modeling cellular deformations using the level set formalism

    Directory of Open Access Journals (Sweden)

    Yang Liu

    2008-07-01

    Full Text Available Abstract Background Many cellular processes involve substantial shape changes. Traditional simulations of these cell shape changes require that grids and boundaries be moved as the cell's shape evolves. Here we demonstrate that accurate cell shape changes can be recreated using level set methods (LSM, in which the cellular shape is defined implicitly, thereby eschewing the need for updating boundaries. Results We obtain a viscoelastic model of Dictyostelium cells using micropipette aspiration and show how this viscoelastic model can be incorporated into LSM simulations to recreate the observed protrusion of cells into the micropipette faithfully. We also demonstrate the use of our techniques by simulating the cell shape changes elicited by the chemotactic response to an external chemoattractant gradient. Conclusion Our results provide a simple but effective means of incorporating cellular deformations into mathematical simulations of cell signaling. Such methods will be useful for simulating important cellular events such as chemotaxis and cytokinesis.

  9. Identifying Aquifer Heterogeneities using the Level Set Method

    Science.gov (United States)

    Lu, Z.; Vesselinov, V. V.; Lei, H.

    2016-12-01

    Material interfaces between hydrostatigraphic units (HSU) with contrasting aquifer parameters (e.g., strata and facies with different hydraulic conductivity) have a great impact on flow and contaminant transport in subsurface. However, the identification of HSU shape in the subsurface is challenging and typically relies on tomographic approaches where a series of steady-state/transient head measurements at spatially distributed observation locations are analyzed using inverse models. In this study, we developed a mathematically rigorous approach for identifying material interfaces among any arbitrary number of HSUs using the level set method. The approach has been tested first with several synthetic cases, where the true spatial distribution of HSUs was assumed to be known and the head measurements were taken from the flow simulation with the true parameter fields. These synthetic inversion examples demonstrate that the level set method is capable of characterizing the spatial distribution of the heterogeneous. We then applied the methodology to a large-scale problem in which the spatial distribution of pumping wells and observation well screens is consistent with the actual aquifer contamination (chromium) site at the Los Alamos National Laboratory (LANL). In this way, we test the applicability of the methodology at an actual site. We also present preliminary results using the actual LANL site data. We also investigated the impact of the number of pumping/observation wells and the drawdown observation frequencies/intervals on the quality of the inversion results. We also examined the uncertainties associated with the estimated HSU shapes, and the accuracy of the results under different hydraulic-conductivity contrasts between the HSU's.

  10. Rhodopsin expression level affects rod outer segment morphology and photoresponse kinetics.

    Directory of Open Access Journals (Sweden)

    Clint L Makino

    Full Text Available BACKGROUND: The retinal rod outer segment is a sensory cilium that is specialized for the conversion of light into an electrical signal. Within the cilium, up to several thousand membranous disks contain as many as a billion copies of rhodopsin for efficient photon capture. Disks are continually turned over, requiring the daily synthesis of a prodigious amount of rhodopsin. To promote axial diffusion in the aqueous cytoplasm, the disks have one or more incisures. Across vertebrates, the range of disk diameters spans an order of magnitude, and the number and length of the incisures vary considerably, but the mechanisms controlling disk architecture are not well understood. The finding that transgenic mice overexpressing rhodopsin have enlarged disks lacking an incisure prompted us to test whether lowered rhodopsin levels constrain disk assembly. METHODOLOGY/PRINCIPAL FINDINGS: The structure and function of rods from hemizygous rhodopsin knockout (R+/- mice with decreased rhodopsin expression were analyzed by transmission electron microscopy and single cell recording. R+/- rods were structurally altered in three ways: disk shape changed from circular to elliptical, disk surface area decreased, and the single incisure lengthened to divide the disk into two sections. Photocurrent responses to flashes recovered more rapidly than normal. A spatially resolved model of phototransduction indicated that changes in the packing densities of rhodopsin and other transduction proteins were responsible. The decrease in aqueous outer segment volume and the lengthened incisure had only minor effects on photon response amplitude and kinetics. CONCLUSIONS/SIGNIFICANCE: Rhodopsin availability limits disk assembly and outer segment girth in normal rods. The incisure may buffer the supply of structural proteins needed to form larger disks. Decreased rhodopsin level accelerated photoresponse kinetics by increasing the rates of molecular collisions on the membrane

  11. Plasma high-mobility group box 1 levels predict mortality after ST-segment elevation myocardial infarction

    DEFF Research Database (Denmark)

    Sørensen, Morten V; Pedersen, Sune; Møgelvang, Rasmus

    2011-01-01

    We evaluated the potential association between plasma high-mobility group box 1 (HMGB1) levels and outcome in patients with ST-segment elevation myocardial infarction (STEMI) treated with primary percutaneous coronary intervention.......We evaluated the potential association between plasma high-mobility group box 1 (HMGB1) levels and outcome in patients with ST-segment elevation myocardial infarction (STEMI) treated with primary percutaneous coronary intervention....

  12. Is Preventative Long-Segment Surgery for Multi-Level Spondylolysis Necessary? A Finite Element Analysis Study.

    Directory of Open Access Journals (Sweden)

    Jianqiang Mo

    Full Text Available For multi-level spondylolysis patients, surgeons commonly choose to fix all the segments with pars interarticularis defect even those without slippage and not responsible for clinical symptoms. In this study, we tried to study the necessity of the preventative long-segment surgery for the defected segment without slippage in treatment of multi-level spondylolysis patients from a biomechanical perspective.We established a bi-level spondylolysis model with pars defects at L4 and L5 segments, and simulated posterior lumbar interbody fusion (PLIF and pedicle screw fixation at L5-S1 level. Then we compared the biomechanical changes at L4 segment before and after surgery in neutral, flexion, extension, lateral bending and axial rotation position.The stress on L4 pars interarticularis was very similar before and after surgery, and reached the highest in axial rotation. The L3-L4 intradiscal pressure was almost the same, while L4-L5 intradiscal pressure changed a little in lateral bending (increase from 1.993 to 2.160 MPa and axial rotation (decrease from 1.639 to 1.307 MPa after surgery. The PLIF surgery caused a little increase of range of motion at adjacent L4-L5 and L3-L4 levels, but the change is very tiny (1 degree.The PLIF surgery will not cause significant biomechanical change at adjacent segment with pars defect in multi-level spondylolysis. On the contrary, excessive long-segment surgery will damage surrounding soft tissues which are important for maintaining the stability of spine. So a preventative long-segment surgery is not necessary for multi-level spondylolysis as long as there are no soft tissue degeneration signs at adjacent level.

  13. Deep learning in the small sample size setting: cascaded feed forward neural networks for medical image segmentation

    Science.gov (United States)

    Gaonkar, Bilwaj; Hovda, David; Martin, Neil; Macyszyn, Luke

    2016-03-01

    Deep Learning, refers to large set of neural network based algorithms, have emerged as promising machine- learning tools in the general imaging and computer vision domains. Convolutional neural networks (CNNs), a specific class of deep learning algorithms, have been extremely effective in object recognition and localization in natural images. A characteristic feature of CNNs, is the use of a locally connected multi layer topology that is inspired by the animal visual cortex (the most powerful vision system in existence). While CNNs, perform admirably in object identification and localization tasks, typically require training on extremely large datasets. Unfortunately, in medical image analysis, large datasets are either unavailable or are extremely expensive to obtain. Further, the primary tasks in medical imaging are organ identification and segmentation from 3D scans, which are different from the standard computer vision tasks of object recognition. Thus, in order to translate the advantages of deep learning to medical image analysis, there is a need to develop deep network topologies and training methodologies, that are geared towards medical imaging related tasks and can work in a setting where dataset sizes are relatively small. In this paper, we present a technique for stacked supervised training of deep feed forward neural networks for segmenting organs from medical scans. Each `neural network layer' in the stack is trained to identify a sub region of the original image, that contains the organ of interest. By layering several such stacks together a very deep neural network is constructed. Such a network can be used to identify extremely small regions of interest in extremely large images, inspite of a lack of clear contrast in the signal or easily identifiable shape characteristics. What is even more intriguing is that the network stack achieves accurate segmentation even when it is trained on a single image with manually labelled ground truth. We validate

  14. Pixel-Level Deep Segmentation: Artificial Intelligence Quantifies Muscle on Computed Tomography for Body Morphometric Analysis.

    Science.gov (United States)

    Lee, Hyunkwang; Troschel, Fabian M; Tajmir, Shahein; Fuchs, Georg; Mario, Julia; Fintelmann, Florian J; Do, Synho

    2017-08-01

    Pretreatment risk stratification is key for personalized medicine. While many physicians rely on an "eyeball test" to assess whether patients will tolerate major surgery or chemotherapy, "eyeballing" is inherently subjective and difficult to quantify. The concept of morphometric age derived from cross-sectional imaging has been found to correlate well with outcomes such as length of stay, morbidity, and mortality. However, the determination of the morphometric age is time intensive and requires highly trained experts. In this study, we propose a fully automated deep learning system for the segmentation of skeletal muscle cross-sectional area (CSA) on an axial computed tomography image taken at the third lumbar vertebra. We utilized a fully automated deep segmentation model derived from an extended implementation of a fully convolutional network with weight initialization of an ImageNet pre-trained model, followed by post processing to eliminate intramuscular fat for a more accurate analysis. This experiment was conducted by varying window level (WL), window width (WW), and bit resolutions in order to better understand the effects of the parameters on the model performance. Our best model, fine-tuned on 250 training images and ground truth labels, achieves 0.93 ± 0.02 Dice similarity coefficient (DSC) and 3.68 ± 2.29% difference between predicted and ground truth muscle CSA on 150 held-out test cases. Ultimately, the fully automated segmentation system can be embedded into the clinical environment to accelerate the quantification of muscle and expanded to volume analysis of 3D datasets.

  15. Device for timing and power level setting for microwave applications

    Science.gov (United States)

    Ursu, M.-P.; Buidoş, T.

    2016-08-01

    Nowadays, the microwaves are widely used for various technological processes. The microwaves are emitted by magnetrons, which have strict requirements concerning power supplies for anode and filament cathodes, intensity of magnetic field, cooling and electromagnetic shielding. The magnetrons do not tolerate any alteration of their required voltages, currents and magnetic fields, which means that their output microwave power is fixed, so the only way to alter the power level is to use time-division, by turning the magnetron on and off by repetitive time patterns. In order to attain accurate and reproducible results, as well as correct and safe operation of the microwave device, all these requirements must be fulfilled. Safe, correct and reproducible operation of the microwave appliance can be achieved by means of a specially built electronic device, which ensures accurate and reproducible exposure times, interlocking of the commands and automatic switch off when abnormal operating conditions occur. This driving device, designed and realized during the completion of Mr.Ursu's doctoral thesis, consists of a quartz time-base, several programmable frequency and duration dividers, LED displays, sensors and interlocking gates. The active and passive electronic components are placed on custom-made PCB's, designed and made by means of computer-aided applications and machines. The driving commands of the electronic device are delivered to the magnetron power supplies by means of optic zero-passing relays. The inputs of the electronic driving device can sense the status of the microwave appliance. The user is able to enter the total exposure time, the division factor that sets the output power level and, as a novelty, the clock frequency of the time divider.

  16. A comparison of multi-segment foot kinematics during level overground and treadmill walking.

    Science.gov (United States)

    Tulchin, Kirsten; Orendurff, Michael; Karol, Lori

    2010-01-01

    Previous work comparing treadmill and overground walking has focused on lower extremity motion and kinetics, with few identified differences. However, a comparison of multi-segment foot kinematics between these conditions has not been previously reported. Sagittal ankle motion using a single rigid body foot model and three-dimensional hindfoot and forefoot kinematics were compared during barefoot, level, overground walking at a self-selected speed and treadmill walking at a similar speed for 20 healthy adults. Slight differences were seen in ankle plantarflexion and hindfoot plantarflexion during first rocker, as well as peak forefoot eversion and abduction, however all changes were less than 3 degrees , and most were within the day-to-day repeatability. These results indicate that foot mechanics as determined using a multi-segment foot model were similar between overground and treadmill walking at similar speeds in healthy adults. Treadmill protocols may provide a controlled method to analyze a patient's ability to adapt to walking at different speeds and surface slopes, which are encountered often during ambulation of daily living.

  17. Loudness discomfort level for speech: comparison of two instructional sets for saturation sound pressure level selection.

    Science.gov (United States)

    Beattie, R C; Svihovec, D A; Carmen, R E; Kunkel, H A

    1980-01-01

    This study was undertaken to compare the speech loudness discomfort levels (LDL's) with two instructional sets which have been proposed for saturation sound pressure level selection of hearing aids. The phraseology recommended by McCandless and by Berger was presented to normal-hearing and hearing-impaired listeners. The normal-hearing subjects obtained mean LDL's of 94.6 and 111.9 dB SPL for these respective instructions, which was statistically significant. The hearing-impaired listeners also showed LDL's with Berger's instructions (114.7 dB SPL) to be significantly higher than with McCandless' instructional set (109.3 dB SPL). Consequently, this investigation suggests that these two instructional sets may lead to substantially different saturation sound pressure levels. Further studies are needed to determine the most appropriate phraseology for LDL measurement, including the assessment of speech intelligibility at various saturation sound pressure levels. Another instructional set was constructed which (1) includes an explanation to patients of the purpose and importance of the test, (2) requests listeners to indicate the upper level they are "willing" to listen as opposed to the level they are "able" to listen, (3) instructs patients to search thoroughly around their LDL before making a final judgment, and (4) contains a statement that the LDL should be made with the understanding that the speech could be listened to for a period of time. Whatever instructions are used, clinicians are advised to interpret their LDL's very cautiously until validational studies are available.

  18. Variational B-spline level-set: a linear filtering approach for fast deformable model evolution.

    Science.gov (United States)

    Bernard, Olivier; Friboulet, Denis; Thévenaz, Philippe; Unser, Michael

    2009-06-01

    In the field of image segmentation, most level-set-based active-contour approaches take advantage of a discrete representation of the associated implicit function. We present in this paper a different formulation where the implicit function is modeled as a continuous parametric function expressed on a B-spline basis. Starting from the active-contour energy functional, we show that this formulation allows us to compute the solution as a restriction of the variational problem on the space spanned by the B-splines. As a consequence, the minimization of the functional is directly obtained in terms of the B-spline coefficients. We also show that each step of this minimization may be expressed through a convolution operation. Because the B-spline functions are separable, this convolution may in turn be performed as a sequence of simple 1-D convolutions, which yields an efficient algorithm. As a further consequence, each step of the level-set evolution may be interpreted as a filtering operation with a B-spline kernel. Such filtering induces an intrinsic smoothing in the algorithm, which can be controlled explicitly via the degree and the scale of the chosen B-spline kernel. We illustrate the behavior of this approach on simulated as well as experimental images from various fields.

  19. Multi-level segment analysis: definition and application in turbulent systems

    Science.gov (United States)

    Wang, L. P.; Huang, Y. X.

    2015-06-01

    For many complex systems the interaction of different scales is among the most interesting and challenging features. It seems not very successful to extract the physical properties in different scale regimes by the existing approaches, such as the structure-function and Fourier spectrum method. Fundamentally, these methods have their respective limitations, for instance scale mixing, i.e. the so-called infrared and ultraviolet effects. To make improvements in this regard, a new method, multi-level segment analysis (MSA) based on the local extrema statistics, has been developed. Benchmark (fractional Brownian motion) verifications and the important case tests (Lagrangian and two-dimensional turbulence) show that MSA can successfully reveal different scaling regimes which have remained quite controversial in turbulence research. In general the MSA method proposed here can be applied to different dynamic systems in which the concepts of multiscale and multifractality are relevant.

  20. Automatic Multi-Level Thresholding Segmentation Based on Multi-Objective Optimization

    Directory of Open Access Journals (Sweden)

    L. DJEROU,

    2012-01-01

    Full Text Available In this paper, we present a new multi-level image thresholding technique, called Automatic Threshold based on Multi-objective Optimization "ATMO" that combines the flexibility of multi-objective fitness functions with the power of a Binary Particle Swarm Optimization algorithm "BPSO", for searching the "optimum" number of the thresholds and simultaneously the optimal thresholds of three criteria: the between-class variances criterion, the minimum error criterion and the entropy criterion. Some examples of test images are presented to compare our segmentation method, based on the multi-objective optimization approach with Otsu’s, Kapur’s and Kittler’s methods. Our experimental results show that the thresholding method based on multi-objective optimization is more efficient than the classical Otsu’s, Kapur’s and Kittler’s methods.

  1. Multi-level segment analysis: definition and application in turbulent systems

    CERN Document Server

    Wang, L P

    2015-01-01

    For many complex systems the interaction of different scales is among the most interesting and challenging features. It seems not very successful to extract the physical properties in different scale regimes by the existing approaches, such as structure-function and Fourier spectrum method. Fundamentally these methods have their respective limitations, for instance scale mixing, i.e. the so-called infrared and ultraviolet effects. To make improvement in this regard, a new method, multi-level segment analysis (MSA) based on the local extrema statistics, has been developed. Benchmark (fractional Brownian motion) verifications and the important case tests (Lagrangian and two-dimensional turbulence) show that MSA can successfully reveal different scaling regimes, which has been remaining quite controversial in turbulence research. In general the MSA method proposed here can be applied to different dynamic systems in which the concepts of multiscaling and multifractal are relevant.

  2. Semi-automatic lung segmentation of DCE-MRI data sets of 2-year old children after congenital diaphragmatic hernia repair: Initial results.

    Science.gov (United States)

    Zöllner, Frank G; Daab, Markus; Weidner, Meike; Sommer, Verena; Zahn, Katrin; Schaible, Thomas; Weisser, Gerald; Schoenberg, Stefan O; Neff, K Wolfgang; Schad, Lothar R

    2015-12-01

    In congenital diaphragmatic hernia (CDH), lung hypoplasia and secondary pulmonary hypertension are the major causes of death and severe disability. Based on new therapeutic strategies survival rates could be improved to up to 80%. However, after surgical repair of CDH, long-term follow-up of these pediatric patients is necessary. In this, dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) provides insights into the pulmonary microcirculation and might become a tool within the routine follow-up program of CDH patients. However, whole lung segmentation from DCE-MRI scans is tedious and automated procedures are warranted. Therefore, in this study, an approach to semi-automated lung segmentation is presented. Segmentation of the lung is obtained by calculating the cross correlation and the area under curve between all voxels in the data set and a reference region-of-interest (ROI), here the arterial input function (AIF). By applying an upper and lower threshold to the obtained maps and intersecting these, a final segmentation is reached. This approach was tested on twelve DCE-MRI data sets of 2-year old children after CDH repair. Segmentation accuracy was evaluated by comparing obtained automatic segmentations to manual delineations using the Dice overlap measure. Optimal thresholds for the cross correlation were 0.5/0.95 and 0.1/0.5 for the area under curve, respectively. The ipsilateral (left) lung showed reduced segmentation accuracy compared to the contralateral (right) lung. Average processing time was about 1.4s per data set. Average Dice score was 0.7±0.1 for the whole lung. In conclusion, initial results are promising. By our approach, whole lung segmentation is possible and a rapid evaluation of whole lung perfusion becomes possible. This might allow for a more detailed analysis of lung hypoplasia of children after CDH.

  3. The use of phrase-level prosodic information in lexical segmentation: evidence from word-spotting experiments in Korean.

    Science.gov (United States)

    Kim, Sahyang; Cho, Taehong

    2009-05-01

    This study investigated the role of phrase-level prosodic boundary information in word segmentation in Korean with two word-spotting experiments. In experiment 1, it was found that intonational cues alone helped listeners with lexical segmentation. Listeners paid more attention to local intonational cues (...H#L...) across the prosodic boundary than the intonational information within a prosodic phrase. The results imply that intonation patterns with high frequency are used, though not exclusively, in lexical segmentation. In experiment 2, final lengthening was added to see how multiple prosodic cues influence lexical segmentation. The results showed that listeners did not necessarily benefit from the presence of both intonational and final lengthening cues: Their performance was improved only when intonational information contained infrequent tonal patterns for boundary marking, showing only partially cumulative effects of prosodic cues. When the intonational information was optimal (frequent) for boundary marking, however, poorer performance was observed with final lengthening. This is arguably because the phrase-initial segmental allophonic cues for the accentual phrase were not matched with the prosodic cues for the intonational phrase. It is proposed that the asymmetrical use of multiple cues was due to interaction between prosodic and segmental information that are computed in parallel in lexical segmentation.

  4. Measuring Afterschool Program Quality Using Setting-Level Observational Approaches

    Science.gov (United States)

    Oh, Yoonkyung; Osgood, D. Wayne; Smith, Emilie P.

    2015-01-01

    The importance of afterschool hours for youth development is widely acknowledged, and afterschool settings have recently received increasing attention as an important venue for youth interventions, bringing a growing need for reliable and valid measures of afterschool quality. This study examined the extent to which the two observational tools,…

  5. Variational level set approach for automatic correction of multiplicative and additive intensity inhomogeneities in brain MR Images.

    Science.gov (United States)

    Verma, Nishant; Cowperthwaite, Matthew C; Markey, Mia K

    2012-01-01

    Retrospective correction of intensity inhomogeneities in magnetic resonance images of the brain is an essential pre-processing step before any sophisticated image analysis task can be performed. A popular choice when defining the degradation model in MR images is to use multiplicative intensity inhomogeneities that slowly varying across the image domain; this approach has been extensively used for bias field estimation. However, such a multiplicative model is often insufficient given that some of the most dominant physical causes of intensity inhomogeneities in MRI (such as nonuniform excitation strength) have a non-linear relationship with the receptor signal intensity. In this study, we consider a linear image degradation model with multiplicative and additive intensity inhomogeneity components. We propose a variational level sets approach that combines estimation of intensity inhomogeneity components during the image segmentation process. The evaluation of proposed approach on real MR image datasets demonstrate accurate estimation of multiplicative and additive intensity inhomogeneities improving brain tissue segmentation.

  6. An automated method for segmenting white matter lesions through multi-level morphometric feature classification with application to lupus

    Directory of Open Access Journals (Sweden)

    Mark Scully

    2010-04-01

    Full Text Available We demonstrate an automated, multi-level method to segment white matter brain lesions and apply it to lupus. The method makes use of local morphometric features based on multiple MR sequences, including T1-weighted, T2-weighted, and Fluid Attenuated Inversion Recovery. After preprocessing, including co-registration, brain extraction, bias correction, and intensity standardization, 49 features are calculated for each brain voxel based on local morphometry. At each level of segmentation a supervised classifier takes advantage of a different subset of the features to conservatively segment lesion voxels, passing on more difficult voxels to the next classifier. This multi-level approach allows for a fast lesion classification method with tunable trade-offs between sensitivity and specificity producing accuracy comparable to a human rater.

  7. Target Detection in SAR Images Based on a Level Set Approach

    Energy Technology Data Exchange (ETDEWEB)

    Marques, Regis C.P.; Medeiros, Fatima N.S.; Ushizima, Daniela M.

    2008-09-01

    This paper introduces a new framework for point target detection in synthetic aperture radar (SAR) images. We focus on the task of locating reflective small regions using alevel set based algorithm. Unlike most of the approaches in image segmentation, we address an algorithm which incorporates speckle statistics instead of empirical parameters and also discards speckle filtering. The curve evolves according to speckle statistics, initially propagating with a maximum upward velocity in homogeneous areas. Our approach is validated by a series of tests on synthetic and real SAR images and compared with three other segmentation algorithms, demonstrating that it configures a novel and efficient method for target detection purpose.

  8. Exploring Veteran Success through State-Level Administrative Data Sets

    Science.gov (United States)

    Massa, Tod; Gogia, Laura

    2017-01-01

    This chapter describes the benefits and challenges of state-level longitudinal data collection on student veterans and offers recommendations for optimizing collection and reporting for the advocacy of student veteran success.

  9. Multi-level SLIC superpixels segmentation method based on edge detection operator

    Science.gov (United States)

    Ni, Sen; Fu, Dongmei; Yang, Tao

    2016-10-01

    Simple linear iterative clustering (SLIC) super-pixel algorithm for its excellent performance and efficient border holding computational efficiency is widely used in image processing. But with the increase of the number of super-pixels, there will be a lot of redundancy in the image merging process. In this paper, we propose a multi-level super-pixels method based SLIC algorithm, which focuses on the target area to set up edge detection operator for generating multi-level super-pixels. Simulation results show that the proposed method ensures the accuracy of extraction and improves the computational efficiency.

  10. Trusting Politicians and Institutions in a Multi-Level Setting

    DEFF Research Database (Denmark)

    Hansen, Sune Welling; Kjær, Ulrik

    Trust in government and in politicians is a very crucial prerequisite for democratic processes. This goes not only for the national level of government but also for the regional and local. We make use of a large scale survey among citizens in Denmark to evaluate trust in politicians at different...... levels of government. And find that trust in local politicians is a bit higher than trust in MPs – especially among citizens who are well satisfied with the municipal service delivery. By introducing a number of municipal level variables in an MLA analysis, it is also found, that very chaotic government...... formation processes can negatively influence trust in the mayor and the councilors. Reaching out for the local power by being disloyal to one’s own party or by breaking deals already made can sometimes secure the mayoralty but it comes with a prize: lower trust among the electorate....

  11. A genus-level taxonomic review of primitively segmented spiders (Mesothelae, Liphistiidae

    Directory of Open Access Journals (Sweden)

    Xu Xin

    2015-03-01

    Full Text Available The spider suborder Mesothelae, containing a single extant family Liphistiidae, represents a species-poor and ancient lineage. These are conspicuous spiders that primitively retain a segmented abdomen and appendage-like spinnerets. While their classification history is nearly devoid of phylogenetic hypotheses, we here revise liphistiid genus level taxonomy based on original sampling throughout their Asian range, and on the evidence from a novel molecular phylogeny. By combining morphological and natural history evidence with phylogenetic relationships in the companion paper, we provide strong support for the monophyly of Liphistiidae, and the two subfamilies Liphistiinae and Heptathelinae. While the former only contains Liphistius Schiödte, 1849, a genus distributed in Indonesia (Sumatra, Laos, Malaysia, Myanmar, Thailand, we recognize and diagnose seven heptatheline genera, all but three removed from the synonymy of Heptathela: i Ganthela Xu & Kuntner, gen. n. with the type species G. yundingensis Xu, sp. n. is known from Fujian and Jiangxi, China; ii a rediagnosed Heptathela Kishida, 1923 is confined to the Japanese islands (Kyushu and Okinawa; iii Qiongthela Xu & Kuntner, gen. n. with the type species Q. baishensis Xu, sp. n. is distributed disjunctly in Hainan, China and Vietnam; iv Ryuthela Haupt, 1983 is confined to the Ryukyu archipelago (Japan; v Sinothela Haupt, 2003 inhabits Chinese areas north of Yangtze; vi Songthela Ono, 2000 inhabits southwest China and northern Vietnam; and vii Vinathela Ono, 2000 (Abcathela Ono, 2000, syn. n.; Nanthela Haupt, 2003, syn. n. is known from southeast China and Vietnam.

  12. Dictionary Based Image Segmentation

    DEFF Research Database (Denmark)

    Dahl, Anders Bjorholm; Dahl, Vedrana Andersen

    2015-01-01

    We propose a method for weakly supervised segmentation of natural images, which may contain both textured or non-textured regions. Our texture representation is based on a dictionary of image patches. To divide an image into separated regions with similar texture we use an implicit level sets...

  13. 76 FR 9004 - Public Comment on Setting Achievement Levels in Writing

    Science.gov (United States)

    2011-02-16

    ... Assessment Governing Board. ACTION: Notice, Public Comment on Setting Achievement Levels in Writing. SUMMARY... setting achievement levels for the new assessment of writing at grades 4, 8, and 12, the Governing Board... set achievement levels for the 2011 and 2013 NAEP writing assessments. Does the study design...

  14. Geologic setting of the low-level burial grounds

    Energy Technology Data Exchange (ETDEWEB)

    Lindsey, K.A.; Jaeger, G.K. [CH2M Hill Hanford, Inc., Richland, WA (United States); Slate, J.L. [Associated Western Universities Northwest, Richland, WA (United States); Swett, K.J.; Mercer, R.B. [Westinghouse Hanford Co., Richland, WA (United States)

    1994-10-13

    This report describes the regional and site specific geology of the Hanford Sites low-level burial grounds in the 200 East and West Areas. The report incorporates data from boreholes across the entire 200 Areas, integrating the geology of this area into a single framework. Geologic cross-sections, isopach maps, and structure contour maps of all major geological units from the top of the Columbia River Basalt Group to the surface are included. The physical properties and characteristics of the major suprabasalt sedimentary units also are discussed.

  15. DSA Image Blood Vessel Skeleton Extraction Based on Anti-concentration Diffusion and Level Set Method

    Science.gov (United States)

    Xu, Jing; Wu, Jian; Feng, Daming; Cui, Zhiming

    Serious types of vascular diseases such as carotid stenosis, aneurysm and vascular malformation may lead to brain stroke, which are the third leading cause of death and the number one cause of disability. In the clinical practice of diagnosis and treatment of cerebral vascular diseases, how to do effective detection and description of the vascular structure of two-dimensional angiography sequence image that is blood vessel skeleton extraction has been a difficult study for a long time. This paper mainly discussed two-dimensional image of blood vessel skeleton extraction based on the level set method, first do the preprocessing to the DSA image, namely uses anti-concentration diffusion model for the effective enhancement and uses improved Otsu local threshold segmentation technology based on regional division for the image binarization, then vascular skeleton extraction based on GMM (Group marching method) with fast sweeping theory was actualized. Experiments show that our approach not only improved the time complexity, but also make a good extraction results.

  16. Semi-Automated Detection of Surface Degradation on Bridges Based on a Level Set Method

    Science.gov (United States)

    Masiero, A.; Guarnieri, A.; Pirotti, F.; Vettore, A.

    2015-08-01

    Due to the effect of climate factors, natural phenomena and human usage, buildings and infrastructures are subject of progressive degradation. The deterioration of these structures has to be monitored in order to avoid hazards for human beings and for the natural environment in their neighborhood. Hence, on the one hand, monitoring such infrastructures is of primarily importance. On the other hand, unfortunately, nowadays this monitoring effort is mostly done by expert and skilled personnel, which follow the overall data acquisition, analysis and result reporting process, making the whole monitoring procedure quite expensive for the public (and private, as well) agencies. This paper proposes the use of a partially user-assisted procedure in order to reduce the monitoring cost and to make the obtained result less subjective as well. The developed method relies on the use of images acquired with standard cameras by even inexperienced personnel. The deterioration on the infrastructure surface is detected by image segmentation based on a level sets method. The results of the semi-automated analysis procedure are remapped on a 3D model of the infrastructure obtained by means of a terrestrial laser scanning acquisition. The proposed method has been successfully tested on a portion of a road bridge in Perarolo di Cadore (BL), Italy.

  17. Urine cardiac specific microRNA-1 level in patients with ST segment elevation acute myocardial infarction

    Institute of Scientific and Technical Information of China (English)

    段晓霞

    2013-01-01

    Objective To observe the change of urine level of cardiac specific microRNA-1(miR-1) in patients with ST segment elevation acute myocardial infarction(STEAMI) and investigate its potential applications. Methods Urine samples were collected from 20 STEAMI patients within

  18. High-level waste tank farm set point document

    Energy Technology Data Exchange (ETDEWEB)

    Anthony, J.A. III

    1995-01-15

    Setpoints for nuclear safety-related instrumentation are required for actions determined by the design authorization basis. Minimum requirements need to be established for assuring that setpoints are established and held within specified limits. This document establishes the controlling methodology for changing setpoints of all classifications. The instrumentation under consideration involve the transfer, storage, and volume reduction of radioactive liquid waste in the F- and H-Area High-Level Radioactive Waste Tank Farms. The setpoint document will encompass the PROCESS AREA listed in the Safety Analysis Report (SAR) (DPSTSA-200-10 Sup 18) which includes the diversion box HDB-8 facility. In addition to the PROCESS AREAS listed in the SAR, Building 299-H and the Effluent Transfer Facility (ETF) are also included in the scope.

  19. Are anti-arsonate antibody N-segments selected at both the protein and the DNA level?

    Science.gov (United States)

    Milner, E C; Meek, K D; Rathbun, G; Tucker, P; Capra, J D

    1986-02-01

    The V-D junctional residue at position 99 of AIJ anti-arsonate antibodies with a major cross-reactive idiotype is invariably a serine. This serine is not encoded in the germline of either the VH or DH gene segments nor can it be generated by intracodonic recombination between VH and DH. It must, therefore, be generated somatically (N segment addition) and selected by antigen. Sequence data indicate that the serine is frequently encoded by the uncommon TCG triplet. Here J. D. Capra and his colleagues discuss several explanations for the repeated appearance of this unusual codon at this position. They conclude that whatever the mechanism, N segment additions are selected at both protein and DNA levels.

  20. Setting the normalcy level of HI properties in isolated galaxies

    CERN Document Server

    Espada, D; Athanassoula, E; Bosma, A; Huchtmeier, W K; Leon, S; Lisenfeld, U; Sabater, J; Sulentic, J; Verley, S; Yun, M

    2009-01-01

    Studying the atomic gas (HI) properties of the most isolated galaxies is essential to quantify the effect that the environment exerts on this sensitive component of the interstellar medium. We observed and compiled HI data for a well defined sample of ~ 800 galaxies in the Catalog of Isolated Galaxies, as part of the AMIGA project (Analysis of the ISM in Isolated GAlaxies, http://amiga.iaa.es), which enlarges considerably previous samples used to quantify the HI deficiency in galaxies located in denser environments. By studying the shape of 182 HI profiles, we revisited the usually accepted result that, independently of the environment, more than half of the galaxies present a perturbed HI disk. In isolated galaxies this would certainly be a striking result if these are supposed to be the most relaxed systems, and has implications in the relaxation time scales of HI disks and the nature of the most frequent perturbing mechanisms in galaxies. Our sample likely exhibits the lowest HI asymmetry level in the loca...

  1. A study on traffic weaving segment level of service on Malaysia urban highway

    Science.gov (United States)

    Abdullah, Rohaya; Sadullah, Ahmad Farhan Mohd

    2017-07-01

    The objective of this research is to observe weaving problems, analyze the capacity of the weaving segment and to identify the behavior of the Malaysian driver at urban freeway weaving segment. Field data collected during non - peak hours at km. 138.6-138.2 (north bound) Seberang Jaya: Penang Bridge, km.16.8 to km.17.0 Sunway Mentari: Damansara-Puchong Highway and km.21.4 to km.21.9 Puchong Intan: Damansara-Puchong Highway. These segments behave as a bottleneck during peak hour. The data collected are traffic volume, vehicle composition and the road geometry. The drivers behavior pattern at the freeway weaving segment is observed. This research analyses by two different methodologies, the first analysis is by referring to the US Highway Capacity Manual 2010 and the second analysis through a modified method to suit the local traffic composition. The consideration of motorcycle and light heavy vehicle in the analysis lead to a different evaluation of weaving segment capacity. The analysis results show a slight difference between both methods. LOS, weaving speed and density prediction by the modified method is slightly higher than the HCM method. These results, suggest that the numbers of light heavy vehicle and motorcycle contribute to the amount of traffic volume because the value factors of Passenger Car Equivalent (PCE). The adoption of the widely used method without taking consideration of local traffic condition, might lead to improper road planning or design or road operation management.

  2. Characterizing corridor-level travel time distributions based on stochastic flows and segment capacities

    Directory of Open Access Journals (Sweden)

    Hao Lei

    2015-12-01

    Full Text Available Trip travel time reliability is an important measure of transportation system performance and a key factor affecting travelers’ choices. This paper explores a method for estimating travel time distributions for corridors that contain multiple bottlenecks. A set of analytical equations are used to calculate the number of queued vehicles ahead of a probe vehicle and further capture many important factors affecting travel times: the prevailing congestion level, queue discharge rates at the bottlenecks, and flow rates associated with merges and diverges. Based on multiple random scenarios and a vector of arrival times, the lane-by-lane delay at each bottleneck along the corridor is recursively estimated to produce a route-level travel time distribution. The model incorporates stochastic variations of bottleneck capacity and demand and explains the travel time correlations between sequential links. Its data needs are the entering and exiting flow rates and a sense of the lane-by-lane distribution of traffic at each bottleneck. A detailed vehicle trajectory data-set from the Next Generation SIMulation (NGSIM project has been used to verify that the estimated distributions are valid, and the sources of estimation error are examined.

  3. Structural Segmentation of Toru Takemitsu's Piece, Itinerant, by Advanced Level Music Graduate Students.

    Science.gov (United States)

    Ordoñana, Jose A; Laucirica, Ana

    2017-01-01

    This work attempts to study the way higher music graduate students segment a contemporary music work, Itinerant, and to understand the influence of musical feature on segmentation. It attempts to test the theory stating that saliences contribute to organising the music surface. The 42 students listened to the work several times and, in real time, they were requested to indicate the places on the score where they perceived structural boundaries. This work is characterised by its linearity, which could hinder identification of saliences and thereby, the establishment of structural boundaries. The participants show stability in the points of segmentation chosen. The results show significant coincidences among the participants in strategic places of the work, which leads us to conclude, in line with other researches, although in a work with different characteristics, that listeners can find a structural organisation in contemporary music that could allow them to understand it.

  4. Structural Segmentation of Toru Takemitsu’s Piece, Itinerant, by Advanced Level Music Graduate Students

    Science.gov (United States)

    Laucirica, Ana

    2017-01-01

    This work attempts to study the way higher music graduate students segment a contemporary music work, Itinerant, and to understand the influence of musical feature on segmentation. It attempts to test the theory stating that saliences contribute to organising the music surface. The 42 students listened to the work several times and, in real time, they were requested to indicate the places on the score where they perceived structural boundaries. This work is characterised by its linearity, which could hinder identification of saliences and thereby, the establishment of structural boundaries. The participants show stability in the points of segmentation chosen. The results show significant coincidences among the participants in strategic places of the work, which leads us to conclude, in line with other researches, although in a work with different characteristics, that listeners can find a structural organisation in contemporary music that could allow them to understand it. PMID:28515863

  5. Structural Segmentation of Toru Takemitsu’s Piece, Itinerant, by Advanced Level Music Graduate Students

    Directory of Open Access Journals (Sweden)

    Jose A. Ordoñana

    2017-05-01

    Full Text Available This work attempts to study the way higher music graduate students segment a contemporary music work, Itinerant, and to understand the influence of musical feature on segmentation. It attempts to test the theory stating that saliences contribute to organising the music surface. The 42 students listened to the work several times and, in real time, they were requested to indicate the places on the score where they perceived structural boundaries. This work is characterised by its linearity, which could hinder identification of saliences and thereby, the establishment of structural boundaries. The participants show stability in the points of segmentation chosen. The results show significant coincidences among the participants in strategic places of the work, which leads us to conclude, in line with other researches, although in a work with different characteristics, that listeners can find a structural organisation in contemporary music that could allow them to understand it.

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

    Directory of Open Access Journals (Sweden)

    Brian Johnson

    2015-01-01

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

  7. Segmenting the Net-Generation: Embracing the Next Level of Technology

    Science.gov (United States)

    Smith, Russell K.

    2014-01-01

    A segmentation study is used to partition college students into groups that are more or less likely to adopt tablet technology as a learning tool. Because the college population chosen for study presently relies upon laptop computers as their primary learning device, tablet technology represents a "next step" in technology. Student…

  8. Development of new auxiliary basis functions of the Karlsruhe segmented contracted basis sets including diffuse basis functions (def2-SVPD, def2-TZVPPD, and def2-QVPPD) for RI-MP2 and RI-CC calculations.

    Science.gov (United States)

    Hellweg, Arnim; Rappoport, Dmitrij

    2015-01-14

    We report optimized auxiliary basis sets for use with the Karlsruhe segmented contracted basis sets including moderately diffuse basis functions (Rappoport and Furche, J. Chem. Phys., 2010, 133, 134105) in resolution-of-the-identity (RI) post-self-consistent field (post-SCF) computations for the elements H-Rn (except lanthanides). The errors of the RI approximation using optimized auxiliary basis sets are analyzed on a comprehensive test set of molecules containing the most common oxidation states of each element and do not exceed those of the corresponding unaugmented basis sets. During these studies an unsatisfying performance of the def2-SVP and def2-QZVPP auxiliary basis sets for Barium was found and improved sets are provided. We establish the versatility of the def2-SVPD, def2-TZVPPD, and def2-QZVPPD basis sets for RI-MP2 and RI-CC (coupled-cluster) energy and property calculations. The influence of diffuse basis functions on correlation energy, basis set superposition error, atomic electron affinity, dipole moments, and computational timings is evaluated at different levels of theory using benchmark sets and showcase examples.

  9. Evaluation of image segmentation based on type-2 fuzzy sets%图像分割质量评价的二型模糊集方法

    Institute of Scientific and Technical Information of China (English)

    邓廷权; 焦颖颖

    2011-01-01

    Evaluation for quality of image segmentation is an essential stage and has been extensively studied in image analysis and computer vision.In view of advantages of type-2 fuzzy sets in describing inaccuracy of objects, criteria for image segmentation evaluation are characterized by using type-2 fuzzy sets.Two kinds of fuzzy metric of type-2 fuzzy sets are introduced and a model is established to evaluate quality of image segmentation.Simulated experiments show the validity and practicability of the proposed model.%图像分割质量的评价是图像分割技术和算法研究的重要环节,在图像分析和计算机视觉中有着重要应用.依据二型模糊集在不精确性描述方面的独特优势,提出一种图像分割评判指标的二型模糊集表示方法,引入两种二型模糊集的模糊性度量作为图像分割质量的评判标准,构建图像分割质量评价模型.模拟实验验证了该模型的有效性和实用性.

  10. 基于特征点集搜索的三维序列livewire分割方法%3D livewire segmentation based on feature point set searching

    Institute of Scientific and Technical Information of China (English)

    金勇; 蒋建国; 郝世杰; 鲁清凯; 李鸿; 杨青青

    2011-01-01

    On account of the large amount of the three-dimensional(3D) medical image data sets such as computed tomography images(CT) and magnetic resonance image(MRI), the manual image segmentation is time consuming and operator-dependent. Considering the similarity of shape and texture of the segmentation targets between adjacent slices, a 3D livewire segmentation method based on feature point set searching is proposed in this paper. With minimal human interaction, the effective segmentation of objectives in 3D medical image data is achieved. The experiments on the lung CT and cancer MRI show that the temporal cost of the segmentation dramatically falls while its accuracy is close to the manual one.%三维计算机断层图像(CT)或核磁共振图像(MRI)数据量较大,仅仅依靠人工分割整个数据集相当耗时,且分割结果因操作者不同而带有主观性.三维序列图像数据相邻切面间的分割目标形状和纹理通常具有一定的相关性,文章充分利用了这样的先验知识,提出了基于特征点集搜索的三维序列Live Wire 分割方法,旨在尽可能少的人工交互下,完成整个三维医学图像数据中目标的有效分割.实验中,对肺部CT图像和肿瘤MRI图像进行了三维分割,在分割精度与人工分割相当的前提下,分割速度大大提高.

  11. A local level set method based on a finite element method for unstructured meshes

    Energy Technology Data Exchange (ETDEWEB)

    Ngo, Long Cu; Choi, Hyoung Gwon [School of Mechanical Engineering, Seoul National University of Science and Technology, Seoul (Korea, Republic of)

    2016-12-15

    A local level set method for unstructured meshes has been implemented by using a finite element method. A least-square weighted residual method was employed for implicit discretization to solve the level set advection equation. By contrast, a direct re-initialization method, which is directly applicable to the local level set method for unstructured meshes, was adopted to re-correct the level set function to become a signed distance function after advection. The proposed algorithm was constructed such that the advection and direct reinitialization steps were conducted only for nodes inside the narrow band around the interface. Therefore, in the advection step, the Gauss–Seidel method was used to update the level set function using a node-by-node solution method. Some benchmark problems were solved by using the present local level set method. Numerical results have shown that the proposed algorithm is accurate and efficient in terms of computational time.

  12. An Optimized, Grid Independent, Narrow Band Data Structure for High Resolution Level Sets

    DEFF Research Database (Denmark)

    Nielsen, Michael Bang; Museth, Ken

    2004-01-01

    Level sets have recently proven successful in many areas of computer graphics including water simulations and geometric modeling. However, current implementations of these level set methods are limited by factors such as computational efficiency, storage requirements and the restriction to a doma...... difference schemes typically used to numerically solve the level set equation on fixed uniform grids.  ......Level sets have recently proven successful in many areas of computer graphics including water simulations and geometric modeling. However, current implementations of these level set methods are limited by factors such as computational efficiency, storage requirements and the restriction to a domain...... enforced by the convex boundaries of an underlying cartesian computational grid. Here we present a novel very memory efficient narrow band data structure, dubbed the Sparse Grid, that enables the representation of grid independent high resolution level sets. The key features our new data structure are...

  13. Object-level change detection based on full-scale image segmentation and its application to Wenchuan Earthquake

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Aiming at object fragmentation and poor detection results caused by discontinuous segmentation scale in object-level change detection,a new object-level change detection method based on the full-scale object tree is presented in this paper.The core idea of this new algorithm is to establish the full-scale object tree based on convexity model theory and integrate full-scale image segmentation techniques and change detection into the whole process.Some Wenchuan Earthquake images are taken as an example to discuss the new method for earthquake damage detection and evaluation in urban area,landslide detection,and extraction of barrier lake boundary.The application shows that the new method is robust and it provides an advanced tool for the quantitative detection and evaluation of earthquake damage.

  14. A unified methodology based on sparse field level sets and boosting algorithms for false positives reduction in lung nodules detection.

    Science.gov (United States)

    Saien, Soudeh; Moghaddam, Hamid Abrishami; Fathian, Mohsen

    2017-08-09

    This work aims to develop a unified methodology for the false positives reduction in lung nodules computer-aided detection schemes. The 3D region of each detected nodule candidate is first reconstructed using the sparse field method for accurately segmenting the objects. This technique enhances the level set modeling by restricting the computations to a narrow band near the evolving curve. Then, a set of 2D and 3D relevant features are extracted for each segmented candidate. Subsequently, a hybrid undersampling/boosting algorithm called RUSBoost is applied to analyze the features and discriminate real nodules from non-nodules. The performance of the proposed scheme was evaluated by using 70 CT images, randomly selected from the Lung Image Database Consortium and containing 198 nodules. Applying RUSBoost classifier exhibited a better performance than some commonly used classifiers. It effectively reduced the average number of FPs to only 3.9 per scan based on a fivefold cross-validation. The practical implementation, applicability for different nodule types and adaptability in handling the imbalanced data classification insure the improvement in lung nodules detection by utilizing this new approach.

  15. Assessment of the relationship between morphological emphysema phenotype and corresponding pulmonary perfusion pattern on a segmental level

    Energy Technology Data Exchange (ETDEWEB)

    Bryant, Mark; Kauczor, Hans-Ulrich [University of Heidelberg, Department of Diagnostic and Interventional Radiology, Heidelberg (Germany); Member of German Lung Research Center DZL, Translational Lung Research Center TLRC-H, Heidelberg (Germany); Ley, Sebastian [Chirurgische Klinik Dr. Rinecker, Department of Diagnostic and Interventional Radiology, Munich (Germany); Ludwig Maximilians University, Department of Clinical Radiology, Munich (Germany); Eberhardt, Ralf; Herth, Felix [Thoraxklinik University of Heidelberg, Department of Pneumology and Critical Care Medicine, Heidelberg (Germany); Member of German Lung Research Center DZL, Translational Lung Research Center TLRC-H, Heidelberg (Germany); Menezes, Ravi [University of Toronto, Medical Imaging, Toronto (Canada); Sedlaczek, Oliver [University of Heidelberg, Department of Diagnostic and Interventional Radiology, Heidelberg (Germany); German Cancer Research Center, Department of Radiology, Heidelberg (Germany); Member of German Lung Research Center DZL, Translational Lung Research Center TLRC-H, Heidelberg (Germany); Ley-Zaporozhan, Julia [University of Heidelberg, Department of Diagnostic and Interventional Radiology, Heidelberg (Germany); Ludwig Maximilians University, Department of Clinical Radiology, Munich (Germany)

    2015-01-15

    Distinct morphological emphysema phenotypes were assessed by CT to show characteristic perfusion defect patterns. Forty-one patients with severe emphysema (GOLD III/IV) underwent three-dimensional high resolution computed tomography (3D-HRCT) and contrast-enhanced magnetic resonance (MR) perfusion. 3D-HRCT data was visually analyzed for emphysema phenotyping and quantification by consensus of three experts in chest-radiology. The predominant phenotype per segment was categorized as normal, centrilobular, panlobular or paraseptal. Segmental lung perfusion was visually analyzed using six patterns of pulmonary perfusion (1-normal; 2-mild homogeneous reduction in perfusion; 3-heterogeneous perfusion without focal defects; 4-heterogeneous perfusion with focal defects; 5-heterogeneous absence of perfusion; 6-homogeneous absence of perfusion), with the extent of the defect given as a percentage. 730 segments were evaluated. CT categorized 566 (78 %) as centrilobular, 159 (22 %) as panlobular and 5 (<1 %) as paraseptal with no normals. Scores with regards to MR perfusion patterns were: 1-0; 2-0; 3-28 (4 %); 4-425 (58 %); 5-169 (23 %); 6-108 (15 %). The predominant perfusion pattern matched as follows: 70 % centrilobular emphysema - heterogeneous perfusion with focal defects (score 4); 42 % panlobular - homogeneous absence of perfusion (score 5); and 43 % panlobular - heterogeneous absence of perfusion (score 6). MR pulmonary perfusion patterns correlate with the CT phenotype at a segmental level in patients with severe emphysema. (orig.)

  16. A new approach for the sequence spaces of fuzzy level sets with the partial metric

    Directory of Open Access Journals (Sweden)

    Uğur Kadak

    2014-03-01

    Full Text Available In this paper, we investigate the classical sets of sequences of fuzzy numbers by using partial metric which is based on a partial ordering. Some elementary notions and concepts for partial metric and fuzzy level sets are given. In addition, several necessary and sufficient conditions for partial completeness are established by means of fuzzy level sets. Finally, we give some illustrative examples and present some results between fuzzy and partial metric spaces.

  17. Cervical anterior hybrid technique with bi-level Bryan artificial disc replacement and adjacent segment fusion for cervical myelopathy over three consecutive segments.

    Science.gov (United States)

    Chen, Jiang; Xu, Lin; Jia, Yu-Song; Sun, Qi; Li, Jin-Yu; Zheng, Chen-Ying; Bai, Chun-Xiao; Yu, Qin-Sheng

    2016-05-01

    This study aimed to assess the preliminary clinical efficacy and feasibility of the hybrid technique for multilevel cervical myelopathy. Considering the many shortcomings of traditional treatment methods for multilevel cervical degenerative myelopathy, hybrid surgery (bi-level Bryan artificial disc [Medtronic Sofamor Danek, Memphis, TN, USA] replacement and anterior cervical discectomy and fusion) should be considered. Between March 2006 and November 2012, 108 patients (68 men and 40 women, average age 45years) underwent hybrid surgery. Based on the Japanese Orthopaedic Association (JOA) score, Neck Disability Index (NDI), and Odom's criteria, the clinical symptoms and neurological function before and after surgery were evaluated. Mean surgery duration was 90minutes, with average blood loss of 30mL. Mean follow-up duration was 36months. At the final follow-up, the mean JOA (± standard deviation) scores were significantly higher compared with preoperative values (15.08±1.47 versus 9.18±1.22; P<0.01); meanwhile, NDI values were markedly decreased (12.32±1.03 versus 42.68±1.83; P<0.01). Using Odom's criteria, the clinical outcomes were rated as excellent (76 patients), good (22 patients), fair (six patients), and poor (four patients). These findings indicate that the hybrid method provides an effective treatment for cervical myelopathy over three consecutive segments, ensuring a good clinical outcome. Copyright © 2015 Elsevier Ltd. All rights reserved.

  18. Brain Tumour Segmentation based on Extremely Randomized Forest with high-level features.

    Science.gov (United States)

    Pinto, Adriano; Pereira, Sergio; Correia, Higino; Oliveira, J; Rasteiro, Deolinda M L D; Silva, Carlos A

    2015-08-01

    Gliomas are among the most common and aggressive brain tumours. Segmentation of these tumours is important for surgery and treatment planning, but also for follow-up evaluations. However, it is a difficult task, given that its size and locations are variable, and the delineation of all tumour tissue is not trivial, even with all the different modalities of the Magnetic Resonance Imaging (MRI). We propose a discriminative and fully automatic method for the segmentation of gliomas, using appearance- and context-based features to feed an Extremely Randomized Forest (Extra-Trees). Some of these features are computed over a non-linear transformation of the image. The proposed method was evaluated using the publicly available Challenge database from BraTS 2013, having obtained a Dice score of 0.83, 0.78 and 0.73 for the complete tumour, and the core and the enhanced regions, respectively. Our results are competitive, when compared against other results reported using the same database.

  19. Prognostic Value of Plasma Intermedin Level in Patients With Non-ST-Segment Elevation Acute Coronary Syndrome.

    Science.gov (United States)

    Li, Pengyang; Shi, Lin; Han, Yalei; Zhao, Yuntao; Qi, Yongfen; Wang, Bin

    2016-04-01

    Intermedin (IMD), an autocrine/paracrine biologically active peptide, plays a critical role in maintaining vascular homeostasis. Recent research has shown that high plasma levels of IMD are associated with poor outcomes for patients with ST-segment elevation acute myocardial infarction. However, the prognostic utility of IMD levels in non-ST-segment elevation acute coronary syndrome (NSTE-ACS) has not yet been investigated. We hypothesized that the level of plasma IMD would have prognostic value in patients with NSTE-ACS. Plasma IMD was determined by radioimmunoassay in 132 NSTE-ACS patients on admission to hospital and 132 sex- and age-matched healthy-control subjects. Major adverse cardiovascular events (MACEs), including death, heart failure, hospitalization, and acute myocardial infarction, were noted during follow-up. In total, 23 patients suffered MACEs during the follow-up period (mean 227 ± 118 days, range 2-421 days). Median IMD levels were higher in NSTE-ACS patients than control [320.0 (250.9/384.6) vs. 227.2 (179.7/286.9) pg/mL, P variables and NT-proBNP showed that the risk of MACEs increased by a factor of 12.96 (95% CI, 3.26-49.42; P <0.001) with high IMD levels (at the cut-off value). IMD has potential as a prognostic biomarker for predicting MACEs in patients with NSTE-ACS.

  20. PCA and level set based non-rigid image registration for MRI and Paxinos-Watson atlas of rat brain

    Science.gov (United States)

    Cai, Chao; Liu, Ailing; Ding, Mingyue; Zhou, Chengping

    2007-12-01

    Image registration provides the ability to geometrically align one dataset with another. It is a basic task in a great variety of biomedical imaging applications. This paper introduced a novel three-dimensional registration method for Magnetic Resonance Image (MRI) and Paxinos-Watson Atlas of rat brain. For the purpose of adapting to a large range and non-linear deformation between MRI and atlas in higher registration accuracy, based on the segmentation of rat brain, we chose the principle components analysis (PCA) automatically performing the linear registration, and then, a level set based nonlinear registration correcting some small distortions. We implemented this registration method in a rat brain 3D reconstruction and analysis system. Experiments have demonstrated that this method can be successfully applied to registering the low resolution and noise affection MRI with Paxinos-Watson Atlas of rat brain.

  1. Automatic Measurement of Thalamic Diameter in 2-D Fetal Ultrasound Brain Images Using Shape Prior Constrained Regularized Level Sets.

    Science.gov (United States)

    Sridar, Pradeeba; Kumar, Ashnil; Li, Changyang; Woo, Joyce; Quinton, Ann; Benzie, Ron; Peek, Michael J; Feng, Dagan; Kumar, R Krishna; Nanan, Ralph; Kim, Jinman

    2017-07-01

    We derived an automated algorithm for accurately measuring the thalamic diameter from 2-D fetal ultrasound (US) brain images. The algorithm overcomes the inherent limitations of the US image modality: nonuniform density; missing boundaries; and strong speckle noise. We introduced a "guitar" structure that represents the negative space surrounding the thalamic regions. The guitar acts as a landmark for deriving the widest points of the thalamus even when its boundaries are not identifiable. We augmented a generalized level-set framework with a shape prior and constraints derived from statistical shape models of the guitars; this framework was used to segment US images and measure the thalamic diameter. Our segmentation method achieved a higher mean Dice similarity coefficient, Hausdorff distance, specificity, and reduced contour leakage when compared to other well-established methods. The automatic thalamic diameter measurement had an interobserver variability of -0.56 ± 2.29 mm compared to manual measurement by an expert sonographer. Our method was capable of automatically estimating the thalamic diameter, with the measurement accuracy on par with clinical assessment. Our method can be used as part of computer-assisted screening tools that automatically measure the biometrics of the fetal thalamus; these biometrics are linked to neurodevelopmental outcomes.

  2. LEVEL SET METHOD FOR TOPOLOGICAL OPTIMIZATION APPLYING TO STRUCTURE,MECHANISM AND MATERIAL DESIGNS

    Institute of Scientific and Technical Information of China (English)

    Mei Yulin; Wang Xiaoming

    2004-01-01

    Based on a level set model,a topology optimization method has been suggested recently.It uses a level set to express the moving structural boundary,which can flexibly handle complex topological changes.By combining vector level set models with gradient projection technology,the level set method for topological optimization is extended to a topological optimization problem with multi-constraints,multi-materials and multi-load cases.Meanwhile,an appropriate nonlinear speed mapping is established in the tangential space of the active constraints for a fast convergence.Then the method is applied to structure designs,mechanism and material designs by a number of benchmark examples.Finally,in order to further improve computational efficiency and overcome the difficulty that the level set method cannot generate new material interfaces during the optimization process,the topological derivative analysis is incorporated into the level set method for topological optimization,and a topological derivative and level set algorithm for topological optimization is proposed.

  3. Metric Learning for Hyperspectral Image Segmentation

    Science.gov (United States)

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

    2011-01-01

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

  4. Level set discrete element method for three-dimensional computations with triaxial case study

    Science.gov (United States)

    Kawamoto, Reid; Andò, Edward; Viggiani, Gioacchino; Andrade, José E.

    2016-06-01

    In this paper, we outline the level set discrete element method (LS-DEM) which is a discrete element method variant able to simulate systems of particles with arbitrary shape using level set functions as a geometric basis. This unique formulation allows seamless interfacing with level set-based characterization methods as well as computational ease in contact calculations. We then apply LS-DEM to simulate two virtual triaxial specimens generated from XRCT images of experiments and demonstrate LS-DEM's ability to quantitatively capture and predict stress-strain and volume-strain behavior observed in the experiments.

  5. An explicit finite volume element method for solving characteristic level set equation on triangular grids

    Institute of Scientific and Technical Information of China (English)

    Sutthisak Phongthanapanich; Pramote Dechaumphai

    2011-01-01

    Level set methods are widely used for predicting evolutions of complex free surface topologies,such as the crystal and crack growth,bubbles and droplets deformation,spilling and breaking waves,and two-phase flow phenomena.This paper presents a characteristic level set equation which is derived from the two-dimensional level set equation by using the characteristic-based scheme.An explicit finite volume element method is developed to discretize the equation on triangular grids.Several examples are presented to demonstrate the performance of the proposed method for calculating interface evolutions in time.The proposed level set method is also coupled with the Navier-Stokes equations for two-phase immiscible incompressible flow analysis with surface tension.The Rayleigh-Taylor instability problem is used to test and evaluate the effectiveness of the proposed scheme.

  6. 3D level set methods for evolving fronts on tetrahedral meshes with adaptive mesh refinement

    Science.gov (United States)

    Morgan, Nathaniel R.; Waltz, Jacob I.

    2017-05-01

    The level set method is commonly used to model dynamically evolving fronts and interfaces. In this work, we present new methods for evolving fronts with a specified velocity field or in the surface normal direction on 3D unstructured tetrahedral meshes with adaptive mesh refinement (AMR). The level set field is located at the nodes of the tetrahedral cells and is evolved using new upwind discretizations of Hamilton-Jacobi equations combined with a Runge-Kutta method for temporal integration. The level set field is periodically reinitialized to a signed distance function using an iterative approach with a new upwind gradient. The details of these level set and reinitialization methods are discussed. Results from a range of numerical test problems are presented.

  7. A LEVEL SET BASED SHAPE OPTIMIZATION METHOD FOR AN ELLIPTIC OBSTACLE PROBLEM

    KAUST Repository

    Burger, Martin

    2011-04-01

    In this paper, we construct a level set method for an elliptic obstacle problem, which can be reformulated as a shape optimization problem. We provide a detailed shape sensitivity analysis for this reformulation and a stability result for the shape Hessian at the optimal shape. Using the shape sensitivities, we construct a geometric gradient flow, which can be realized in the context of level set methods. We prove the convergence of the gradient flow to an optimal shape and provide a complete analysis of the level set method in terms of viscosity solutions. To our knowledge this is the first complete analysis of a level set method for a nonlocal shape optimization problem. Finally, we discuss the implementation of the methods and illustrate its behavior through several computational experiments. © 2011 World Scientific Publishing Company.

  8. On the Morse-Sard Property and Level Sets of Sobolev and BV Functions

    CERN Document Server

    Bourgain, Jean; Kristensen, Jan

    2010-01-01

    We establish Luzin $N$ and Morse-Sard properties for $BV_2$-functions defined on open domains in the plane. Using these results we prove that almost all level sets are finite disjoint unions of Lipschitz arcs whose tangent vectors are of bounded variation. In the case of $W^{2,1}$-functions we strengthen the conclusion and show that almost all level sets are finite disjoint unions of $C^1$-arcs whose tangent vectors are absolutely continuous.

  9. Identifying Attributes of CO2 Leakage Zones in Shallow Aquifers Using a Parametric Level Set Method

    Science.gov (United States)

    Sun, A. Y.; Islam, A.; Wheeler, M.

    2016-12-01

    Leakage through abandoned wells and geologic faults poses the greatest risk to CO2 storage permanence. For shallow aquifers, secondary CO2 plumes emanating from the leak zones may go undetected for a sustained period of time and has the greatest potential to cause large-scale and long-term environmental impacts. Identification of the attributes of leak zones, including their shape, location, and strength, is required for proper environmental risk assessment. This study applies a parametric level set (PaLS) method to characterize the leakage zone. Level set methods are appealing for tracking topological changes and recovering unknown shapes of objects. However, level set evolution using the conventional level set methods is challenging. In PaLS, the level set function is approximated using a weighted sum of basis functions and the level set evolution problem is replaced by an optimization problem. The efficacy of PaLS is demonstrated through recovering the source zone created by CO2 leakage into a carbonate aquifer. Our results show that PaLS is a robust source identification method that can recover the approximate source locations in the presence of measurement errors, model parameter uncertainty, and inaccurate initial guesses of source flux strengths. The PaLS inversion framework introduced in this work is generic and can be adapted for any reactive transport model by switching the pre- and post-processing routines.

  10. An adaptive level set approach for incompressible two-phase flows

    Energy Technology Data Exchange (ETDEWEB)

    Sussman, M.; Almgren, A.S.; Bell, J.B. [and others

    1997-04-01

    In Sussman, Smereka and Osher, a numerical method using the level set approach was formulated for solving incompressible two-phase flow with surface tension. In the level set approach, the interface is represented as the zero level set of a smooth function; this has the effect of replacing the advection of density, which has steep gradients at the interface, with the advection of the level set function, which is smooth. In addition, the interface can merge or break up with no special treatment. The authors maintain the level set function as the signed distance from the interface in order to robustly compute flows with high density ratios and stiff surface tension effects. In this work, they couple the level set scheme to an adaptive projection method for the incompressible Navier-Stokes equations, in order to achieve higher resolution of the interface with a minimum of additional expense. They present two-dimensional axisymmetric and fully three-dimensional results of air bubble and water drop computations.

  11. A discontinuous Galerkin conservative level set scheme for interface capturing in multiphase flows

    Energy Technology Data Exchange (ETDEWEB)

    Owkes, Mark, E-mail: mfc86@cornell.edu; Desjardins, Olivier

    2013-09-15

    The accurate conservative level set (ACLS) method of Desjardins et al. [O. Desjardins, V. Moureau, H. Pitsch, An accurate conservative level set/ghost fluid method for simulating turbulent atomization, J. Comput. Phys. 227 (18) (2008) 8395–8416] is extended by using a discontinuous Galerkin (DG) discretization. DG allows for the scheme to have an arbitrarily high order of accuracy with the smallest possible computational stencil resulting in an accurate method with good parallel scaling. This work includes a DG implementation of the level set transport equation, which moves the level set with the flow field velocity, and a DG implementation of the reinitialization equation, which is used to maintain the shape of the level set profile to promote good mass conservation. A near second order converging interface curvature is obtained by following a height function methodology (common amongst volume of fluid schemes) in the context of the conservative level set. Various numerical experiments are conducted to test the properties of the method and show excellent results, even on coarse meshes. The tests include Zalesak’s disk, two-dimensional deformation of a circle, time evolution of a standing wave, and a study of the Kelvin–Helmholtz instability. Finally, this novel methodology is employed to simulate the break-up of a turbulent liquid jet.

  12. Multiphase permittivity imaging using absolute value electrical capacitance tomography data and a level set algorithm.

    Science.gov (United States)

    Al Hosani, E; Soleimani, M

    2016-06-28

    Multiphase flow imaging is a very challenging and critical topic in industrial process tomography. In this article, simulation and experimental results of reconstructing the permittivity profile of multiphase material from data collected in electrical capacitance tomography (ECT) are presented. A multiphase narrowband level set algorithm is developed to reconstruct the interfaces between three- or four-phase permittivity values. The level set algorithm is capable of imaging multiphase permittivity by using one set of ECT measurement data, so-called absolute value ECT reconstruction, and this is tested with high-contrast and low-contrast multiphase data. Simulation and experimental results showed the superiority of this algorithm over classical pixel-based image reconstruction methods. The multiphase level set algorithm and absolute ECT reconstruction are presented for the first time, to the best of our knowledge, in this paper and critically evaluated. This article is part of the themed issue 'Supersensing through industrial process tomography'. © 2016 The Author(s).

  13. Setting Healthcare Priorities at the Macro and Meso Levels: A Framework for Evaluation

    Directory of Open Access Journals (Sweden)

    Edwine W. Barasa

    2015-11-01

    Full Text Available Background Priority setting in healthcare is a key determinant of health system performance. However, there is no widely accepted priority setting evaluation framework. We reviewed literature with the aim of developing and proposing a framework for the evaluation of macro and meso level healthcare priority setting practices. Methods We systematically searched Econlit, PubMed, CINAHL, and EBSCOhost databases and supplemented this with searches in Google Scholar, relevant websites and reference lists of relevant papers. A total of 31 papers on evaluation of priority setting were identified. These were supplemented by broader theoretical literature related to evaluation of priority setting. A conceptual review of selected papers was undertaken. Results Based on a synthesis of the selected literature, we propose an evaluative framework that requires that priority setting practices at the macro and meso levels of the health system meet the following conditions: (1 Priority setting decisions should incorporate both efficiency and equity considerations as well as the following outcomes; (a Stakeholder satisfaction, (b Stakeholder understanding, (c Shifted priorities (reallocation of resources, and (d Implementation of decisions. (2 Priority setting processes should also meet the procedural conditions of (a Stakeholder engagement, (b Stakeholder empowerment, (c Transparency, (d Use of evidence, (e Revisions, (f Enforcement, and (g Being grounded on community values. Conclusion Available frameworks for the evaluation of priority setting are mostly grounded on procedural requirements, while few have included outcome requirements. There is, however, increasing recognition of the need to incorporate both consequential and procedural considerations in priority setting practices. In this review, we adapt an integrative approach to develop and propose a framework for the evaluation of priority setting practices at the macro and meso levels that draws from

  14. Adaptive multi-level conditional random fields for detection and segmentation of small enhanced pathology in medical images.

    Science.gov (United States)

    Karimaghaloo, Zahra; Arnold, Douglas L; Arbel, Tal

    2016-01-01

    Detection and segmentation of large structures in an image or within a region of interest have received great attention in the medical image processing domains. However, the problem of small pathology detection and segmentation still remains an unresolved challenge due to the small size of these pathologies, their low contrast and variable position, shape and texture. In many contexts, early detection of these pathologies is critical in diagnosis and assessing the outcome of treatment. In this paper, we propose a probabilistic Adaptive Multi-level Conditional Random Fields (AMCRF) with the incorporation of higher order cliques for detecting and segmenting such pathologies. In the first level of our graphical model, a voxel-based CRF is used to identify candidate lesions. In the second level, in order to further remove falsely detected regions, a new CRF is developed that incorporates higher order textural features, which are invariant to rotation and local intensity distortions. At this level, higher order textures are considered together with the voxel-wise cliques to refine boundaries and is therefore adaptive. The proposed algorithm is tested in the context of detecting enhancing Multiple Sclerosis (MS) lesions in brain MRI, where the problem is further complicated as many of the enhancing voxels are associated with normal structures (i.e. blood vessels) or noise in the MRI. The algorithm is trained and tested on large multi-center clinical trials from Relapsing-Remitting MS patients. The effect of several different parameter learning and inference techniques is further investigated. When tested on 120 cases, the proposed method reaches a lesion detection rate of 90%, with very few false positive lesion counts on average, ranging from 0.17 for very small (3-5 voxels) to 0 for very large (50+ voxels) regions. The proposed model is further tested on a very large clinical trial containing 2770 scans where a high sensitivity of 91% with an average false positive

  15. The Effect of Antiproteinuric Treatment on Lipid Levels in Patients with Focal Segmental Glomerulosclerosis and Membranous Glomerulopathy

    Directory of Open Access Journals (Sweden)

    Gürsu, Meltem

    2013-01-01

    Full Text Available OBJECTIVE: The primary objective of our study was to investigate effects of antiproteinuric treatment on lipid levels of patients with idiopathic focal segmental glomerulosclerosis (FSGS or membranous glomerulonephritis (MGN.MATERIAL and METHODS: The clinical and laboratory data of the patients were recorded at three-month intervals during 18 months of follow-up. Patients with non-nephrotic proteinuria without hypoalbuminemia received conservative treatment while those with more severe disease received steroid therapy as well. Lipid parameters in the two groups and the factors effective on these parameters were investigated.RESULTS: Sixty eight patients (36 with FSGS, 32 with MG were included. The mean age of the patients and the follow-up period were 39.6±16.6 years and 16.4±8.9months, respectively. 36 (53% patients received steroid therapy. The percentage of patients taking antilipemic treatment was statistically significantly higher in the group taking steroid therapy. LDL cholesterol levels were higher at the beginning in patients taking steroid therapy but the difference disappeared after the ninth month. Total and LDL cholesterol levels showed a negative correlation with albumin levels and a positive correlation with proteinuria level.CONCLUSION: Treatment of hyperlipidemia in nephrotic syndrome should be directed towards increasing serum albumin levels, and therefore treatment of the glomerular disease. Antilipidemic therapies should be considered in patients who do not respond to other antiproteinuric treatment.

  16. Appropriate criteria set for personnel promotion across organizational levels using analytic hierarchy process (AHP

    Directory of Open Access Journals (Sweden)

    Charles Noven Castillo

    2017-01-01

    Full Text Available Currently, there has been limited established specific set of criteria for personnel promotion to each level of the organization. This study is conducted in order to develop a personnel promotion strategy by identifying specific sets of criteria for each level of the organization. The complexity of identifying the criteria set along with the subjectivity of these criteria require the use of multi-criteria decision-making approach particularly the analytic hierarchy process (AHP. Results show different sets of criteria for each management level which are consistent with several frameworks in literature. These criteria sets would help avoid mismatch of employee skills and competencies and their job, and at the same time eliminate the issues in personnel promotion such as favouritism, glass ceiling, and gender and physical attractiveness preference. This work also shows that personality and traits, job satisfaction and experience and skills are more critical rather than social capital across different organizational levels. The contribution of this work is in identifying relevant criteria in developing a personnel promotion strategy across organizational levels.

  17. A Level Set Discontinuous Galerkin Method for Free Surface Flows - and Water-Wave Modeling

    DEFF Research Database (Denmark)

    Grooss, Jesper

    2005-01-01

    We present a discontinuous Galerkin method on a fully unstructured grid for the modeling of unsteady incompressible fluid flows with free surfaces. The surface is modeled by a level set technique. We describe the discontinuous Galerkin method in general, and its application to the flow equations....... accurately. We present techniques for reinitialization, and outline the strengths and weaknesses of the level set method. Through a few numerical tests, the robustness and versatility of the proposed scheme is confirmed.......We present a discontinuous Galerkin method on a fully unstructured grid for the modeling of unsteady incompressible fluid flows with free surfaces. The surface is modeled by a level set technique. We describe the discontinuous Galerkin method in general, and its application to the flow equations....... The deferred correction method is applied on the fluid flow equations and show good results in periodic domains. We describe the design of a level set method for the free surface modeling. The level set utilize the high order accurate discontinuous Galerkin method fully and represent smooth surfaces very...

  18. Pituitary Adenoma Segmentation

    CERN Document Server

    Egger, Jan; Kuhnt, Daniela; Freisleben, Bernd; Nimsky, Christopher

    2011-01-01

    Sellar tumors are approximately 10-15% among all intracranial neoplasms. The most common sellar lesion is the pituitary adenoma. Manual segmentation is a time-consuming process that can be shortened by using adequate algorithms. In this contribution, we present a segmentation method for pituitary adenoma. The method is based on an algorithm we developed recently in previous work where the novel segmentation scheme was successfully used for segmentation of glioblastoma multiforme and provided an average Dice Similarity Coefficient (DSC) of 77%. This scheme is used for automatic adenoma segmentation. In our experimental evaluation, neurosurgeons with strong experiences in the treatment of pituitary adenoma performed manual slice-by-slice segmentation of 10 magnetic resonance imaging (MRI) cases. Afterwards, the segmentations were compared with the segmentation results of the proposed method via the DSC. The average DSC for all data sets was 77.49% +/- 4.52%. Compared with a manual segmentation that took, on the...

  19. Using multi-channel level sets to measure the cytoplasmic localization of HCMV pUL97 in GFP-B-gal fusion constructs.

    Science.gov (United States)

    Held, Christian; Webel, Rike; Palmisano, Ralf; Hutterer, Corina; Marschall, Manfred; Wittenberg, Thomas

    2014-04-01

    Human cytomegalovirus UL97-encoded protein kinase (pUL97) phosphorylates cellular and viral proteins and is critical for viral replication. To quantify the efficiency of nuclear translocation and to elucidate the role of putative nuclear localization signal (NLS) elements, immunofluorescence analysis of different pUL97 expression constructs was performed. Since manual quantitation of respective expression levels lacks objectivity and reproducibility, and is time-consuming as well, a computer-based model is established. This model enables objective quantitation of the degree of cytoplasmic localization λ. To determine the degree of cytoplasmic localization of different pUL97-GFP-β-gal fusion proteins automatically, a multi-channel segmentation of the nucleus and cytoplasm of transfected HeLa cells is performed in DAPI and GFP micrographs. A watershed transform-based segmentation scheme is used for the segmentation of the cell nuclei. Subsequently, the cytoplasm is segmented using a fast marching level set method. Based on the segmentation of cell nuclei and cytoplasm, λ can be determined for each HeLa cell by quantitation of the ratio of average signal intensity outside and inside the nucleus. The degree of cytoplasmic localization of an individual construct is then determined by evaluating the average and standard deviation of λ for the corresponding HeLa cells. Evaluation demonstrates that nuclear transport of pUL97 is a multilayered mechanism resulting in different efficiencies of nuclear translocation between a small and a large isoform and objective quantitation of the cytoplasmic localization is possible with a high accuracy (96.7% and 94.3%). Copyright © 2013 Elsevier B.V. All rights reserved.

  20. A Level Set Discontinuous Galerkin Method for Free Surface Flows - and Water-Wave Modeling

    DEFF Research Database (Denmark)

    Grooss, Jesper

    2005-01-01

    We present a discontinuous Galerkin method on a fully unstructured grid for the modeling of unsteady incompressible fluid flows with free surfaces. The surface is modeled by a level set technique. We describe the discontinuous Galerkin method in general, and its application to the flow equations....... The deferred correction method is applied on the fluid flow equations and show good results in periodic domains. We describe the design of a level set method for the free surface modeling. The level set utilize the high order accurate discontinuous Galerkin method fully and represent smooth surfaces very...... equations in time are discussed. We investigate theory of di erential algebraic equations, and connect the theory to current methods for solving the unsteady fluid flow equations. We explore the use of a semi-implicit spectral deferred correction method having potential to achieve high temporal order...

  1. Level set methods for detonation shock dynamics using high-order finite elements

    Energy Technology Data Exchange (ETDEWEB)

    Dobrev, V. A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Grogan, F. C. [Univ. of California, San Diego, CA (United States); Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Kolev, T. V. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Rieben, R [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Tomov, V. Z. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2017-05-26

    Level set methods are a popular approach to modeling evolving interfaces. We present a level set ad- vection solver in two and three dimensions using the discontinuous Galerkin method with high-order nite elements. During evolution, the level set function is reinitialized to a signed distance function to maintain ac- curacy. Our approach leads to stable front propagation and convergence on high-order, curved, unstructured meshes. The ability of the solver to implicitly track moving fronts lends itself to a number of applications; in particular, we highlight applications to high-explosive (HE) burn and detonation shock dynamics (DSD). We provide results for two- and three-dimensional benchmark problems as well as applications to DSD.

  2. Edge-Aware Level Set Diffusion and Bilateral Filtering Reconstruction for Image Magnification

    Institute of Scientific and Technical Information of China (English)

    Hua Huang; Yu Zang; Paul L.Rosin; Chun Qi

    2009-01-01

    In this paper we propose an image magnification reconstruction method. In recent years many interpolation algorithms have been proposed for image magnification, but all of them have defects to some degree, such as jaggies and blurring. To solve these problems, we propose applying post-processing which consists of edge-aware level set diffusion and bilateral filtering. After the initial interpolation, the contours of the image are identified. Next, edge-aware level set diffusion is applied to these significant contours to remove the jaggies, followed by bilateral filtering at the same locations to reduce the blurring created by the initial interpolation and level set diffusion. These processes produce sharp contours without jaggies and preserve the details of the image. Results show that the overall RMS error of our method barely increases while the contour smoothness and sharpness are substantially improved.

  3. Aerostructural Level Set Topology Optimization for a Common Research Model Wing

    Science.gov (United States)

    Dunning, Peter D.; Stanford, Bret K.; Kim, H. Alicia

    2014-01-01

    The purpose of this work is to use level set topology optimization to improve the design of a representative wing box structure for the NASA common research model. The objective is to minimize the total compliance of the structure under aerodynamic and body force loading, where the aerodynamic loading is coupled to the structural deformation. A taxi bump case was also considered, where only body force loads were applied. The trim condition that aerodynamic lift must balance the total weight of the aircraft is enforced by allowing the root angle of attack to change. The level set optimization method is implemented on an unstructured three-dimensional grid, so that the method can optimize a wing box with arbitrary geometry. Fast matching and upwind schemes are developed for an unstructured grid, which make the level set method robust and efficient. The adjoint method is used to obtain the coupled shape sensitivities required to perform aerostructural optimization of the wing box structure.

  4. A LEVEL SET METHOD FOR STRUCTURAL TOPOLOGY OPTIMIZATION WITH MULTI-CONSTRAINTS AND MULTI-MATERIALS

    Institute of Scientific and Technical Information of China (English)

    MEI Yulin; WANG Xiaoming

    2004-01-01

    Combining the vector level set model, the shape sensitivity analysis theory with the gradient projection technique, a level set method for topology optimization with multi-constraints and multi-materials is presented in this paper. The method implicitly describes structural material interfaces by the vector level set and achieves the optimal shape and topology through the continuous evolution of the material interfaces in the structure. In order to increase computational efficiency for a fast convergence, an appropriate nonlinear speed mapping is established in the tangential space of the active constraints. Meanwhile, in order to overcome the numerical instability of general topology optimization problems, the regularization with the mean curvature flow is utilized to maintain the interface smoothness during the optimization process. The numerical examples demonstrate that the approach possesses a good flexibility in handling topological changes and gives an interface representation in a high fidelity, compared with other methods based on explicit boundary variations in the literature.

  5. Types and Levels of Bioaerosols in Healthcare and Community Indoor Settings in Iran

    Directory of Open Access Journals (Sweden)

    Ghasemian

    2016-09-01

    Full Text Available Context Bioaerosols are associated with a wide spectrum of health effects, including infections and contagious diseases, acute toxicities, allergies, and even cancer. Evidence Acquisition Previous publications describing research conducted in healthcare and community settings during the years 2001 - 2016 were included in this analysis. The words bioaerosol, contamination, bacteria, fungi, viruses, and Iran were explored via the use of search engines such as PubMed, Google, Google Scholar, and Science Direct. A total of 28 studies were found. Results The levels of bacterial contamination were higher than those found in the fungal species. The most isolated of the bacterial species were S. aureus (38.24% and Micrococci (31.6%, and the most isolated of the fungal species were Penicillium (32.28% and Aspergillus spp (22.78%. The highest levels of contamination were detected in infectious disease (ID settings (mean = 91 ± 86 cfu/m3 for bacteria and 27 ± 24 for fungi. Moreover, levels of indoor air contamination were lower than the world health organization (WHO standards, with the exception of S. aureus at 201 cfu/m3 and 189 cfu/m3 in infectious disease (ID and intensive care unit (ICU settings, respectively. In terms of geographic area and cultural differences, the numbers of bacterial and fungal agents were not significantly different (i.e., North versus South and East versus West. Moisture levels were significantly related to air contamination (pv = 0.02. Conclusions The levels of air contamination inside hospital and healthcare settings were lower than the WHO mean standard. Active air sampling methods are necessary for measuring bioaerosol contamination. There were no significant differences in the levels of contamination found in various indoor settings in Iran. Efficient ventilation systems and contamination prevention or minimization are necessary for these settings.

  6. On intermediate level sets of two-dimensional discrete Gaussian Free Field

    OpenAIRE

    Biskup, Marek; Louidor, Oren

    2016-01-01

    We consider the discrete Gaussian Free Field (DGFF) in scaled-up (square-lattice) versions of suitably regular continuum domains $D\\subset\\mathbb C$ and describe the scaling limit, including local structure, of the level sets at heights growing as a $\\lambda$-multiple of the height of the absolute maximum, for any $\\lambda\\in(0,1)$. We prove that, in the scaling limit, the scaled spatial position of a typical point $x$ sampled from this level set is distributed according to a Liouville Quantu...

  7. Individual-and Setting-Level Correlates of Secondary Traumatic Stress in Rape Crisis Center Staff.

    Science.gov (United States)

    Dworkin, Emily R; Sorell, Nicole R; Allen, Nicole E

    2016-02-01

    Secondary traumatic stress (STS) is an issue of significant concern among providers who work with survivors of sexual assault. Although STS has been studied in relation to individual-level characteristics of a variety of types of trauma responders, less research has focused specifically on rape crisis centers as environments that might convey risk or protection from STS, and no research to knowledge has modeled setting-level variation in correlates of STS. The current study uses a sample of 164 staff members representing 40 rape crisis centers across a single Midwestern state to investigate the staff member-and agency-level correlates of STS. Results suggest that correlates exist at both levels of analysis. Younger age and greater severity of sexual assault history were statistically significant individual-level predictors of increased STS. Greater frequency of supervision was more strongly related to secondary stress for non-advocates than for advocates. At the setting level, lower levels of supervision and higher client loads agency-wide accounted for unique variance in staff members' STS. These findings suggest that characteristics of both providers and their settings are important to consider when understanding their STS.

  8. Influence of reconstruction settings on the performance of adaptive thresholding algorithms for FDG-PET image segmentation in radiotherapy planning.

    Science.gov (United States)

    Matheoud, Roberta; Della Monica, Patrizia; Loi, Gianfranco; Vigna, Luca; Krengli, Marco; Inglese, Eugenio; Brambilla, Marco

    2011-01-30

    The purpose of this study was to analyze the behavior of a contouring algorithm for PET images based on adaptive thresholding depending on lesions size and target-to-background (TB) ratio under different conditions of image reconstruction parameters. Based on this analysis, the image reconstruction scheme able to maximize the goodness of fit of the thresholding algorithm has been selected. A phantom study employing spherical targets was designed to determine slice-specific threshold (TS) levels which produce accurate cross-sectional areas. A wide range of TB ratio was investigated. Multiple regression methods were used to fit the data and to construct algorithms depending both on target cross-sectional area and TB ratio, using various reconstruction schemes employing a wide range of iteration number and amount of postfiltering Gaussian smoothing. Analysis of covariance was used to test the influence of iteration number and smoothing on threshold determination. The degree of convergence of ordered-subset expectation maximization (OSEM) algorithms does not influence TS determination. Among these approaches, the OSEM at two iterations and eight subsets with a 6-8 mm post-reconstruction Gaussian three-dimensional filter provided the best fit with a coefficient of determination R² = 0.90 for cross-sectional areas ≤ 133 mm² and R² = 0.95 for cross-sectional areas > 133 mm². The amount of post-reconstruction smoothing has been directly incorporated in the adaptive thresholding algorithms. The feasibility of the method was tested in two patients with lymph node FDG accumulation and in five patients using the bladder to mimic an anatomical structure of large size and uniform uptake, with satisfactory results. Slice-specific adaptive thresholding algorithms look promising as a reproducible method for delineating PET target volumes with good accuracy.

  9. Demons versus level-set motion registration for coronary 18F-sodium fluoride PET

    Science.gov (United States)

    Rubeaux, Mathieu; Joshi, Nikhil; Dweck, Marc R.; Fletcher, Alison; Motwani, Manish; Thomson, Louise E.; Germano, Guido; Dey, Damini; Berman, Daniel S.; Newby, David E.; Slomka, Piotr J.

    2016-03-01

    Ruptured coronary atherosclerotic plaques commonly cause acute myocardial infarction. It has been recently shown that active microcalcification in the coronary arteries, one of the features that characterizes vulnerable plaques at risk of rupture, can be imaged using cardiac gated 18F-sodium fluoride (18F-NaF) PET. We have shown in previous work that a motion correction technique applied to cardiac-gated 18F-NaF PET images can enhance image quality and improve uptake estimates. In this study, we further investigated the applicability of different algorithms for registration of the coronary artery PET images. In particular, we aimed to compare demons vs. level-set nonlinear registration techniques applied for the correction of cardiac motion in coronary 18F-NaF PET. To this end, fifteen patients underwent 18F-NaF PET and prospective coronary CT angiography (CCTA). PET data were reconstructed in 10 ECG gated bins; subsequently these gated bins were registered using demons and level-set methods guided by the extracted coronary arteries from CCTA, to eliminate the effect of cardiac motion on PET images. Noise levels, target-to-background ratios (TBR) and global motion were compared to assess image quality. Compared to the reference standard of using only diastolic PET image (25% of the counts from PET acquisition), cardiac motion registration using either level-set or demons techniques almost halved image noise due to the use of counts from the full PET acquisition and increased TBR difference between 18F-NaF positive and negative lesions. The demons method produces smoother deformation fields, exhibiting no singularities (which reflects how physically plausible the registration deformation is), as compared to the level-set method, which presents between 4 and 8% of singularities, depending on the coronary artery considered. In conclusion, the demons method produces smoother motion fields as compared to the level-set method, with a motion that is physiologically

  10. Analysis of linear measurements on 3D surface models using CBCT data segmentation obtained by automatic standard pre-set thresholds in two segmentation software programs: an in vitro study.

    Science.gov (United States)

    Poleti, Marcelo Lupion; Fernandes, Thais Maria Freire; Pagin, Otávio; Moretti, Marcela Rodrigues; Rubira-Bullen, Izabel Regina Fischer

    2016-01-01

    The aim of this in vitro study was to evaluate the reliability and accuracy of linear measurements on three-dimensional (3D) surface models obtained by standard pre-set thresholds in two segmentation software programs. Ten mandibles with 17 silica markers were scanned for 0.3-mm voxels in the i-CAT Classic (Imaging Sciences International, Hatfield, PA, USA). Twenty linear measurements were carried out by two observers two times on the 3D surface models: the Dolphin Imaging 11.5 (Dolphin Imaging & Management Solutions, Chatsworth, CA, USA), using two filters(Translucent and Solid-1), and in the InVesalius 3.0.0 (Centre for Information Technology Renato Archer, Campinas, SP, Brazil). The physical measurements were made by another observer two times using a digital caliper on the dry mandibles. Excellent intra- and inter-observer reliability for the markers, physical measurements, and 3D surface models were found (intra-class correlation coefficient (ICC) and Pearson's r ≥ 0.91). The linear measurements on 3D surface models by Dolphin and InVesalius software programs were accurate (Dolphin Solid-1 > InVesalius > Dolphin Translucent). The highest absolute and percentage errors were obtained for the variable R1-R1 (1.37 mm) and MF-AC (2.53 %) in the Dolphin Translucent and InVesalius software, respectively. Linear measurements on 3D surface models obtained by standard pre-set thresholds in the Dolphin and InVesalius software programs are reliable and accurate compared with physical measurements. Studies that evaluate the reliability and accuracy of the 3D models are necessary to ensure error predictability and to establish diagnosis, treatment plan, and prognosis in a more realistic way.

  11. Some numerical studies of interface advection properties of level set method

    Indian Academy of Sciences (India)

    A Salih; S Ghosh Moulic

    2009-04-01

    In this paper, we discuss the results of a series of tests carried out to assess the level set methodology for capturing interfaces between two immiscible fluids. The tests are designed to investigate the accuracy of convection process, the preservation of interface shape, and the mass conservation properties of individual fluids. These test cases involve the advection of interfaces of different shapes exposed to translation, rotation, deformation, and shear flow. Prescribed solenoidal velocity fields are used and no attempt is made to couple the advection of the level set function with the momentum equations. For the solution of level set equation we have employed first-order upwind scheme, MacCormack method, second-order ENO scheme, and fifth-order WENO scheme. Our studies show that the level set method perform well when higher-order schemes are used for the solution of advection equation. However, for certain type of shearing and vortical velocity fields mass conservation is an issue on coarser meshes even with higher order schemes. Finer mesh must be used in such situations to reduce numerical diffusion.

  12. Controlling entrainment in the smoke cloud using level set-based front tracking

    Directory of Open Access Journals (Sweden)

    Eckhard Dietze

    2015-01-01

    Full Text Available Although large-eddy simulation (LES has been shown to produce a reasonable representation of the turbulent circulations within the stratocumulus-topped boundary layer, it has difficulties to accurately predict cloud-top entrainment rates. In this paper, we present a front-tracking algorithm for LES to untangle the numerical and physical contributions to entrainment. Instead of resolving the cloud-top inversion, we treat it as a discontinuity separating the boundary layer from the free atmosphere and use the level set method to track its location. We apply our method to the smoke cloud test case as presented by Bretherton et al. (1999 which is simpler than stratocumulus in that it is only driven by radiative cooling avoiding evaporative feedbacks on entrainment. We present three-dimensional LES results with and without use of the level set method varying the grid resolution and the flux limiter. With the level set method, we prescribe zero entrainment and use this case to evaluate our method's ability to maintain a non-entraining smoke-cloud layer. We use an empirically-based entrainment law to estimate numerical errors. With the level set method, the prescribed entrainment rate was maintained with errors about one order of magnitude smaller than the entrainment errors found in the standard LES. At the same time, the dependence of the entrainment errors on the choice of the limiter was reduced by more than a factor of 10.

  13. A level-set based topology optimization using the element connectivity parameterization method

    NARCIS (Netherlands)

    Van Dijk, N.P.; Yoon, G.H.; Van Keulen, F.; Langelaar, M.

    2010-01-01

    This contribution presents a novel and versatile approach to geometrically nonlinear topology optimization by combining the level-set method with the element connectivity parameterization method or ECP. The combined advantages of both methods open up the possibility to treat a wide range of optimiza

  14. Re-Setting the Concentration Levels of Students in Higher Education: An Exploratory Study

    Science.gov (United States)

    Burke, Lisa A.; Ray, Ruth

    2008-01-01

    Evidence suggests that college students' concentration levels are limited and hard to maintain. Even though relevant in higher education, scant empirical research exists on interventions to "re-set" their concentration during a college lecture. Using a within-subjects design, four active learning interventions are administered across two…

  15. Pushing the Boundaries: Level-set Methods and Geometrical Nonlinearities in Structural Topology Optimization

    NARCIS (Netherlands)

    Van Dijk, N.P.

    2012-01-01

    This thesis aims at understanding and improving topology optimization techniques focusing on density-based level-set methods and geometrical nonlinearities. Central in this work are the numerical modeling of the mechanical response of a design and the consistency of the optimization process itself.

  16. Two Surface-Tension Formulations For The Level Set Interface-Tracking Method

    Energy Technology Data Exchange (ETDEWEB)

    Shepel, S.V.; Smith, B.L

    2005-03-01

    The paper describes a comparative study of two surface-tension models for the Level Set interface tracking method. In both models, the surface tension is represented as a body force, concentrated near the interface, but the technical implementation of the two options is different. The first is based on a traditional Level Set approach, in which the surface tension is distributed over a narrow band around the interface using a smoothed Delta function. In the second model, which is based on the integral form of the fluid-flow equations, the force is imposed only in those computational cells through which the interface passes. Both models have been incorporated into the Finite-Element/Finite-Volume Level Set method, previously implemented into the commercial Computational Fluid Dynamics (CFD) code CFX-4. A critical evaluation of the two models, undertaken in the context of four standard Level Set benchmark problems, shows that the first model, based on the smoothed Delta function approach, is the more general, and more robust, of the two. (author)

  17. Changes in cardiac specific microRNA-208a level in peripheral blood in ST segment elevation acute myocardial infarction patients

    Institute of Scientific and Technical Information of China (English)

    姚怡

    2013-01-01

    Objective To observe serum cardiac specific microRNA-208a(miR-208a) levels in ST segment elevation acute myocardial infarction(STEAMI) patients,and to explore the role of serum miR-208a levels in the diagnosis of STEAMI. Methods The serum miR-208a concentrations were assessed within 12 hours after STEAMI,while

  18. A GPU Accelerated Discontinuous Galerkin Conservative Level Set Method for Simulating Atomization

    Science.gov (United States)

    Jibben, Zechariah J.

    This dissertation describes a process for interface capturing via an arbitrary-order, nearly quadrature free, discontinuous Galerkin (DG) scheme for the conservative level set method (Olsson et al., 2005, 2008). The DG numerical method is utilized to solve both advection and reinitialization, and executed on a refined level set grid (Herrmann, 2008) for effective use of processing power. Computation is executed in parallel utilizing both CPU and GPU architectures to make the method feasible at high order. Finally, a sparse data structure is implemented to take full advantage of parallelism on the GPU, where performance relies on well-managed memory operations. With solution variables projected into a kth order polynomial basis, a k + 1 order convergence rate is found for both advection and reinitialization tests using the method of manufactured solutions. Other standard test cases, such as Zalesak's disk and deformation of columns and spheres in periodic vortices are also performed, showing several orders of magnitude improvement over traditional WENO level set methods. These tests also show the impact of reinitialization, which often increases shape and volume errors as a result of level set scalar trapping by normal vectors calculated from the local level set field. Accelerating advection via GPU hardware is found to provide a 30x speedup factor comparing a 2.0GHz Intel Xeon E5-2620 CPU in serial vs. a Nvidia Tesla K20 GPU, with speedup factors increasing with polynomial degree until shared memory is filled. A similar algorithm is implemented for reinitialization, which relies on heavier use of shared and global memory and as a result fills them more quickly and produces smaller speedups of 18x.

  19. Integrated SFM Techniques Using Data Set from Google Earth 3d Model and from Street Level

    Science.gov (United States)

    Inzerillo, L.

    2017-08-01

    Structure from motion (SfM) represents a widespread photogrammetric method that uses the photogrammetric rules to carry out a 3D model from a photo data set collection. Some complex ancient buildings, such as Cathedrals, or Theatres, or Castles, etc. need to implement the data set (realized from street level) with the UAV one in order to have the 3D roof reconstruction. Nevertheless, the use of UAV is strong limited from the government rules. In these last years, Google Earth (GE) has been enriched with the 3D models of the earth sites. For this reason, it seemed convenient to start to test the potentiality offered by GE in order to extract from it a data set that replace the UAV function, to close the aerial building data set, using screen images of high resolution 3D models. Users can take unlimited "aerial photos" of a scene while flying around in GE at any viewing angle and altitude. The challenge is to verify the metric reliability of the SfM model carried out with an integrated data set (the one from street level and the one from GE) aimed at replace the UAV use in urban contest. This model is called integrated GE SfM model (i-GESfM). In this paper will be present a case study: the Cathedral of Palermo.

  20. [Segmentation Method for Liver Organ Based on Image Sequence Context].

    Science.gov (United States)

    Zhang, Meiyun; Fang, Bin; Wang, Yi; Zhong, Nanchang

    2015-10-01

    In view of the problems of more artificial interventions and segmentation defects in existing two-dimensional segmentation methods and abnormal liver segmentation errors in three-dimensional segmentation methods, this paper presents a semi-automatic liver organ segmentation method based on the image sequence context. The method takes advantage of the existing similarity between the image sequence contexts of the prior knowledge of liver organs, and combines region growing and level set method to carry out semi-automatic segmentation of livers, along with the aid of a small amount of manual intervention to deal with liver mutation situations. The experiment results showed that the liver segmentation algorithm presented in this paper had a high precision, and a good segmentation effect on livers which have greater variability, and can meet clinical application demands quite well.

  1. Using the level set method in geodynamical modeling of multi-material flows and Earth's free surface

    NARCIS (Netherlands)

    Hillebrand, B.; Thieulot, C.; Geenen, T.; Van Den Berg, A. P.; Spakman, W.

    2014-01-01

    The level set method allows for tracking material surfaces in 2-D and 3-D flow modeling and is well suited for applications of multi-material flow modeling. The level set method utilizes smooth level set functions to define material interfaces, which makes the method stable and free of oscillations

  2. Using the level set method in geodynamical modeling of multi-material flows and Earth's free surface

    NARCIS (Netherlands)

    Hillebrand, B.; Thieulot, C.; Geenen, T.; Van Den Berg, A. P.; Spakman, W.

    2014-01-01

    The level set method allows for tracking material surfaces in 2-D and 3-D flow modeling and is well suited for applications of multi-material flow modeling. The level set method utilizes smooth level set functions to define material interfaces, which makes the method stable and free of oscillations

  3. Significant Association of Serum Adiponectin and Creatine Kinase-MB Levels in ST-Segment Elevation Myocardial Infarction.

    Science.gov (United States)

    Natsukawa, Tomoaki; Maeda, Norikazu; Fukuda, Shiro; Yamaoka, Masaya; Fujishima, Yuya; Nagao, Hirofumi; Sato, Fumi; Nishizawa, Hitoshi; Sawano, Hirotaka; Hayashi, Yasuyuki; Funahashi, Tohru; Kai, Tatsuro; Shimomura, Iichiro

    2017-08-01

    Adiponectin, an adipocyte-specific secretory protein, abundantly exists in the blood stream while its concentration paradoxically decreases in obesity. Hypoadiponectinemia is one of risks of cardiovascular diseases. However, impact of serum adiponectin concentration on acute ischemic myocardial damages has not been fully clarified. The present study investigated the association of serum adiponectin and creatine kinase (CK)-MB levels in subjects with ST-segment elevation myocardial infarction (STEMI). This study is a physician-initiated observational study and is also registered with the University Hospital Medical Information Network (Number: UMIN 000014418). Patients were admitted to Senri Critical Care Medical Center, given a diagnosis of STEMI, and treated by primary percutaneous coronary intervention (PCI). Finally, 49 patients were enrolled and the association of serum adiponectin, CK-MB, and clinical features were mainly analyzed. Serum adiponectin levels decreased rapidly and reached the bottom at 24 hours after recanalization. Such reduction of serum adiponectin was inversely correlated with the area under the curve (AUC) of serum CK-MB (p=0.013). Serum adiponectin concentrations were inversely correlated with AUC of serum CK-MB. In multivariate analysis, serum adiponectin concentration on admission (p=0.002) and collateral (p=0.037) were significantly and independently correlated with serum AUC of CK-MB. Serum AUC of CK-MB in STEMI subjects was significantly associated with serum adiponectin concentration on admission and reduction of serum adiponectin levels from baseline to bottom. The present study may provide a possibility that serum adiponectin levels at acute phase are useful in the prediction for prognosis after PCI-treated STEMI subjects.

  4. Determination of the Integrated Sidelobe Level of Sets of Rotated Legendre Sequences

    CERN Document Server

    Haboba, Salvador Javier; Setti, Gianluca

    2010-01-01

    Sequences sets with low aperiodic auto- and cross-correlations play an important role in many applications like communications, radar and other active sensing applications. The use of antipodal sequences reduces hardware requirements while increases the difficult of the task of signal design. In this paper we present a method for the computation of the Integrated Sidelobe Level (ISL), and we use it to calculate the asymptotic expression for the ISL of a set of sequences formed by different rotations of a Legendre sequence.

  5. Evaluation of internal carotid artery segmentation by InsightSNAP

    Science.gov (United States)

    Spangler, Emily L.; Brown, Christopher; Roberts, John A.; Chapman, Brian E.

    2007-03-01

    Quantification of cervical carotid geometry may facilitate improved clinical decision making and scientific discovery. We set out to evaluate the ability of InsightSNAP (ITK-SNAP), an open-source segmentation program for 3D medical images (http://www.itksnap.org, version 1.4), to semi-automatically segment internal carotid arteries. A sample of five individuals (three normal volunteers, and two diseased patients) were imaged with an MR exam consisting of a MOTSA TOF MRA image volume and multiple black blood images acquired with different contrast weightings. Comparisons were made to a manual segmentation created during simultaneous evaluation of the MOTSA image and the various black blood images (typically PD-weighted, T1-weighted, and T2-weighted). These individuals were selected as a training set to determine acceptable parameters for ITK-SNAP's semi-automatic level sets segmentation method. The conclusion from this training set was that the initial thresholding (assigning probabilities to the intensities of image pixels) in the image pre-processing step was most important to obtaining an acceptable segmentation. Unfortunately no consistent trends emerged in how this threshold should be chosen. Figures of percent over- and under-segmentation were computed as a means of comparing the hand segmented and semi-automatically segmented internal carotids. Overall the under-segmentation by ITK-SNAP (voxels included in the manual segmentation but not in the semiautomated segmentation) was 10.94% +/- 6.35% while the over-segmentation (voxels excluded in the manual segmentation but included in the semi-automated segmentation) was 8.16% +/- 4.40% defined by reference to the total number of voxels included in the manual segmentation.

  6. Parallel level-set methods on adaptive tree-based grids

    Science.gov (United States)

    Mirzadeh, Mohammad; Guittet, Arthur; Burstedde, Carsten; Gibou, Frederic

    2016-10-01

    We present scalable algorithms for the level-set method on dynamic, adaptive Quadtree and Octree Cartesian grids. The algorithms are fully parallelized and implemented using the MPI standard and the open-source p4est library. We solve the level set equation with a semi-Lagrangian method which, similar to its serial implementation, is free of any time-step restrictions. This is achieved by introducing a scalable global interpolation scheme on adaptive tree-based grids. Moreover, we present a simple parallel reinitialization scheme using the pseudo-time transient formulation. Both parallel algorithms scale on the Stampede supercomputer, where we are currently using up to 4096 CPU cores, the limit of our current account. Finally, a relevant application of the algorithms is presented in modeling a crystallization phenomenon by solving a Stefan problem, illustrating a level of detail that would be impossible to achieve without a parallel adaptive strategy. We believe that the algorithms presented in this article will be of interest and useful to researchers working with the level-set framework and modeling multi-scale physics in general.

  7. Noncooperative Iris Segmentation

    Directory of Open Access Journals (Sweden)

    Elsayed Mostafa

    2012-01-01

    Full Text Available In noncooperative iris recognition one should deal with uncontrolled behavior of the subject as well as uncontrolled lighting conditions. That means eyelids and eyelashes occlusion, non uniform intensities, reflections, imperfect focus, and orientation among the others are to be considered. To cope with this situation a noncooperative iris segmentation algorithm based on numerically stable direct least squares fitting of ellipses model and modified Chan-Vese model (local binary fitting energy with variational level set formulation is to be proposed. The proposed algorithm is tested using CASIA-IrisV3.

  8. Therapeutic and diagnostic set for irradiation the cell lines in low level laser therapy

    Science.gov (United States)

    Gryko, Lukasz; Zajac, Andrzej; Gilewski, Marian; Szymanska, Justyna; Goralczyk, Krzysztof

    2014-05-01

    In the paper is presented optoelectronic diagnostic set for standardization the biostimulation procedures performed on cell lines. The basic functional components of the therapeutic set are two digitally controlled illuminators. They are composed of the sets of semiconductor emitters - medium power laser diodes and high power LEDs emitting radiation in wide spectral range from 600 nm to 1000 nm. Emitters are coupled with applicator by fibre optic and optical systems that provides uniform irradiation of vessel with cell culture samples. Integrated spectrometer and optical power meter allow to control the energy and spectral parameters of electromagnetic radiation during the Low Level Light Therapy procedure. Dedicated power supplies and digital controlling system allow independent power of each emitter . It was developed active temperature stabilization system to thermal adjust spectral line of emitted radiation to more efficient association with absorption spectra of biological acceptors. Using the set to controlled irradiation and allowing to measure absorption spectrum of biological medium it is possible to carry out objective assessment the impact of the exposure parameters on the state cells subjected to Low Level Light Therapy. That procedure allows comparing the biological response of cell lines after irradiation with radiation of variable spectral and energetic parameters. Researches were carried out on vascular endothelial cell lines. Cells proliferations after irradiation of LEDs: 645 nm, 680 nm, 740 nm, 780 nm, 830 nm, 870 nm, 890 nm, 970 nm and lasers 650 nm and 830 nm were examined.

  9. Embedded Real-Time Architecture for Level-Set-Based Active Contours

    Directory of Open Access Journals (Sweden)

    Dejnožková Eva

    2005-01-01

    Full Text Available Methods described by partial differential equations have gained a considerable interest because of undoubtful advantages such as an easy mathematical description of the underlying physics phenomena, subpixel precision, isotropy, or direct extension to higher dimensions. Though their implementation within the level set framework offers other interesting advantages, their vast industrial deployment on embedded systems is slowed down by their considerable computational effort. This paper exploits the high parallelization potential of the operators from the level set framework and proposes a scalable, asynchronous, multiprocessor platform suitable for system-on-chip solutions. We concentrate on obtaining real-time execution capabilities. The performance is evaluated on a continuous watershed and an object-tracking application based on a simple gradient-based attraction force driving the active countour. The proposed architecture can be realized on commercially available FPGAs. It is built around general-purpose processor cores, and can run code developed with usual tools.

  10. Stability of Semi-implicit Finite Volume Scheme for Level Set Like Equation

    Institute of Scientific and Technical Information of China (English)

    Kim Kwang-il; Son Yong-chol

    2015-01-01

    We study numerical methods for level set like equations arising in im-age processing and curve evolution problems. Semi-implicit finite volume-element type schemes are constructed for the general level set like equation (image selective smoothing model) given by Alvarez et al. (Alvarez L, Lions P L, Morel J M. Image selective smoothing and edge detection by nonlinear diffusion II. SIAM J. Numer. Anal., 1992, 29: 845–866). Through the reasonable semi-implicit discretization in time and co-volume method for space approximation, we give finite volume schemes, unconditionally stable in L∞ and W 1,2 (W 1,1) sense in isotropic (anisotropic) diffu-sion domain.

  11. Level set formulation of two-dimensional Lagrangian vortex detection methods

    CERN Document Server

    Hadjighasem, Alireza

    2016-01-01

    We propose here the use of the variational level set methodology to capture Lagrangian vortex boundaries in 2D unsteady velocity fields. This method reformulates earlier approaches that seek material vortex boundaries as extremum solutions of variational problems. We demonstrate the performance of this technique for two different variational formulations built upon different notions of coherence. The first formulation uses an energy functional that penalizes the deviation of a closed material line from piecewise uniform stretching [Haller and Beron-Vera, J. Fluid Mech. 731, R4 (2013)]. The second energy function is derived for a graph-based approach to vortex boundary detection [Hadjighasem et al., Phys. Rev. E 93, 063107 (2016)]. Our level-set formulation captures an a priori unknown number of vortices simultaneously at relatively low computational cost. We illustrate the approach by identifying vortices from different coherence principles in several examples.

  12. Level Set Projection Method for Incompressible Navier-Stokes on Arbitrary Boundaries

    KAUST Repository

    Williams-Rioux, Bertrand

    2012-01-12

    Second order level set projection method for incompressible Navier-Stokes equations is proposed to solve flow around arbitrary geometries. We used rectilinear grid with collocated cell centered velocity and pressure. An explicit Godunov procedure is used to address the nonlinear advection terms, and an implicit Crank-Nicholson method to update viscous effects. An approximate pressure projection is implemented at the end of the time stepping using multigrid as a conventional fast iterative method. The level set method developed by Osher and Sethian [17] is implemented to address real momentum and pressure boundary conditions by the advection of a distance function, as proposed by Aslam [3]. Numerical results for the Strouhal number and drag coefficients validated the model with good accuracy for flow over a cylinder in the parallel shedding regime (47 < Re < 180). Simulations for an array of cylinders and an oscillating cylinder were performed, with the latter demonstrating our methods ability to handle dynamic boundary conditions.

  13. Higher-Order Level-Set Method and Its Application in Biomolecular Surfaces Construction

    Institute of Scientific and Technical Information of China (English)

    Chandrajit L. Bajaj; Guo-Liang Xu; Qin Zhang

    2008-01-01

    We present a general framework for a higher-order spline level-set (HLS) method and apply this to biomolecule surfaces construction. Starting from a first order energy functional, we obtain a general level set formulation of geometric partial differential equation, and provide an efficient approach to solving this partial differential equation using a C2 spline basis. We also present a fast cubic spline interpolation algorithm based on convolution and the Z-transform, which exploits the local relationship of interpolatory cubic spline coefficients with respect to given function data values. One example of our HLS method is demonstrated, which is the construction of biomolecule surfaces (an implicit salvation interface) with their individual atomic coordinates and solvated radii as prerequisites.

  14. A level set-based shape optimization method for periodic sound barriers composed of elastic scatterers

    Science.gov (United States)

    Hashimoto, Hiroshi; Kim, Min-Geun; Abe, Kazuhisa; Cho, Seonho

    2013-10-01

    This paper presents a level set-based topology optimization method for noise barriers formed from an assembly of scatterers. The scattering obstacles are modeled by elastic bodies arranged periodically along the wall. Due to the periodicity, the problem can be reduced to that in a unit cell. The interaction between the elastic scatterers and the acoustic field is described in the context of the level set analysis. The semi-infinite acoustic wave regions located on the both sides of the barrier are represented by impedance matrices. The objective function is defined by the energy transmission passing the barrier. The design sensitivity is evaluated analytically by the aid of adjoint equations. The dependency of the optimal profile on the stiffness of scatterers and on the target frequency band is examined. The feasibility of the developed optimization method is proved through numerical examples.

  15. Comparison between advected-field and level-set methods in the study of vesicle dynamics

    CERN Document Server

    Maitre, E; Peyla, P; Raoult, A

    2010-01-01

    Phospholipidic membranes and vesicles constitute a basic element in real biological functions. Vesicles are viewed as a model system to mimic basic viscoelastic behaviors of some cells, like red blood cells. Phase field and level-set models are powerful tools to tackle dynamics of membranes and their coupling to the flow. These two methods are somewhat similar, but to date no bridge between them has been made. This is a first focus of this paper. Furthermore, a constitutive viscoelastic law is derived for the composite fluid: the ambient fluid and the membranes. We present two different approaches to deal with the membrane local incompressibility, and point out differences. Some numerical results following from the level-set approach are presented.

  16. A level set method for reliability-based topology optimization of compliant mechanisms

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Based on the level set model and the reliability theory, a numerical approach of reliability-based topology optimization for compliant mechanisms with multiple inputs and outputs is presented. A multi-objective topology optimal model of compliant mechanisms considering uncertainties of the loads, material properties, and member geometries is developed. The reliability analysis and topology optimization are integrated in the optimal iterative process. The reliabilities of the compliant mechanisms are evaluated by using the first order reliability method. Meanwhile, the problem of structural topology optimization is solved by the level set method which is flexible in handling complex topological changes and concise in describing the boundary shape of the mechanism. Numerical examples show the importance of considering the stochastic nature of the compliant mechanisms in the topology optimization process.

  17. A robust method for calculating interface curvature and normal vectors using an extracted local level set

    CERN Document Server

    Ervik, Åsmund; Munkejord, Svend Tollak

    2014-01-01

    The level-set method is a popular interface tracking method in two-phase flow simulations. An often-cited reason for using it is that the method naturally handles topological changes in the interface, e.g. merging drops, due to the implicit formulation. It is also said that the interface curvature and normal vectors are easily calculated. This last point is not, however, the case in the moments during a topological change, as several authors have already pointed out. Various methods have been employed to circumvent the problem. In this paper, we present a new such method which retains the implicit level-set representation of the surface and handles general interface configurations. It is demonstrated that the method extends easily to 3D. The method is validated on static interface configurations, and then applied to two-phase flow simulations where the method outperforms the standard method and the results agree well with experiments.

  18. Stochastic level-set variational implicit-solvent approach to solute-solvent interfacial fluctuations.

    Science.gov (United States)

    Zhou, Shenggao; Sun, Hui; Cheng, Li-Tien; Dzubiella, Joachim; Li, Bo; McCammon, J Andrew

    2016-08-01

    Recent years have seen the initial success of a variational implicit-solvent model (VISM), implemented with a robust level-set method, in capturing efficiently different hydration states and providing quantitatively good estimation of solvation free energies of biomolecules. The level-set minimization of the VISM solvation free-energy functional of all possible solute-solvent interfaces or dielectric boundaries predicts an equilibrium biomolecular conformation that is often close to an initial guess. In this work, we develop a theory in the form of Langevin geometrical flow to incorporate solute-solvent interfacial fluctuations into the VISM. Such fluctuations are crucial to biomolecular conformational changes and binding process. We also develop a stochastic level-set method to numerically implement such a theory. We describe the interfacial fluctuation through the "normal velocity" that is the solute-solvent interfacial force, derive the corresponding stochastic level-set equation in the sense of Stratonovich so that the surface representation is independent of the choice of implicit function, and develop numerical techniques for solving such an equation and processing the numerical data. We apply our computational method to study the dewetting transition in the system of two hydrophobic plates and a hydrophobic cavity of a synthetic host molecule cucurbit[7]uril. Numerical simulations demonstrate that our approach can describe an underlying system jumping out of a local minimum of the free-energy functional and can capture dewetting transitions of hydrophobic systems. In the case of two hydrophobic plates, we find that the wavelength of interfacial fluctuations has a strong influence to the dewetting transition. In addition, we find that the estimated energy barrier of the dewetting transition scales quadratically with the inter-plate distance, agreeing well with existing studies of molecular dynamics simulations. Our work is a first step toward the inclusion of

  19. Hausdorff measures of the image, graph and level set of bifractional Brownian motion

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Let BH,K = {BH,K(t), t ∈ R+} be a bifractional Brownian motion in Rd. This process is a selfsimilar Gaussian process depending on two parameters H and K and it constitutes a natural generalization of fractional Brownian motion (which is obtained for K = 1). The exact Hausdorff measures of the image, graph and the level set of BH,K are investigated. The results extend the corresponding results proved by Talagrand and Xiao for fractional Brownian motion.

  20. Numerical Simulation of Dynamic Contact Angles and Contact Lines in Multiphase Flows using Level Set Method

    Science.gov (United States)

    Pendota, Premchand

    Many physical phenomena and industrial applications involve multiphase fluid flows and hence it is of high importance to be able to simulate various aspects of these flows accurately. The Dynamic Contact Angles (DCA) and the contact lines at the wall boundaries are a couple of such important aspects. In the past few decades, many mathematical models were developed for predicting the contact angles of the inter-face with the wall boundary under various flow conditions. These models are used to incorporate the physics of DCA and contact line motion in numerical simulations using various interface capturing/tracking techniques. In the current thesis, a simple approach to incorporate the static and dynamic contact angle boundary conditions using the level set method is developed and implemented in multiphase CFD codes, LIT (Level set Interface Tracking) (Herrmann (2008)) and NGA (flow solver) (Desjardins et al (2008)). Various DCA models and associated boundary conditions are reviewed. In addition, numerical aspects such as the occurrence of a stress singularity at the contact lines and grid convergence of macroscopic interface shape are dealt with in the context of the level set approach.

  1. Modelling turbulence effects in wildland fire propagation by the randomized level-set method

    CERN Document Server

    Pagnini, Gianni

    2014-01-01

    Turbulence is of paramount importance in wildland fire propagation since it randomly transports the hot air mass that can pre-heat and then ignite the area ahead the fire. This contributes to give a random character to the firefront position together with other phenomena as for example fire spotting, vegetation distribution (patchiness), gaseous combustion fluctuation, small-scale terrain elevation changes. Here only turbulence is considered. The level-set method is used to numerically describe the evolution of the fireline contour that is assumed to have a random motion because of turbulence. The progression of the combustion process is then described by a level-set contour distributed according to a weight function given by the probability density function of the air particles in turbulent motion. From the comparison between the ordinary and the randomized level-set methods, it emerges that the proposed modelling approach turns out to be suitable to simulate a moving firefront fed by the ground fuel and dri...

  2. A level set formulation for the numerical simulation of impact of surge fronts

    Indian Academy of Sciences (India)

    A Salih; S Ghosh Moulic

    2006-12-01

    In this paper we present a level set-based algorithm for the solution of incompressible two-phase flow problems. The technique is applied to the numerical simulation of impact of two surge fronts resulting from the collapse of liquid columns. The incompressible Navier–Stokes equations are solved using a projection method based on forward Euler time-stepping. The Hamilton–Jacobi type equation for the transport of level set function is carried out by a high resolution fifth-order accurate WENO scheme. For efficient implementation of the WENO scheme we have proposed grid staggering for the level set function. The solution of the pressure Poisson equation is obtained using an efficient preconditioned conjugate gradient method. It is shown that the present formulation works very well for large density and viscosity ratios. For the purpose of validation, we have simulated small-amplitude free sloshing of liquid in a container and the well-known two-dimensional broken-dam problem of Martin and Moyce. Simulations of impact of surge fronts have been carried out and the results are discussed.

  3. Some free boundary problems in potential flow regime usinga based level set method

    Energy Technology Data Exchange (ETDEWEB)

    Garzon, M.; Bobillo-Ares, N.; Sethian, J.A.

    2008-12-09

    Recent advances in the field of fluid mechanics with moving fronts are linked to the use of Level Set Methods, a versatile mathematical technique to follow free boundaries which undergo topological changes. A challenging class of problems in this context are those related to the solution of a partial differential equation posed on a moving domain, in which the boundary condition for the PDE solver has to be obtained from a partial differential equation defined on the front. This is the case of potential flow models with moving boundaries. Moreover the fluid front will possibly be carrying some material substance which will diffuse in the front and be advected by the front velocity, as for example the use of surfactants to lower surface tension. We present a Level Set based methodology to embed this partial differential equations defined on the front in a complete Eulerian framework, fully avoiding the tracking of fluid particles and its known limitations. To show the advantages of this approach in the field of Fluid Mechanics we present in this work one particular application: the numerical approximation of a potential flow model to simulate the evolution and breaking of a solitary wave propagating over a slopping bottom and compare the level set based algorithm with previous front tracking models.

  4. A low false negative filter for detecting rare bird species from short video segments using a probable observation data set-based EKF method.

    Science.gov (United States)

    Song, Dezhen; Xu, Yiliang

    2010-09-01

    We report a new filter to assist the search for rare bird species. Since a rare bird only appears in front of a camera with very low occurrence (e.g., less than ten times per year) for very short duration (e.g., less than a fraction of a second), our algorithm must have a very low false negative rate. We verify the bird body axis information with the known bird flying dynamics from the short video segment. Since a regular extended Kalman filter (EKF) cannot converge due to high measurement error and limited data, we develop a novel probable observation data set (PODS)-based EKF method. The new PODS-EKF searches the measurement error range for all probable observation data that ensures the convergence of the corresponding EKF in short time frame. The algorithm has been extensively tested using both simulated inputs and real video data of four representative bird species. In the physical experiments, our algorithm has been tested on rock pigeons and red-tailed hawks with 119 motion sequences. The area under the ROC curve is 95.0%. During the one-year search of ivory-billed woodpeckers, the system reduces the raw video data of 29.41 TB to only 146.7 MB (reduction rate 99.9995%).

  5. Auto-Segmentation of Head and Neck Cancer using Textural features

    DEFF Research Database (Denmark)

    Hollensen, Christian; Jørgensen, Peter Stanley; Højgaard, Liselotte;

    - and intra observer variability. Several automatic segmentation methods have been developed using positron emission tomography (PET) and/or computerised tomography (CT). The aim of the present study is to develop a model for 3-dimensional auto-segmentation, the level set method, to contour gross tumour...... inside and outside the GTV respectively to choose an appropriate feature combination for segmentation of the GTV. The feature combination with the highest dissimilarity was extracted on PET and CT images from the remaining 25 HNC patients. Using these features as input for a level set segmentation method...... the tumours were segmented automatically. Segmentation results were evaluated against manual contours of radiologists using the DICE coefficient, and sensitivity. The result of the level set approach method was compared with threshold segmentation of PET standard uptake value (SUV) of 3 or 20% of maximal...

  6. Stacking sequence and shape optimization of laminated composite plates via a level-set method

    Science.gov (United States)

    Allaire, G.; Delgado, G.

    2016-12-01

    We consider the optimal design of composite laminates by allowing a variable stacking sequence and in-plane shape of each ply. In order to optimize both variables we rely on a decomposition technique which aggregates the constraints into one unique constraint margin function. Thanks to this approach, an exactly equivalent bi-level optimization problem is established. This problem is made up of an inner level represented by the combinatorial optimization of the stacking sequence and an outer level represented by the topology and geometry optimization of each ply. We propose for the stacking sequence optimization an outer approximation method which iteratively solves a set of mixed integer linear problems associated to the evaluation of the constraint margin function. For the topology optimization of each ply, we lean on the level set method for the description of the interfaces and the Hadamard method for boundary variations by means of the computation of the shape gradient. Numerical experiments are performed on an aeronautic test case where the weight is minimized subject to different mechanical constraints, namely compliance, reserve factor and buckling load.

  7. The Edge Factor in Early Word Segmentation: Utterance-Level Prosody Enables Word Form Extraction by 6-Month-Olds

    Science.gov (United States)

    Johnson, Elizabeth K.; Seidl, Amanda; Tyler, Michael D.

    2014-01-01

    Past research has shown that English learners begin segmenting words from speech by 7.5 months of age. However, more recent research has begun to show that, in some situations, infants may exhibit rudimentary segmentation capabilities at an earlier age. Here, we report on four perceptual experiments and a corpus analysis further investigating the initial emergence of segmentation capabilities. In Experiments 1 and 2, 6-month-olds were familiarized with passages containing target words located either utterance medially or at utterance edges. Only those infants familiarized with passages containing target words aligned with utterance edges exhibited evidence of segmentation. In Experiments 3 and 4, 6-month-olds recognized familiarized words when they were presented in a new acoustically distinct voice (male rather than female), but not when they were presented in a phonologically altered manner (missing the initial segment). Finally, we report corpus analyses examining how often different word types occur at utterance boundaries in different registers. Our findings suggest that edge-aligned words likely play a key role in infants’ early segmentation attempts, and also converge with recent reports suggesting that 6-month-olds’ have already started building a rudimentary lexicon. PMID:24421892

  8. Level Characteristics of Rough Fuzzy Sets and Fuzzy Rough Sets%粗糙模糊集与模糊粗糙集的截集性质

    Institute of Scientific and Technical Information of China (English)

    胡宝清; 咸艳霞

    2006-01-01

    研究粗糙模糊集、模糊粗糙集、广义粗糙模糊集和广义模糊粗糙集的截集性质,并且还研究了基于逻辑算子的广义模糊粗糙集的基本性质.%This paper mainly studies the level characteristics of various rough sets under fuzzy environment,such as rough fuzzy sets, fuzzy rough sets, generalized rough fuzzy sets, generalized fuzzy rough sets based on fuzzy rough sets and logic operators. Moreover, other basic properties of generalized fuzzy rough sets based on logic operators are also investigated.

  9. Improved inhalation technology for setting safe exposure levels for workplace chemicals

    Science.gov (United States)

    Stuart, Bruce O.

    1993-01-01

    Threshold Limit Values recommended as allowable air concentrations of a chemical in the workplace are often based upon a no-observable-effect-level (NOEL) determined by experimental inhalation studies using rodents. A 'safe level' for human exposure must then be estimated by the use of generalized safety factors in attempts to extrapolate from experimental rodents to man. The recent development of chemical-specific physiologically-based toxicokinetics makes use of measured physiological, biochemical, and metabolic parameters to construct a validated model that is able to 'scale-up' rodent response data to predict the behavior of the chemical in man. This procedure is made possible by recent advances in personal computer software and the emergence of appropriate biological data, and provides an analytical tool for much more reliable risk evaluation and airborne chemical exposure level setting for humans.

  10. Texture Analysis and Modified Level Set Method for Automatic Detection of Bone Boundaries in Hand Radiographs

    Directory of Open Access Journals (Sweden)

    Syaiful Anam

    2014-10-01

    Full Text Available Rheumatoid Arthritis (RA is a chronic inflammatory joint disease characterized by a distinctive pattern of bone and joint destruction. To give an RA diagnosis, hand bone radiographs are taken and analyzed. A hand bone radiograph analysis starts with the bone boundary detection. It is however an extremely exhausting and time consuming task for radiologists. An automatic bone boundary detection in hand radiographs is thus strongly required. Garcia et al. have proposed a method for automatic bone boundary detection in hand radiographs by using an adaptive snake method, but it doesn’t work for those affected by RA. The level set method has advantages over the snake method. It however often leads to either a complete breakdown or a premature termination of the curve evolution process, resulting in unsatisfactory results. For those reasons, we propose a modified level set method for detecting bone boundaries in hand radiographs affected by RA. Texture analysis is also applied for distinguishing the hand bones and other areas. Evaluating the experiments using a particular set of hand bone radiographs, the effectiveness of the proposed method has been proved.

  11. AUTOMATIC MULTILEVEL IMAGE SEGMENTATION BASED ON FUZZY REASONING

    Directory of Open Access Journals (Sweden)

    Liang Tang

    2011-05-01

    Full Text Available An automatic multilevel image segmentation method based on sup-star fuzzy reasoning (SSFR is presented. Using the well-known sup-star fuzzy reasoning technique, the proposed algorithm combines the global statistical information implied in the histogram with the local information represented by the fuzzy sets of gray-levels, and aggregates all the gray-levels into several classes characterized by the local maximum values of the histogram. The presented method has the merits of determining the number of the segmentation classes automatically, and avoiding to calculating thresholds of segmentation. Emulating and real image segmentation experiments demonstrate that the SSFR is effective.

  12. Structural Topology Design of Container Ship Based on Knowledge-Based Engineering and Level Set Method

    Institute of Scientific and Technical Information of China (English)

    崔进举; 王德禹; 史琪琪

    2015-01-01

    Knowledge-Based Engineering (KBE) is introduced into the ship structural design in this paper. From the implementation of KBE, the design solutions for both Rules Design Method (RDM) and Interpolation Design Method (IDM) are generated. The corresponding Finite Element (FE) models are generated. Topological design of the longitudinal structures is studied where the Gaussian Process (GP) is employed to build the surrogate model for FE analysis. Multi-objective optimization methods inspired by Pareto Front are used to reduce the design tank weight and outer surface area simultaneously. Additionally, an enhanced Level Set Method (LSM) which employs implicit algorithm is applied to the topological design of typical bracket plate which is used extensively in ship structures. Two different sets of boundary conditions are considered. The proposed methods show satisfactory efficiency and accuracy.

  13. On the applicability of the level set method beyond the flamelet regime in thermonuclear supernova simulations

    CERN Document Server

    Schmidt, W

    2007-01-01

    In thermonuclear supernovae, intermediate mass elements are mostly produced by distributed burning provided that a deflagration to detonation transition does not set in. Apart from the two-dimensional study by Roepke & Hillebrandt (2005), very little attention has been payed so far to the correct treatment of this burning regime in numerical simulations. In this article, the physics of distributed burning is reviewed from the literature on terrestrial combustion and differences which arise from the very small Prandtl numbers encountered in degenerate matter are pointed out. Then it is shown that the level set method continues to be applicable beyond the flamelet regime as long as the width of the flame brush does not become smaller than the numerical cutoff length. Implementing this constraint with a simple parameterisation of the effect of turbulence onto the energy generation rate, the production of intermediate mass elements increases substantially compared to previous simulations, in which the burning...

  14. A level set based algorithm to reconstruct the urinary bladder from multiple views.

    Science.gov (United States)

    Ma, Zhen; Jorge, Renato Natal; Mascarenhas, T; Tavares, João Manuel R S

    2013-12-01

    The urinary bladder can be visualized from different views by imaging facilities such as computerized tomography and magnetic resonance imaging. Multi-view imaging can present more details of this pelvic organ and contribute to a more reliable reconstruction. Based on the information from multi-view planes, a level set based algorithm is proposed to reconstruct the 3D shape of the bladder using the cross-sectional boundaries. The algorithm provides a flexible solution to handle the discrepancies from different view planes and can obtain an accurate bladder surface with more geometric details. Copyright © 2013 IPEM. Published by Elsevier Ltd. All rights reserved.

  15. Adaptive gradient-augmented level set method with multiresolution error estimation

    CERN Document Server

    Kolomenskiy, Dmitry; Schneider, Kai

    2014-01-01

    A space-time adaptive scheme is presented for solving advection equations in two space dimensions. The gradient-augmented level set method using a semi-Lagrangian formulation with backward time integration is coupled with a point value multiresolution analysis using Hermite interpolation. Thus locally refined dyadic spatial grids are introduced which are efficiently implemented with dynamic quad-tree data structures. For adaptive time integration, an embedded Runge-Kutta method is employed. The precision of the new fully adaptive method is analysed and speed up of CPU time and memory compression with respect to the uniform grid discretization are reported.

  16. A level set approach for damage identification of continuum structures based on dynamic responses

    Science.gov (United States)

    Zhang, Weisheng; Du, Zongliang; Sun, Guo; Guo, Xu

    2017-01-01

    The present paper aims to propose a novel approach for damage identification of continuum structures based on their dynamic performances. The main idea is resorting to the level set model, which is used to describe the shape and topology of the damage regions implicitly. The original natural frequency-based inverse problem is thus transferred into a generalized shape optimization problem which can be tackled by solving an evolution type Hamilton-Jacobi equation. Compared to traditional approaches, the distinctive advantage of the proposed approach is that it can deal with damage regions of complex shapes in a convenient way. Numerical examples demonstrate the effectiveness of the proposed approach.

  17. Geochemistry, geochronology, and tectonic setting of Early Cretaceous volcanic rocks in the northern segment of the Tan-Lu Fault region, northeast China

    Science.gov (United States)

    Ling, Yi-Yun; Zhang, Jin-Jiang; Liu, Kai; Ge, Mao-Hui; Wang, Meng; Wang, Jia-Min

    2017-08-01

    We present new geochemical and geochronological data for volcanic and related rocks in the regions of the Jia-Yi and Dun-Mi faults, in order to constrain the late Mesozoic tectonic evolution of the northern segment of the Tan-Lu Fault. Zircon U-Pb dating shows that rhyolite and intermediate-mafic rocks along the southern part of the Jia-Yi Fault formed at 124 and 113 Ma, respectively, whereas the volcanic rocks along the northern parts of the Jia-Yi and Dun-Mi faults formed at 100 Ma. The rhyolite has an A-type granitoid affinity, with high alkalis, low MgO, Ti, and P contents, high rare earth element (REE) contents and Ga/Al ratios, enrichments in large-ion lithophile (LILEs; e.g., Rb, Th, and U) and high-field-strength element (HFSEs; e.g., Nb, Ta, Zr, and Y), and marked negative Eu anomalies. These features indicate that the rhyolites were derived from partial melting of crustal material in an extensional environment. The basaltic rocks are enriched in light REEs and LILEs (e.g., Rb, K, Th, and U), and depleted in heavy REEs, HFSEs (e.g., Nb, Ta, Ti, and P), and Sr. These geochemical characteristics indicate that these rocks are calc-alkaline basalts that formed in an intraplate extensional tectonic setting. The dacite is a medium- to high-K, calc-alkaline, I-type granite that was derived from a mixed source involving both crustal and mantle components in a magmatic arc. Therefore, the volcanic rocks along the Jia-Yi and Dun-Mi faults were formed in an extensional regime at 124-100 Ma (Early Cretaceous), and these faults were extensional strike-slip faults at this time.

  18. Level set motion assisted non-rigid 3D image registration

    Science.gov (United States)

    Yang, Deshan; Deasy, Joseph O.; Low, Daniel A.; El Naqa, Issam

    2007-03-01

    Medical imaging applications of rigid and non-rigid elastic deformable image registration are undergoing wide scale development. Our approach determines image deformation maps through a hierarchical process, from global to local scales. Vemuri (2000) reported a registration method, based on levelset evolution theory, to morph an image along the motion gradient until it deforms to the reference image. We have applied this level set motion method as basis to iteratively compute the incremental motion fields and then we approximated the field using a higher-level affine and non-rigid motion model. In such a way, we combine sequentially the global affine motion, local affine motion and local non-rigid motion. Our method is fully automated, computationally efficient, and is able to detect large deformations if used together with multi-grid approaches, potentially yielding greater registration accuracy.

  19. Simulation of heterogeneous two-phase media using random fields and level sets

    Institute of Scientific and Technical Information of China (English)

    George STEFANOU[1,2

    2015-01-01

    The accurate and efficient simulation of random heterogeneous media is important in the framework of modeling and design of complex materials across multiple length scales. It is usually assumed that the morphology of a random microstructure can be described as a non-Gaussian random field that is completely defined by its multivariate distribution. A particular kind of non-Gaussian random fields with great practical importance is that of translation fields resulting from a simple memory-less transformation of an underlying Gaussian field with known second-order statistics. This paper provides a critical examination of existing random field models of heterogeneous two-phase media with emphasis on level-cut random fields which are a special case of translation fields. The case of random level sets, often used to represent the geometry of physical systems, is also examined. Two numerical examples are provided to illustrate the basic features of the different approaches.

  20. Brain tumor segmentation based on a hybrid clustering technique

    Directory of Open Access Journals (Sweden)

    Eman Abdel-Maksoud

    2015-03-01

    This paper presents an efficient image segmentation approach using K-means clustering technique integrated with Fuzzy C-means algorithm. It is followed by thresholding and level set segmentation stages to provide an accurate brain tumor detection. The proposed technique can get benefits of the K-means clustering for image segmentation in the aspects of minimal computation time. In addition, it can get advantages of the Fuzzy C-means in the aspects of accuracy. The performance of the proposed image segmentation approach was evaluated by comparing it with some state of the art segmentation algorithms in case of accuracy, processing time, and performance. The accuracy was evaluated by comparing the results with the ground truth of each processed image. The experimental results clarify the effectiveness of our proposed approach to deal with a higher number of segmentation problems via improving the segmentation quality and accuracy in minimal execution time.

  1. FULLY AUTOMATIC FRAMEWORK FOR SEGMENTATION OF BRAIN MRI IMAGE

    Institute of Scientific and Technical Information of China (English)

    Lin Pan; Zheng Chongxun; Yang Yong; Gu Jianwen

    2005-01-01

    Objective To propose an automatic framework for segmentation of brain image in this paper. Methods The brain MRI image segmentation framework consists of three-step segmentation procedures. First, Non-brain structures removal by level set method. Then, the non-uniformity correction method is based on computing estimates of tissue intensity variation. Finally, it uses a statistical model based on Markov random filed for MRI brain image segmentation. The brain tissue can be classified into cerebrospinal fluid, white matter and gray matter. Results To evaluate the proposed our method, we performed two sets of experiments, one on simulated MR and another on real MR brain data. Conclusion The efficacy of the brain MRI image segmentation framework has been demonstrated by the extensive experiments. In the future, we are also planning on a large-scale clinical evaluation of this segmentation framework.

  2. 基于频繁镜头集合的视频场景分割方法%A VIDEO SCENE SEGMENTATION METHOD BASED ON FREQUENT SHOT SET

    Institute of Scientific and Technical Information of China (English)

    郭小川; 刘明杰; 王婧璐; 董道国; 万乾荣

    2011-01-01

    The paper proposes a video scene segmentation method that searches for frequent shot sets in video sequences on the basis of global scene characteristics as well as precisely locates video scene borders by local semantic properties. At first the analyzing video is shot split by high resolution to choose representative shot key frames. Then the global scene features and local features of every shot key frame are extracted. Then with the visual vocabulary created by local feature clustering, every shot key frame is semantically labeled. Next the relativity among shots based on global scene features is calculated. Combining the video scene concept and features, shot sets with high relativity in local frequent appearance are sought for among shot key frame sequences in order to roughly locate the video scene. At last the shot key frame semantic labeling feature is used to precisely define the video scene border. Experiments prove the method can accurately and effectively detect and locate most video scenes.%提出一种基于全局场景特征在视频序列中寻找频繁镜头集合,并通过局部语义特征精确定位视频场景边界的视频场景分割方法.首先对分析视频进行高精度镜头分割,选取具有代表性的镜头关键帧.然后提取各镜头关键帧的全局场景特征和局部特征,并利用局部特征聚类得到的视觉词对各个镜头关键帧进行语义标注.接下来计算基于全局场景特征的镜头间相关性,结合视频场景的概念和特性,在镜头关键帧序列中寻找局部频繁出现的相关性高的镜头集合,粗略定位视频场景位置.最后利用镜头关键帧的语义标注特征精确定位视频场景边界.实验证明该方法能够准确、有效地检测并定位到大部分视频场景.

  3. Time-optimal path planning in dynamic flows using level set equations: theory and schemes

    Science.gov (United States)

    Lolla, Tapovan; Lermusiaux, Pierre F. J.; Ueckermann, Mattheus P.; Haley, Patrick J.

    2014-10-01

    We develop an accurate partial differential equation-based methodology that predicts the time-optimal paths of autonomous vehicles navigating in any continuous, strong, and dynamic ocean currents, obviating the need for heuristics. The goal is to predict a sequence of steering directions so that vehicles can best utilize or avoid currents to minimize their travel time. Inspired by the level set method, we derive and demonstrate that a modified level set equation governs the time-optimal path in any continuous flow. We show that our algorithm is computationally efficient and apply it to a number of experiments. First, we validate our approach through a simple benchmark application in a Rankine vortex flow for which an analytical solution is available. Next, we apply our methodology to more complex, simulated flow fields such as unsteady double-gyre flows driven by wind stress and flows behind a circular island. These examples show that time-optimal paths for multiple vehicles can be planned even in the presence of complex flows in domains with obstacles. Finally, we present and support through illustrations several remarks that describe specific features of our methodology.

  4. Level set immersed boundary method for gas-liquid-solid interactions

    Science.gov (United States)

    Wang, Shizhao; Balaras, Elias

    2015-11-01

    We will discuss an approach to simulate the interaction between free surface flows and deformable structures. In our formulation the Navier-Stokes equations are solved on a block-structured grid with adaptive mesh refinement, and the pressure jumps across the interface between different phases, which is tracked using a level set approach, are sharply defined. Deformable structures are simulated with a solid mechanics solver utilizing a finite element method. The overall approach is tailored to problems with large displacement/deformations. The boundary conditions on a solid body are imposed using a direct forcing, immersed boundary method (Vanella & Balaras, J. Comput. Physics, 228(18), 6617-6628, 2009). The flow and structural solvers are coupled by a predictor-corrector, strong-coupling scheme. The consistency between the Eulerian field based level set method for fluid-fluid interface and Lagrangian marker based immersed boundary method for fluid-structure interface is ensured by reconstructing the flow field around the three phase intersections. A variety of 2D and 3D problems ranging from water impact of wedges, entry and exit of cylinders and flexible plates interacting with a free surfaces, are presented to demonstrate the accuracy of the proposed approach. Supported by ONR N000141110588 monitored by Dr. Thomas Fu.

  5. A review of selected research priority setting processes at national level in low and middle income countries: towards fair and legitimate priority setting

    Directory of Open Access Journals (Sweden)

    Hoosain Naeema

    2011-05-01

    Full Text Available Abstract Background It is estimated that more than $130 billion is invested globally into health research each year. Increasingly, there is a need to set priorities in health research investments in a fair and legitimate way, using a sound and transparent methodology. In this paper we review selected priority setting processes at national level in low and middle income countries. We outline a set of criteria to assess the process of research priority setting and use these to describe and evaluate priority setting exercises that have taken place at country level. Based on these insights, recommendations are made regarding the constituents of a good priority setting process. Methods Data were gathered from presentations at a meeting held at the World Health Organization (WHO in 2008 and a web-based search. Based on this literature review a number of criteria were developed to evaluate the priority setting processes. Results Across the countries surveyed there was a relative lack of genuine stakeholder engagement; countries varied markedly in the extent to which the priority setting processes were documented; none of the countries surveyed had a systematic or operational appeals process for outlined priorities; and in all countries (except South Africa the priorities that were outlined described broad disease categories rather than specific research questions. Conclusions Country level priority setting processes differed significantly in terms of the methods used. We argue that priority setting processes must have in-built mechanisms for publicizing results, effective procedures to enforce decisions as well as processes to ensure that the revision of priorities happens in practice.

  6. The impact of numeric and graphic displays of ST-segment deviation levels on cardiologists' decisions of reperfusion therapy for patients with acute coronary occlusion.

    Science.gov (United States)

    Nimmermark, Magnus O; Wang, John J; Maynard, Charles; Cohen, Mauricio; Gilcrist, Ian; Heitner, John; Hudson, Michael; Palmeri, Sebastian; Wagner, Galen S; Pahlm, Olle

    2011-01-01

    The study purpose is to determine whether numeric and/or graphic ST measurements added to the display of the 12-lead electrocardiogram (ECG) would influence cardiologists' decision to provide myocardial reperfusion therapy. Twenty ECGs with borderline ST-segment deviation during elective percutaneous coronary intervention and 10 controls before balloon inflation were included. Only 5 of the 20 ECGs during coronary balloon occlusion met the 2007 American Heart Association guidelines for ST-elevation myocardial infarction (STEMI). Fifteen cardiologists read 4 sets of these ECGs as the basis for a "yes/no" reperfusion therapy decision. Sets 1 and 4 were the same 12-lead ECGs alone. Set 2 also included numeric ST-segment measurements, and set 3 included both numeric and graphically displayed ST measurements ("ST Maps"). The mean (range) positive reperfusion decisions were 10.6 (2-15), 11.4 (1-19), 9.7 (2-14), and 10.7 (1-15) for sets 1 to 4, respectively. The accuracies of the observers for the 5 STEMI ECGs were 67%, 69%, and 77% for the standard format, the ST numeric format, and the ST graphic format, respectively. The improved detection rate (77% vs 67%) with addition of both numeric and graphic displays did achieve statistical significance (P numeric and/or graphic displays. Acute coronary occlusion detection rate was low for ECGs meeting STEMI criteria, and this was improved by adding ST-segment measurements in numeric and graphic forms. These results merit further study of the clinical value of this technique for improved acute coronary occlusion treatment decision support.

  7. 一种新的基于双层PCNN的自适应图像分割算法%New adaptive algorithm for image segmentation using the dual-level PCNN model

    Institute of Scientific and Technical Information of China (English)

    严春满; 郭宝龙; 马义德; 张旭

    2011-01-01

    A novel adaptive algorithm for image segmentation based on the dual-level pulse coupled neural networks(PCNN) is proposed.For the dual-level PCNN,the first level is based on the simplified PCNN model to obtain the region seeds;the next level adopts the region growing strategy,and recruits the pixels which have similar gray level to the seeds to achieve the growth of the regions.The sensitive parameters of the PCNN can be tuned adaptively,which can overcome the limitation of the parameter setting.Moreover,the region growing strategy strengthens the region characteristics of PCNN.Experimental results show that the proposed algorithm can improve the region connectivity and the edge regularity of the segmented image,and the advantages of PCNN for image segmentation are developed.%提出一种新的基于双层脉冲耦合神经网络(PCNN)的自适应图像分割算法。双层PCNN的前级以简化PCNN模型为基础,获得区域生长的种子;后级采用区域生长机制,征募区域内灰度相似像素,完成前级种子的生长。新算法PCNN的关键参数可自适应更新,避免了传统PCNN参数设置难的问题;区域生长机制强化了PCNN的区域特性。实验结果表明,新算法所得分割图像的区域连通性及边缘规整性得到进一步提高,发挥了PCNN应用于图像分割的优越性。

  8. Reservoir characterisation by a binary level set method and adaptive multiscale estimation

    Energy Technology Data Exchange (ETDEWEB)

    Nielsen, Lars Kristian

    2006-01-15

    The main focus of this work is on estimation of the absolute permeability as a solution of an inverse problem. We have both considered a single-phase and a two-phase flow model. Two novel approaches have been introduced and tested numerical for solving the inverse problems. The first approach is a multi scale zonation technique which is treated in Paper A. The purpose of the work in this paper is to find a coarse scale solution based on production data from wells. In the suggested approach, the robustness of an already developed method, the adaptive multi scale estimation (AME), has been improved by utilising information from several candidate solutions generated by a stochastic optimizer. The new approach also suggests a way of combining a stochastic and a gradient search method, which in general is a problematic issue. The second approach is a piecewise constant level set approach and is applied in Paper B, C, D and E. Paper B considers the stationary single-phase problem, while Paper C, D and E use a two-phase flow model. In the two-phase flow problem we have utilised information from both production data in wells and spatially distributed data gathered from seismic surveys. Due to the higher content of information provided by the spatially distributed data, we search solutions on a slightly finer scale than one typically does with only production data included. The applied level set method is suitable for reconstruction of fields with a supposed known facies-type of solution. That is, the solution should be close to piecewise constant. This information is utilised through a strong restriction of the number of constant levels in the estimate. On the other hand, the flexibility in the geometries of the zones is much larger for this method than in a typical zonation approach, for example the multi scale approach applied in Paper A. In all these papers, the numerical studies are done on synthetic data sets. An advantage of synthetic data studies is that the true

  9. CT Findings of Disease with Elevated Serum D-Dimer Levels in an Emergency Room Setting

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Ji Youn; Kwon, Woo Cheol; Kim, Young Ju [Dept. of Radiology, Wonju Christian Hospital, Yensei University Wonju College of Medicine, Wonju (Korea, Republic of)

    2012-01-15

    Pulmonary embolism and deep vein thrombosis are the leading causes of elevated serum D-dimer levels in the emergency room. Although D-dimer is a useful screening test because of its high sensitivity and negative predictive value, it has a low specificity. In addition, D-dimer can be elevated in various diseases. Therefore, information on the various diseases with elevated D-dimer levels and their radiologic findings may allow for accurate diagnosis and proper management. Herein, we report the CT findings of various diseases with elevated D-dimer levels in an emergency room setting, including an intravascular contrast filling defect with associated findings in a venous thromboembolism, fracture with soft tissue swelling and hematoma formation in a trauma patient, enlargement with contrast enhancement in the infected organ of a patient, coronary artery stenosis with a perfusion defect of the myocardium in a patient with acute myocardial infarction, high density of acute thrombus in a cerebral vessel with a low density of affected brain parenchyma in an acute cerebral infarction, intimal flap with two separated lumens in a case of aortic dissection, organ involvement of malignancy in a cancer patient, and atrophy of a liver with a dilated portal vein and associated findings.

  10. Enabling user-guided segmentation and tracking of surface-labeled cells in time-lapse image sets of living tissues.

    Science.gov (United States)

    Mashburn, David N; Lynch, Holley E; Ma, Xiaoyan; Hutson, M Shane

    2012-05-01

    To study the process of morphogenesis, one often needs to collect and segment time-lapse images of living tissues to accurately track changing cellular morphology. This task typically involves segmenting and tracking tens to hundreds of individual cells over hundreds of image frames, a scale that would certainly benefit from automated routines; however, any automated routine would need to reliably handle a large number of sporadic, and yet typical problems (e.g., illumination inconsistency, photobleaching, rapid cell motions, and drift of focus or of cells moving through the imaging plane). Here, we present a segmentation and cell tracking approach based on the premise that users know their data best-interpreting and using image features that are not accounted for in any a priori algorithm design. We have developed a program, SeedWater Segmenter, that combines a parameter-less and fast automated watershed algorithm with a suite of manual intervention tools that enables users with little to no specialized knowledge of image processing to efficiently segment images with near-perfect accuracy based on simple user interactions.

  11. A GPU-accelerated adaptive discontinuous Galerkin method for level set equation

    Science.gov (United States)

    Karakus, A.; Warburton, T.; Aksel, M. H.; Sert, C.

    2016-01-01

    This paper presents a GPU-accelerated nodal discontinuous Galerkin method for the solution of two- and three-dimensional level set (LS) equation on unstructured adaptive meshes. Using adaptive mesh refinement, computations are localised mostly near the interface location to reduce the computational cost. Small global time step size resulting from the local adaptivity is avoided by local time-stepping based on a multi-rate Adams-Bashforth scheme. Platform independence of the solver is achieved with an extensible multi-threading programming API that allows runtime selection of different computing devices (GPU and CPU) and different threading interfaces (CUDA, OpenCL and OpenMP). Overall, a highly scalable, accurate and mass conservative numerical scheme that preserves the simplicity of LS formulation is obtained. Efficiency, performance and local high-order accuracy of the method are demonstrated through distinct numerical test cases.

  12. LEVEL SET METHOD FOR NUMERICAL SIMULATION OF A CAVITATION BUBBLE COLLAPSING NEAR A RIGID WALL

    Institute of Scientific and Technical Information of China (English)

    HUANG Jun-tao; ZHANG Hui-sheng

    2005-01-01

    The level set method, TVD scheme of second order upwind procedure coupled with flux limiter, ENO velocity extension procedure inside the bubble, and MAC projection algorithm were incorporated to simulate the whole collapse evolution of a cavitation bubble near a rigid wall with many complicated phenomena, such as topology distortion and shrinking, jet impact, bubble breaking into a toroidal form, and diminishing volume to zero, etc.The bubble shape, evolution and distribution of velocity and pressure fields of the fluid during the bubble collapsing were investigated.It is found that the method is numerically stable and has good convergence property, and the results are in good agreements with those in previous work.

  13. Level Set-Based Topology Optimization for the Design of an Electromagnetic Cloak With Ferrite Material

    DEFF Research Database (Denmark)

    Otomori, Masaki; Yamada, Takayuki; Andkjær, Jacob Anders;

    2013-01-01

    This paper presents a structural optimization method for the design of an electromagnetic cloak made of ferrite material. Ferrite materials exhibit a frequency-dependent degree of permeability, due to a magnetic resonance phenomenon that can be altered by changing the magnitude of an externally...... applied dc magnetic field. Thus, such ferrite cloaks have the potential to provide novel functions, such as on-off operation in response to on-off application of an external magnetic field. The optimization problems are formulated to minimize the norm of the scattering field from a cylindrical obstacle....... A level set-based topology optimization method incorporating a fictitious interface energy is used to find optimized configurations of the ferrite material. The numerical results demonstrate that the optimization successfully found an appropriate ferrite configuration that functions as an electromagnetic...

  14. Level set method for computational multi-fluid dynamics: A review on developments, applications and analysis

    Indian Academy of Sciences (India)

    Atul Sharma

    2015-05-01

    Functions and conservation as well as subsidiary equations in Level Set Method (LSM) are presented. After the mathematical formulation, improvements in the numerical methodology for LSM are reviewed here for advection schemes, reinitialization methods, hybrid methods, adaptive-grid LSM, dual-resolution LSM, sharp-interface LSM, conservative LSM, parallel computing and extension from two to multi fluid/phase as well as to various types of two-phase flow. In the second part of this article, LSM method based Computational Multi-Fluid Dynamics (CMFD) applications and analysis are reviewed for four different types of multi-phase flow: separated and parallel internal flow, drop/bubble dynamics during jet break-up, drop impact dynamics on a solid or liquid surface and boiling. In the last twenty years, LSM has established itself as a method which is easy to program and is accurate as well as computationally-efficient.

  15. Breast cancer diagnosis using level-set statistics and support vector machines.

    Science.gov (United States)

    Liu, Jianguo; Yuan, Xiaohui; Buckles, Bill P

    2008-01-01

    Breast cancer diagnosis based on microscopic biopsy images and machine learning has demonstrated great promise in the past two decades. Various feature selection (or extraction) and classification algorithms have been attempted with success. However, some feature selection processes are complex and the number of features used can be quite large. We propose a new feature selection method based on level-set statistics. This procedure is simple and, when used with support vector machines (SVM), only a small number of features is needed to achieve satisfactory accuracy that is comparable to those using more sophisticated features. Therefore, the classification can be completed in much shorter time. We use multi-class support vector machines as the classification tool. Numerical results are reported to support the viability of this new procedure.

  16. Large deformation solid-fluid interaction via a level set approach.

    Energy Technology Data Exchange (ETDEWEB)

    Schunk, Peter Randall; Noble, David R.; Baer, Thomas A.; Rao, Rekha Ranjana; Notz, Patrick K.; Wilkes, Edward Dean

    2003-12-01

    Solidification and blood flow seemingly have little in common, but each involves a fluid in contact with a deformable solid. In these systems, the solid-fluid interface moves as the solid advects and deforms, often traversing the entire domain of interest. Currently, these problems cannot be simulated without innumerable expensive remeshing steps, mesh manipulations or decoupling the solid and fluid motion. Despite the wealth of progress recently made in mechanics modeling, this glaring inadequacy persists. We propose a new technique that tracks the interface implicitly and circumvents the need for remeshing and remapping the solution onto the new mesh. The solid-fluid boundary is tracked with a level set algorithm that changes the equation type dynamically depending on the phases present. This novel approach to coupled mechanics problems promises to give accurate stresses, displacements and velocities in both phases, simultaneously.

  17. A Level Set Analysis and A Nonparametric Regression on S&P 500 Daily Return

    Directory of Open Access Journals (Sweden)

    Yipeng Yang

    2016-02-01

    Full Text Available In this paper, a level set analysis is proposed which aims to analyze the S&P 500 return with a certain magnitude. It is found that the process of large jumps/drops of return tend to have negative serial correlation, and volatility clustering phenomenon can be easily seen. Then, a nonparametric analysis is performed and new patterns are discovered. An ARCH model is constructed based on the patterns we discovered and it is capable of manifesting the volatility skew in option pricing. A comparison of our model with the GARCH(1,1 model is carried out. The explanation of the validity on our model through prospect theory is provided, and, as a novelty, we linked the volatility skew phenomenon to the prospect theory in behavioral finance.

  18. Defining obesity: second-level agenda setting attributes in black newspapers and general audience newspapers.

    Science.gov (United States)

    Lee, Hyunmin; Len-Ríos, María E

    2014-01-01

    This content analysis study examines how obesity is depicted in general-audience and Black newspaper stories (N=391) through the lens of second-level agenda setting theory. The results reveal that both Black newspapers and general-audience newspapers generally ascribe individual causes for obesity. While both types of newspapers largely neglected to mention solutions for the problem, Black newspapers were more likely than general-audience newspapers to suggest both individual and societal solutions for treating obesity. For Black newspapers, these solutions more often included community interventions. In addition, Black newspapers more often used a negative tone in stories and more frequently mentioned ethnic and racial minorities as at-risk groups.

  19. SVM for density estimation and application to medical image segmentation

    Institute of Scientific and Technical Information of China (English)

    ZHANG Zhao; ZHANG Su; ZHANG Chen-xi; CHEN Ya-zhu

    2006-01-01

    A method of medical image segmentation based on support vector machine (SVM) for density estimation is presented. We used this estimator to construct a prior model of the image intensity and curvature profile of the structure from training images. When segmenting a novel image similar to the training images, the technique of narrow level set method is used. The higher dimensional surface evolution metric is defined by the prior model instead of by energy minimization function. This method offers several advantages. First, SVM for density estimation is consistent and its solution is sparse. Second, compared to the traditional level set methods, this method incorporates shape information on the object to be segmented into the segmentation process.Segmentation results are demonstrated on synthetic images, MR images and ultrasonic images.

  20. Modeling the advection of discontinuous quantities in Geophysical flows using Particle Level Sets

    Science.gov (United States)

    Aleksandrov, V.; Samuel, H.; Evonuk, M.

    2010-12-01

    Advection is one of the major processes that commonly acts on various scales in nature (core formation, mantle convective stirring, multi-phase flows in magma chambers, salt diapirism ...). While this process can be modeled numerically by solving conservation equations, various geodynamic scenarios involve advection of quantities with sharp discontinuities. Unfortunately, in these cases modeling numerically pure advection becomes very challenging, in particular because sharp discontinuities lead to numerical instabilities, which prevent the local use of high order numerical schemes. Several approaches have been used in computational geodynamics in order to overcome this difficulty, with variable amounts of success. Despite the use of correcting filters or non-oscillatory, shock-preserving schemes, Eulerian (fixed grid) techniques generally suffer from artificial numerical diffusion. Lagrangian approaches (dynamic grids or particles) tend to be more popular in computational geodynamics because they are not prone to excessive numerical diffusion. However, these approaches are generally computationally expensive, especially in 3D, and can suffer from spurious statistical noise. As an alternative to these aforementioned approaches, we have applied a relatively recent Particle Level set method [Enright et al., 2002] for modeling advection of quantities with the presence of sharp discontinuities. We have tested this improved method, which combines the best of Eulerian and Lagrangian approaches, against well known benchmarks and classical Geodynamic flows. In each case the Particle Level Set method accuracy equals or is better than other Eulerian and Lagrangian methods, and leads to significantly smaller computational cost, in particular in three-dimensional flows, where the reduction of computational time for modeling advection processes is most needed.

  1. Characterizing the spatiotemporal variability of groundwater levels of alluvial aquifers in different settings using drought indices

    Science.gov (United States)

    Haas, Johannes Christoph; Birk, Steffen

    2017-05-01

    To improve the understanding of how aquifers in different alluvial settings respond to extreme events in a changing environment, we analyze standardized time series of groundwater levels (Standardized Groundwater level Index - SGI), precipitation (Standardized Precipitation Index - SPI), and river stages of three subregions within the catchment of the river Mur (Austria). Using correlation matrices, differences and similarities between the subregions, ranging from the Alpine upstream part of the catchment to its shallow foreland basin, are identified and visualized. Generally, river stages exhibit the highest correlations with groundwater levels, frequently affecting not only the wells closest to the river, but also more distant parts of the alluvial aquifer. As a result, human impacts on the river are transferred to the aquifer, thus affecting the behavior of groundwater levels. Hence, to avoid misinterpretation of groundwater levels in this type of setting, it is important to account for the river and human impacts on it. While the river is a controlling factor in all of the subregions, an influence of precipitation is evident too. Except for deep wells found in an upstream Alpine basin, groundwater levels show the highest correlation with a precipitation accumulation period of 6 months (SPI6). The correlation in the foreland is generally higher than that in the Alpine subregions, thus corresponding to a trend from deeper wells in the Alpine parts of the catchment towards more shallow wells in the foreland. Extreme events are found to affect the aquifer in different ways. As shown with the well-known European 2003 drought and the local 2009 floods, correlations are reduced under flood conditions, but increased under drought. Thus, precipitation, groundwater levels and river stages tend to exhibit uniform behavior under drought conditions, whereas they may show irregular behavior during floods. Similarly, correlations are found to be weaker in years with little

  2. Assessing the Potential for Salmon Recovery via Floodplain Restoration: A Multitrophic Level Comparison of Dredge-Mined to Reference Segments

    Science.gov (United States)

    Bellmore, J. Ryan; Baxter, Colden V.; Ray, Andrew M.; Denny, Lytle; Tardy, Kurt; Galloway, Evelyn

    2012-03-01

    Pre-restoration studies typically focus on physical habitat, rather than the food-base that supports aquatic species. However, both food and habitat are necessary to support the species that habitat restoration is frequently aimed at recovering. Here we evaluate if and how the productivity of the food-base that supports fish production is impaired in a dredge-mined floodplain within the Yankee Fork Salmon River (YFSR), Idaho (USA); a site where past restoration has occurred and where more has been proposed to help recover anadromous salmonids. Utilizing an ecosystem approach, we found that the dredged segment had comparable terrestrial leaf and invertebrate inputs, aquatic primary producer biomass, and production of aquatic invertebrates relative to five reference floodplains. Thus, the food-base in the dredged segment did not necessarily appear impaired. On the other hand, we observed that off-channel aquatic habitats were frequently important to productivity in reference floodplains, and the connection of these habitats in the dredged segment via previous restoration increased invertebrate productivity by 58%. However, using a simple bioenergetic model, we estimated that the invertebrate food-base was at least 4× larger than present demand for food by fish in dredged and reference segments. In the context of salmon recovery efforts, this observation questions whether additional food-base productivity provided by further habitat restoration would be warranted in the YFSR. Together, our findings highlight the importance of studies that assess the aquatic food-base, and emphasize the need for more robust ecosystem models that evaluate factors potentially limiting fish populations that are the target of restoration.

  3. Coupled Shape Model Segmentation in Pig Carcasses

    DEFF Research Database (Denmark)

    Hansen, Mads Fogtmann; Larsen, Rasmus; Ersbøll, Bjarne Kjær;

    2006-01-01

    In this paper we are concerned with multi-object segmentation. For each object we will train a level set function based shape prior from a sample set of outlines. The outlines are aligned in a multi-resolution scheme wrt. an Euclidean similarity transformation in order to maximize the overlap...... levels inside the outline as well as in a narrow band outside the outline. The maximum a posteriori estimate of the outline is found by gradient descent optimization. In order to segment a group of mutually dependent objects we propose 2 procedures, 1) the objects are found sequentially by conditioning...... the initialization of the next search from already found objects; 2) all objects are found simultaneously and a repelling force is introduced in order to avoid overlap between outlines in the solution. The methods are applied to segmentation of cross sections of muscles in slices of CT scans of pig backs for quality...

  4. Scene setting: criteria for acceptability and suspension levels in diagnostic radiology, nuclear medicine and radiotherapy.

    Science.gov (United States)

    Malone, Jim; Faulkner, Keith; Christofides, Stelios; Lillicrap, Stephen; Horton, Patrick

    2013-02-01

    The EC (European Commission) Directive on radiation protection of patients requires that Criteria for Acceptability of Equipment in Diagnostic Radiology, Nuclear Medicine and Radiotherapy be established throughout the member states. This paper reviews the background to this requirement and to its implementation in practice. It notes parallel requirements in the EC medical devices directive and International Electrotechnical Commission standards. It is also important to be aware and that both sets of requirements should ideally be harmonised due to the global nature of the equipment industry. The paper further reviews the type of criteria that can be well applied for the above purposes, and defines qualitative criteria and suspension levels suitable for application. Both are defined and relationships with other acceptance processes are considered (including acceptance testing at the time of purchase, commissioning and the issue of second-hand equipment). Suspension levels are divided into four types, A, B, C and D, depending on the quality of evidence and consensus on which they are based. Exceptional situations involving, for example, new or rapidly evolving technology are also considered. The publication and paper focuses on the role of the holder of the equipment and related staff, particularly the medical physics expert and the practitioner. Advice on how the criteria should be created and implemented and how this might be coordinated with the supplier is provided for these groups. Additional advice on the role of the regulator is provided.

  5. Cooperative fuzzy games approach to setting target levels of ECs in quality function deployment.

    Science.gov (United States)

    Yang, Zhihui; Chen, Yizeng; Yin, Yunqiang

    2014-01-01

    Quality function deployment (QFD) can provide a means of translating customer requirements (CRs) into engineering characteristics (ECs) for each stage of product development and production. The main objective of QFD-based product planning is to determine the target levels of ECs for a new product or service. QFD is a breakthrough tool which can effectively reduce the gap between CRs and a new product/service. Even though there are conflicts among some ECs, the objective of developing new product is to maximize the overall customer satisfaction. Therefore, there may be room for cooperation among ECs. A cooperative game framework combined with fuzzy set theory is developed to determine the target levels of the ECs in QFD. The key to develop the model is the formulation of the bargaining function. In the proposed methodology, the players are viewed as the membership functions of ECs to formulate the bargaining function. The solution for the proposed model is Pareto-optimal. An illustrated example is cited to demonstrate the application and performance of the proposed approach.

  6. Cooperative Fuzzy Games Approach to Setting Target Levels of ECs in Quality Function Deployment

    Directory of Open Access Journals (Sweden)

    Zhihui Yang

    2014-01-01

    Full Text Available Quality function deployment (QFD can provide a means of translating customer requirements (CRs into engineering characteristics (ECs for each stage of product development and production. The main objective of QFD-based product planning is to determine the target levels of ECs for a new product or service. QFD is a breakthrough tool which can effectively reduce the gap between CRs and a new product/service. Even though there are conflicts among some ECs, the objective of developing new product is to maximize the overall customer satisfaction. Therefore, there may be room for cooperation among ECs. A cooperative game framework combined with fuzzy set theory is developed to determine the target levels of the ECs in QFD. The key to develop the model is the formulation of the bargaining function. In the proposed methodology, the players are viewed as the membership functions of ECs to formulate the bargaining function. The solution for the proposed model is Pareto-optimal. An illustrated example is cited to demonstrate the application and performance of the proposed approach.

  7. A comparison of subtalar joint motion during anticipated medial cutting turns and level walking using a multi-segment foot model.

    Science.gov (United States)

    Jenkyn, T R; Shultz, R; Giffin, J R; Birmingham, T B

    2010-02-01

    The weight-bearing in-vivo kinematics and kinetics of the talocrural joint, subtalar joint and joints of the foot were quantified using optical motion analysis. Twelve healthy subjects were studied during level walking and anticipated medial turns at self-selected pace. A multi-segment model of the foot using skin-mounted marker triads tracked four foot segments: the hindfoot, midfoot, lateral and medial forefoot. The lower leg and thigh were also tracked. Motion between each of the segments could occur in three degrees of rotational freedom, but only six inter-segmental motions were reported in this study: (1) talocrural dorsi-plantar-flexion, (2) subtalar inversion-eversion, (3) frontal plane hindfoot motion, (4) transverse plane hindfoot motion, (5) forefoot supination-pronation twisting and (6) the height-to-length ratio of the medial longitudinal arch. The motion at the subtalar joint during stance phase of walking (eversion then inversion) was reversed during a turning task (inversion then eversion). The external subtalar joint moment was also changed from a moderate eversion moment during walking to a larger inversion moment during the turn. The kinematics of the talocrural joint and the joints of the foot were similar between these two tasks. During a medial turn, the subtalar joint may act to maintain the motions in the foot and talocrural joint that occur during level walking. This is occurring despite the conspicuously different trajectory of the centre of mass of the body. This may allow the foot complex to maintain its function of energy absorption followed by energy return during stance phase that is best suited to level walking.

  8. Computer-aided detection of colonic polyps with level set-based adaptive convolution in volumetric mucosa to advance CT colonography toward a screening modality

    Science.gov (United States)

    Zhu, Hongbin; Duan, Chaijie; Pickhardt, Perry; Wang, Su; Liang, Zhengrong

    2009-01-01

    As a promising second reader of computed tomographic colonography (CTC) screening, the computer-aided detection (CAD) of colonic polyps has earned fast growing research interest. In this paper, we present a CAD scheme to automatically detect colonic polyps in CTC images. First, a thick colon wall representation, ie, a volumetric mucosa (VM) with several voxels wide in general, was segmented from CTC images by a partial-volume image segmentation algorithm. Based on the VM, we employed a level set-based adaptive convolution method for calculating the first- and second-order spatial derivatives more accurately to start the geometric analysis. Furthermore, to emphasize the correspondence among different layers in the VM, we introduced a middle-layer enhanced integration along the image gradient direction inside the VM to improve the operation of extracting the geometric information, like the principal curvatures. Initial polyp candidates (IPCs) were then determined by thresholding the geometric measurements. Based on IPCs, several features were extracted for each IPC, and fed into a support vector machine to reduce false positives (FPs). The final detections were displayed in a commercial system to provide second opinions for radiologists. The CAD scheme was applied to 26 patient CTC studies with 32 confirmed polyps by both optical and virtual colonoscopies. Compared to our previous work, all the polyps can be detected successfully with less FPs. At the 100% by polyp sensitivity, the new method yielded 3.5 FPs/dataset. PMID:20428331

  9. Are Tide Gauges Useful Recorders of Relative Sea-Level Rise in Large Deltaic Settings?

    Science.gov (United States)

    Tornqvist, T. E.; Keogh, M.; Jankowski, K. L.; Fernandes, A. M.

    2016-12-01

    It has long been recognized that the world's largest deltas that often host major population centers are particularly vulnerable to accelerating rates of relative sea-level rise (RSLR). Traditionally, tide-gauge records are used to obtain quantitative data on rates of RSLR, given that they are perceived to capture the rise of the sea surface as well as land subsidence which is often substantial in deltaic settings. We argue here that tide gauges in such settings often provide ambiguous data because they ultimately measure RSLR with respect to a benchmark that is typically anchored tens of meters below the land surface. This is problematic because the prime target of interest is usually the rate of RSLR with respect to the delta top. We illustrate this problem with newly obtained rod surface elevation table - marker horizon (RSET-MH) data from the Mississippi Delta (n=185) that show that total subsidence is dominated by shallow subsidence in the uppermost 5-10 m. Since benchmarks in this region are anchored at 20 m depth on average, tide-gauge records by definition do not capture this important (and often even dominant) component of total subsidence, and thus underestimate RSLR by a considerable amount. We show how RSET-MH data, combined with GPS and satellite altimetry data, enable us to bypass this problem. Present-day rates of RSLR in the Mississippi Delta are 13±9 mm/yr, considerably higher than numbers reported in recent studies based on tide-gauge analysis. It seems unlikely that this problem is unique to the Mississippi Delta, so we argue that the approach to RSLR measurements in large deltas across the planet needs rethinking.

  10. Sparsity and level set regularization for diffuse optical tomography using a transport model in 2D

    Science.gov (United States)

    Prieto, Kernel; Dorn, Oliver

    2017-01-01

    In this paper we address an inverse problem for the time-dependent linear transport equation (or radiative transfer equation) in 2D having in mind applications in diffuse optical tomography (DOT). We propose two new reconstruction algorithms which so far have not been applied to such a situation and compare their performances in certain practically relevant situations. The first of these reconstruction algorithms uses a sparsity promoting regularization scheme, whereas the second one uses a simultaneous level set reconstruction scheme for two parameters of the linear transport equation. We will also compare the results of both schemes with a third scheme which is a more traditional L 2-based Landweber-Kaczmarz scheme. We focus our attention on the DOT application of imaging the human head of a neonate where the simpler diffusion approximation is not well-suited for the inversion due to the presence of a clear layer beneath the skull which is filled with ‘low-scattering’ cerebrospinal fluid. This layer, even if its location and characteristics are known a priori, poses significant difficulties for most reconstruction schemes due to its ‘wave-guiding’ property which reduces sensitivity of the data to the interior regions. A further complication arises due to the necessity to reconstruct simultaneously two different parameters of the linear transport equation, the scattering and the absorption cross-section, from the same data set. A significant ‘cross-talk’ between these two parameters is usually expected. Our numerical experiments indicate that each of the three considered reconstruction schemes do have their merits and perform differently but reasonably well when the clear layer is a priori known. We also demonstrate the behavior of the three algorithms in the particular situation where the clear layer is unknown during the reconstruction.

  11. Segmentation: Identification of consumer segments

    DEFF Research Database (Denmark)

    Høg, Esben

    2005-01-01

    It is very common to categorise people, especially in the advertising business. Also traditional marketing theory has taken in consumer segments as a favorite topic. Segmentation is closely related to the broader concept of classification. From a historical point of view, classification has its...... and analysed possible segments in the market. Results show that the statistical model used identified two segments - a segment of so-called "fish lovers" and another segment called "traditionalists". The "fish lovers" are very fond of eating fish and they actually prefer fish to other dishes...... origin in other sciences as for example biology, anthropology etc. From an economic point of view, it is called segmentation when specific scientific techniques are used to classify consumers to different characteristic groupings. What is the purpose of segmentation? For example, to be able to obtain...

  12. Home advantage in high-level volleyball varies according to set number.

    Science.gov (United States)

    Marcelino, Rui; Mesquita, Isabel; Palao Andrés, José Manuel; Sampaio, Jaime

    2009-01-01

    The aim of the present study was to identify the probability of winning each Volleyball set according to game location (home, away). Archival data was obtained from 275 sets in the 2005 Men's Senior World League and 65,949 actions were analysed. Set result (win, loss), game location (home, away), set number (first, second, third, fourth and fifth) and performance indicators (serve, reception, set, attack, dig and block) were the variables considered in this study. In a first moment, performance indicators were used in a logistic model of set result, by binary logistic regression analysis. After finding the adjusted logistic model, the log-odds of winning the set were analysed according to game location and set number. The results showed that winning a set is significantly related to performance indicators (Chisquare(18)=660.97, pteams always have more probability of winning the game than away teams, regardless of the set number. Home teams have more advantage at the beginning of the game (first set) and in the two last sets of the game (fourth and fifth sets), probably due to facilities familiarity and crowd effects. Different game actions explain these advantages and showed that to win the first set is more important to take risk, through a better performance in the attack and block, and to win the final set is important to manage the risk through a better performance on the reception. These results may suggest intra-game variation in home advantage and can be most useful to better prepare and direct the competition. Key pointsHome teams always have more probability of winning the game than away teams.Home teams have higher performance in reception, set and attack in the total of the sets.The advantage of home teams is more pronounced at the beginning of the game (first set) and in two last sets of the game (fourth and fifth sets) suggesting intra-game variation in home advantage.Analysis by sets showed that home teams have a better performance in the attack and

  13. Multilevel segmentation of intracranial aneurysms in CT angiography images

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Yan [Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California 94122 and University of Lyon, CREATIS, CNRS UMR 5220, INSERM U1206, UCB Lyon1, INSA Lyon, Lyon 69100 (France); Zhang, Yue, E-mail: y.zhang525@gmail.com [Veterans Affairs Medical Center, San Francisco, California 94121 and University of Lyon, CREATIS, CNRS UMR 5220, INSERM U1206, UCB Lyon1, INSA Lyon, Lyon 69100 (France); Navarro, Laurent [Ecole Nationale Superieure des Mines de Saint-Etienne, Saint-Etienne 42015 (France); Eker, Omer Faruk [CHU Montpellier, Neuroradiologie, Montpellier 34000 (France); Corredor Jerez, Ricardo A. [Ecole Polytechnique Federale de Lausanne, Lausanne 1015 (Switzerland); Chen, Yu; Zhu, Yuemin; Courbebaisse, Guy [University of Lyon, CREATIS, CNRS UMR 5220, INSERM U1206, UCB Lyon1, INSA Lyon, Lyon 69100 (France)

    2016-04-15

    Purpose: Segmentation of aneurysms plays an important role in interventional planning. Yet, the segmentation of both the lumen and the thrombus of an intracranial aneurysm in computed tomography angiography (CTA) remains a challenge. This paper proposes a multilevel segmentation methodology for efficiently segmenting intracranial aneurysms in CTA images. Methods: The proposed methodology first uses the lattice Boltzmann method (LBM) to extract the lumen part directly from the original image. Then, the LBM is applied again on an intermediate image whose lumen part is filled by the mean gray-level value outside the lumen, to yield an image region containing part of the aneurysm boundary. After that, an expanding disk is introduced to estimate the complete contour of the aneurysm. Finally, the contour detected is used as the initial contour of the level set with ellipse to refine the aneurysm. Results: The results obtained on 11 patients from different hospitals showed that the proposed segmentation was comparable with manual segmentation, and that quantitatively, the average segmentation matching factor (SMF) reached 86.99%, demonstrating good segmentation accuracy. Chan–Vese method, Sen’s model, and Luca’s model were used to compare the proposed method and their average SMF values were 39.98%, 40.76%, and 77.11%, respectively. Conclusions: The authors have presented a multilevel segmentation method based on the LBM and level set with ellipse for accurate segmentation of intracranial aneurysms. Compared to three existing methods, for all eleven patients, the proposed method can successfully segment the lumen with the highest SMF values for nine patients and second highest SMF values for the two. It also segments the entire aneurysm with the highest SMF values for ten patients and second highest SMF value for the one. This makes it potential for clinical assessment of the volume and aspect ratio of the intracranial aneurysms.

  14. On the modeling of bubble evolution and transport using coupled level-set/CFD method

    Energy Technology Data Exchange (ETDEWEB)

    Bartlomiej Wierzbicki; Steven P Antal; Michael Z Podowski [Dept. of Mechanical, Aerospace and Nuclear Engineering, and Center for Multiphase Research, Rensselaer Polytechnic Institute, Troy, NY 12180 (United States)

    2005-07-01

    Full text of publication follows: The ability to predict the shape of the gas/liquid/solid interfaces is important for various multiphase flow and heat transfer applications. Specific issues of interest to nuclear reactor thermal-hydraulics, include the evolution of the shape of bubbles attached to solid surfaces during nucleation, bubble surface interactions in complex geometries, etc. Additional problems, making the overall task even more complicated, are associated with the effect of material properties that may be significantly altered by the addition of minute amounts of impurities, such as surfactants or nano-particles. The present paper is concerned with the development of an innovative approach to model time-dependent shape of gas/liquid interfaces in the presence of solid walls. The proposed approach combines a modified level-set method with an advanced CFD code, NPHASE. The coupled numerical solver can be used to simulate the evolution of gas/liquid interfaces in two-phase flows for a variety of geometries and flow conditions, from individual bubbles to free surfaces (stratified flows). The issues discussed in the full paper will include: a description of the novel aspects of the proposed level-set concept based method, an overview of the NPHASE code modeling framework and a description of the coupling method between these two elements of the overall model. A particular attention will be give to the consistency and completeness of model formulation for the interfacial phenomena near the liquid/gas/solid triple line, and to the impact of the proposed numerical approach on the accuracy and consistency of predictions. The accuracy will be measured in terms of both the calculated shape of the interfaces and the gas and liquid velocity fields around the interfaces and in the entire computational domain. The results of model testing and validation will also be shown in the full paper. The situations analyzed will include: bubbles of different sizes and varying

  15. HOME ADVANTAGE IN HIGH-LEVEL VOLLEYBALL VARIES ACCORDING TO SET NUMBER

    Directory of Open Access Journals (Sweden)

    Rui Marcelino

    2009-09-01

    Full Text Available The aim of the present study was to identify the probability of winning each Volleyball set according to game location (home, away. Archival data was obtained from 275 sets in the 2005 Men's Senior World League and 65,949 actions were analysed. Set result (win, loss, game location (home, away, set number (first, second, third, fourth and fifth and performance indicators (serve, reception, set, attack, dig and block were the variables considered in this study. In a first moment, performance indicators were used in a logistic model of set result, by binary logistic regression analysis. After finding the adjusted logistic model, the log-odds of winning the set were analysed according to game location and set number. The results showed that winning a set is significantly related to performance indicators (Chi-square(18=660.97, p<0.01. Analyses of log-odds of winning a set demonstrate that home teams always have more probability of winning the game than away teams, regardless of the set number. Home teams have more advantage at the beginning of the game (first set and in the two last sets of the game (fourth and fifth sets, probably due to facilities familiarity and crowd effects. Different game actions explain these advantages and showed that to win the first set is more important to take risk, through a better performance in the attack and block, and to win the final set is important to manage the risk through a better performance on the reception. These results may suggest intra-game variation in home advantage and can be most useful to better prepare and direct the competition

  16. Low-level 14C methane oxidation rate measurements modified for remote field settings

    Science.gov (United States)

    Pack, M. A.; Pohlman, J.; Ruppel, C. D.; Xu, X.

    2012-12-01

    Aerobic methane oxidation limits atmospheric methane emissions from degraded subsea permafrost and dissociated methane hydrates in high latitude oceans. Methane oxidation rate measurements are a crucial tool for investigating the efficacy of this process, but are logistically challenging when working on small research vessels in remote settings. We modified a low-level 14C-CH4 oxidation rate measurement for use in the Beaufort Sea above hydrate bearing sediments during August 2012. Application of the more common 3H-CH4 rate measurement that uses 106 times more radioactivity was not practical because the R/V Ukpik cannot accommodate a radiation van. The low-level 14C measurement does not require a radiation van, but careful isolation of the 14C-label is essential to avoid contaminating natural abundance 14C measurements. We used 14C-CH4 with a total activity of 1.1 μCi, which is far below the 100 μCi permitting level. In addition, we modified field procedures to simplify and shorten sample processing. The original low-level 14C-CH4 method requires 6 steps in the field: (1) collect water samples in glass serum bottles, (2) inject 14C-CH4 into bottles, (3) incubate for 24 hours, (4) filter to separate the methanotrophic bacterial cells from the aqueous sample, (5) kill the filtrate with sodium hydroxide (NaOH), and (6) purge with nitrogen to remove unused 14C-CH4. Onshore, the 14C-CH4 respired to carbon dioxide or incorporated into cell material by methanotrophic bacteria during incubation is quantified by accelerator mass spectrometry (AMS). We conducted an experiment to test the possibility of storing samples for purging and filtering back onshore (steps 4 and 6). We subjected a series of water samples to steps 1-3 & 5, and preserved with mercuric chloride (HgCl2) instead of NaOH because HgCl2 is less likely to break down cell material during storage. The 14C-content of the carbon dioxide in samples preserved with HgCl2 and stored for up to 2 weeks was stable

  17. Evaluation of two-phase flow solvers using Level Set and Volume of Fluid methods

    Science.gov (United States)

    Bilger, C.; Aboukhedr, M.; Vogiatzaki, K.; Cant, R. S.

    2017-09-01

    Two principal methods have been used to simulate the evolution of two-phase immiscible flows of liquid and gas separated by an interface. These are the Level-Set (LS) method and the Volume of Fluid (VoF) method. Both methods attempt to represent the very sharp interface between the phases and to deal with the large jumps in physical properties associated with it. Both methods have their own strengths and weaknesses. For example, the VoF method is known to be prone to excessive numerical diffusion, while the basic LS method has some difficulty in conserving mass. Major progress has been made in remedying these deficiencies, and both methods have now reached a high level of physical accuracy. Nevertheless, there remains an issue, in that each of these methods has been developed by different research groups, using different codes and most importantly the implementations have been fine tuned to tackle different applications. Thus, it remains unclear what are the remaining advantages and drawbacks of each method relative to the other, and what might be the optimal way to unify them. In this paper, we address this gap by performing a direct comparison of two current state-of-the-art variations of these methods (LS: RCLSFoam and VoF: interPore) and implemented in the same code (OpenFoam). We subject both methods to a pair of benchmark test cases while using the same numerical meshes to examine a) the accuracy of curvature representation, b) the effect of tuning parameters, c) the ability to minimise spurious velocities and d) the ability to tackle fluids with very different densities. For each method, one of the test cases is chosen to be fairly benign while the other test case is expected to present a greater challenge. The results indicate that both methods can be made to work well on both test cases, while displaying different sensitivity to the relevant parameters.

  18. Comparing volume of fluid and level set methods for evaporating liquid-gas flows

    Science.gov (United States)

    Palmore, John; Desjardins, Olivier

    2016-11-01

    This presentation demonstrates three numerical strategies for simulating liquid-gas flows undergoing evaporation. The practical aim of this work is to choose a framework capable of simulating the combustion of liquid fuels in an internal combustion engine. Each framework is analyzed with respect to its accuracy and computational cost. All simulations are performed using a conservative, finite volume code for simulating reacting, multiphase flows under the low-Mach assumption. The strategies used in this study correspond to different methods for tracking the liquid-gas interface and handling the transport of the discontinuous momentum and vapor mass fractions fields. The first two strategies are based on conservative, geometric volume of fluid schemes using directionally split and un-split advection, respectively. The third strategy is the accurate conservative level set method. For all strategies, special attention is given to ensuring the consistency between the fluxes of mass, momentum, and vapor fractions. The study performs three-dimensional simulations of an isolated droplet of a single component fuel evaporating into air. Evaporation rates and vapor mass fractions are compared to analytical results.

  19. Automatic Application Level Set Approach in Detection Calcifications in Mammographic Image

    CERN Document Server

    Boujelben, Atef; Mnif, Jameleddine; Abid, Mohamed

    2011-01-01

    Breast cancer is considered as one of a major health problem that constitutes the strongest cause behind mortality among women in the world. So, in this decade, breast cancer is the second most common type of cancer, in term of appearance frequency, and the fifth most common cause of cancer related death. In order to reduce the workload on radiologists, a variety of CAD systems; Computer-Aided Diagnosis (CADi) and Computer-Aided Detection (CADe) have been proposed. In this paper, we interested on CADe tool to help radiologist to detect cancer. The proposed CADe is based on a three-step work flow; namely, detection, analysis and classification. This paper deals with the problem of automatic detection of Region Of Interest (ROI) based on Level Set approach depended on edge and region criteria. This approach gives good visual information from the radiologist. After that, the features extraction using textures characteristics and the vector classification using Multilayer Perception (MLP) and k-Nearest Neighbours...

  20. Numerical Simulation of Two-phase flow with Phase Change Using the Level-set Method

    Science.gov (United States)

    Li, Hongying; Lou, Jing; Pan, Lunsheng; Yap, Yitfatt

    2016-11-01

    Multiphase flow with phase change is widely encountered in many engineering applications. A distinct feature involves in these applications is the phase transition from one phase to another due to the non-uniform temperature distribution. Such kind of process generally releases or absorbs large amount of energy with mass transfer happened simultaneously. It demands great cautions occasionally such as the high pressure due to evaporation. This article presents a numerical model for simulation of two-fluid flow with phase change problem. In these two fluids, one of them changes its state due to phase change. Such a problem then involves two substances with three phases as well as two different interfaces, i.e. the interface between two substances and the interface of one substance between its two phases. Two level-set functions are used to capture the two interfaces in the current problem. The current model is validated against one-dimensional and two-dimensional liquid evaporation. With the code validated, it is applied to different phase change problems including (1) a falling evaporating droplet and the rising of one bubble and (2) two-fluid stratified flow with solidification of one fluid. Comparisons on the bubble and droplet topologies, flow and temperature fields are made for the first case between the falling evaporating droplet and the falling droplet without evaporation. For the second demonstration case, the effect of the superheated temperature on the solidification process is investigated.

  1. Level set simulations of the anisotropic wet etching process for device fabrication in nanotechnologies

    Directory of Open Access Journals (Sweden)

    Rađenović Branislav

    2010-01-01

    Full Text Available Chemical etching is employed as micromachining manufacturing process to produce micron-size components. As a semiconductor wafer is extremely expensive due to many processing steps involved in the making thereof, the need to critically control the etching end point in an etching process is highly desirable. It was found that not only the etchant and temperature determine the exact anisotropy of etched silicon. The angle between the silicon surface and the mask was also shown to play an important role. In this paper, angular dependence of the etching rate is calculated on the base of the silicon symmetry properties, by means of the interpolation technique using experimentally obtained values of the principal <100>, <110>, <111> directions in KOH solutions. The calculations are performed using an extension of the sparse field method for solving three dimensional (3D level set equations that describe the morphological surface evolution during etching process. The analysis of the obtained results confirm that regardless of the initial shape the profile evolution ends with the crystal form composed of the fastest etching planes, {110} in our model.

  2. Ensemble segmentation using efficient integer linear programming.

    Science.gov (United States)

    Alush, Amir; Goldberger, Jacob

    2012-10-01

    We present a method for combining several segmentations of an image into a single one that in some sense is the average segmentation in order to achieve a more reliable and accurate segmentation result. The goal is to find a point in the "space of segmentations" which is close to all the individual segmentations. We present an algorithm for segmentation averaging. The image is first oversegmented into superpixels. Next, each segmentation is projected onto the superpixel map. An instance of the EM algorithm combined with integer linear programming is applied on the set of binary merging decisions of neighboring superpixels to obtain the average segmentation. Apart from segmentation averaging, the algorithm also reports the reliability of each segmentation. The performance of the proposed algorithm is demonstrated on manually annotated images from the Berkeley segmentation data set and on the results of automatic segmentation algorithms.

  3. DESIRE FOR LEVELS. Background study for the policy document "Setting Environmental Quality Standards for Water and Soil"

    NARCIS (Netherlands)

    van de Meent D; Aldenberg T; Canton JH; van Gestel CAM; Slooff W

    1990-01-01

    The report provides scientific support for setting environmental quality objectives for water, sediment and soil. Quality criteria are not set in this report. Only options for decisions are given. The report is restricted to the derivation of the 'maximally acceptable risk' levels (MAR)

  4. Shock capturing, level sets, and PDE based methods in computer vision and image processing: a review of Osher's contributions

    CERN Document Server

    Fedkiw, R P

    2003-01-01

    In this paper we review the algorithm development and applications in high resolution shock capturing methods, level set methods, and PDE based methods in computer vision and image processing. The emphasis is on Stanley Osher's contribution in these areas and the impact of his work. We will start with shock capturing methods and will review the Engquist-Osher scheme, TVD schemes, entropy conditions, ENO and WENO schemes, and numerical schemes for Hamilton-Jacobi type equations. Among level set methods we will review level set calculus, numerical techniques, fluids and materials, variational approach, high codimension motion, geometric optics, and the computation of discontinuous solutions to Hamilton-Jacobi equations. Among computer vision and image processing we will review the total variation model for image denoising, images on implicit surfaces, and the level set method in image processing and computer vision.

  5. A modification of level set re-initialized method for the shock waves through the air bubble

    Directory of Open Access Journals (Sweden)

    Zhang Li

    2014-01-01

    Full Text Available For the re-initialization problem of the level set method, a new re-initialization formula of smoothing parameter based on the traditional implicit method is proposed. The improved method is applied to describe the process of the shock through the air bubble by means of numerical simulation. Numerical results show that the method is superior to the traditional level set method.

  6. Topology Optimization using the Level Set and eXtended Finite Element Methods: Theory and Applications

    Science.gov (United States)

    Villanueva Perez, Carlos Hernan

    Computational design optimization provides designers with automated techniques to develop novel and non-intuitive optimal designs. Topology optimization is a design optimization technique that allows for the evolution of a broad variety of geometries in the optimization process. Traditional density-based topology optimization methods often lack a sufficient resolution of the geometry and physical response, which prevents direct use of the optimized design in manufacturing and the accurate modeling of the physical response of boundary conditions. The goal of this thesis is to introduce a unified topology optimization framework that uses the Level Set Method (LSM) to describe the design geometry and the eXtended Finite Element Method (XFEM) to solve the governing equations and measure the performance of the design. The methodology is presented as an alternative to density-based optimization approaches, and is able to accommodate a broad range of engineering design problems. The framework presents state-of-the-art methods for immersed boundary techniques to stabilize the systems of equations and enforce the boundary conditions, and is studied with applications in 2D and 3D linear elastic structures, incompressible flow, and energy and species transport problems to test the robustness and the characteristics of the method. A comparison of the framework against density-based topology optimization approaches is studied with regards to convergence, performance, and the capability to manufacture the designs. Furthermore, the ability to control the shape of the design to operate within manufacturing constraints is developed and studied. The analysis capability of the framework is validated quantitatively through comparison against previous benchmark studies, and qualitatively through its application to topology optimization problems. The design optimization problems converge to intuitive designs and resembled well the results from previous 2D or density-based studies.

  7. Improving district level health planning and priority setting in Tanzania through implementing accountability for reasonableness framework

    DEFF Research Database (Denmark)

    Maluka, Stephen; Kamuzora, Peter; Sebastián, Miguel San

    2010-01-01

    In 2006, researchers and decision-makers launched a five-year project - Response to Accountable Priority Setting for Trust in Health Systems (REACT) - to improve planning and priority-setting through implementing the Accountability for Reasonableness framework in Mbarali District, Tanzania...

  8. Flash 型 FPGA 单粒子瞬态脉冲分段滤除电路设计%Segmented Filtering Circuit for SET Pulse in Flash-based FPGAs

    Institute of Scientific and Technical Information of China (English)

    史方显; 曾立; 王淼; 曹建勋; 权妙静

    2016-01-01

    为提高 FPGA 在辐射环境条件下的抗单粒子脉冲(SET)的能力,设计了一种由多个延时单元和并联逻辑保护单元(Guard Gate,GG)构成的 SET 脉冲分段滤除电路.将 SET 脉冲处理延时减小至传统方法的10.42%~49.8%,从而提高电路对 SET 脉冲的处理能力,同时占用的逻辑资源未有明显增加.%A segmented filtering circuit with delay units and guard gates is proposed to filter SET pulses with different width,considering the range and distribution of SET pulse widths produced in FPGA and the propagation induced pulse broadening.Dividing the widths of SET pulses into several intervals,parallel guard gates with different delay buffers generate corresponding results to different intervals.According to the results,this circuit selects the output in the shortest time,improving the performance on dealing with SET pulses.Simulation results in Fusion family flash-based FPGA indicate that,compared to traditional methods,the segmented filtering circuit can cut the filtering delay of SET pulse in critical path down to 10.42%~49.8%,while power consumption decreasing and no hardware resource increase.

  9. 一种基于HSV空间和粗糙集的彩色图像分割方法%Color Image Segmentation Based on HSV Space and Rough-set Theory

    Institute of Scientific and Technical Information of China (English)

    蔡式东; 杨芳

    2011-01-01

    The rough-set histogram thresholding method for color image segmentation based on HSV color space has been investigated. The color distance of HSV has been defined considering the properties of HSV space. The rough-set histogram of each component is calculated, while segmentation is applied. The experimental results demonstrate that the image color is well preserved and the satisfied segmentation can be obtained by this method.%研究了基于HSV颜色空间的粗糙集直方图阈值彩色图像分割方法.根据HSV空间的特性,定义了HSV空间颜色距离计算公式,对HSV三分量计算粗糙集直方图和彩色图像进行分割.实验结果表明该方法较好地保留了图像的颜色信息,具有较高的通用性,能够获得满意的分割效果.

  10. Left atrium segmentation for atrial fibrillation ablation

    Science.gov (United States)

    Karim, R.; Mohiaddin, R.; Rueckert, D.

    2008-03-01

    Segmentation of the left atrium is vital for pre-operative assessment of its anatomy in radio-frequency catheter ablation (RFCA) surgery. RFCA is commonly used for treating atrial fibrillation. In this paper we present an semi-automatic approach for segmenting the left atrium and the pulmonary veins from MR angiography (MRA) data sets. We also present an automatic approach for further subdividing the segmented atrium into the atrium body and the pulmonary veins. The segmentation algorithm is based on the notion that in MRA the atrium becomes connected to surrounding structures via partial volume affected voxels and narrow vessels, the atrium can be separated if these regions are characterized and identified. The blood pool, obtained by subtracting the pre- and post-contrast scans, is first segmented using a region-growing approach. The segmented blood pool is then subdivided into disjoint subdivisions based on its Euclidean distance transform. These subdivisions are then merged automatically starting from a seed point and stopping at points where the atrium leaks into a neighbouring structure. The resulting merged subdivisions produce the segmented atrium. Measuring the size of the pulmonary vein ostium is vital for selecting the optimal Lasso catheter diameter. We present a second technique for automatically identifying the atrium body from segmented left atrium images. The separating surface between the atrium body and the pulmonary veins gives the ostia locations and can play an important role in measuring their diameters. The technique relies on evolving interfaces modelled using level sets. Results have been presented on 20 patient MRA datasets.

  11. Improving district level health planning and priority setting in Tanzania through implementing accountability for reasonableness framework

    DEFF Research Database (Denmark)

    Maluka, Stephen; Kamuzora, Peter; Sebastián, Miguel San;

    2010-01-01

    In 2006, researchers and decision-makers launched a five-year project - Response to Accountable Priority Setting for Trust in Health Systems (REACT) - to improve planning and priority-setting through implementing the Accountability for Reasonableness framework in Mbarali District, Tanzania....... The objective of this paper is to explore the acceptability of Accountability for Reasonableness from the perspectives of the Council Health Management Team, local government officials, health workforce and members of user boards and committees....

  12. Strengthening fairness, transparency and accountability in health care priority setting at district level in Tanzania

    Directory of Open Access Journals (Sweden)

    Stephen Maluka

    2011-11-01

    Full Text Available Health care systems are faced with the challenge of resource scarcity and have insufficient resources to respond to all health problems and target groups simultaneously. Hence, priority setting is an inevitable aspect of every health system. However, priority setting is complex and difficult because the process is frequently influenced by political, institutional and managerial factors that are not considered by conventional priority-setting tools. In a five-year EU-supported project, which started in 2006, ways of strengthening fairness and accountability in priority setting in district health management were studied. This review is based on a PhD thesis that aimed to analyse health care organisation and management systems, and explore the potential and challenges of implementing Accountability for Reasonableness (A4R approach to priority setting in Tanzania. A qualitative case study in Mbarali district formed the basis of exploring the sociopolitical and institutional contexts within which health care decision making takes place. The study also explores how the A4R intervention was shaped, enabled and constrained by the contexts. Key informant interviews were conducted. Relevant documents were also gathered and group priority-setting processes in the district were observed. The study revealed that, despite the obvious national rhetoric on decentralisation, actual practice in the district involved little community participation. The assumption that devolution to local government promotes transparency, accountability and community participation, is far from reality. The study also found that while the A4R approach was perceived to be helpful in strengthening transparency, accountability and stakeholder engagement, integrating the innovation into the district health system was challenging. This study underscores the idea that greater involvement and accountability among local actors may increase the legitimacy and fairness of priority-setting

  13. SET overexpression in HEK293 cells regulates mitochondrial uncoupling proteins levels within a mitochondrial fission/reduced autophagic flux scenario

    Energy Technology Data Exchange (ETDEWEB)

    Almeida, Luciana O.; Goto, Renata N. [Department of Clinical Analyses, Toxicology and Food Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP (Brazil); Neto, Marinaldo P.C. [Department of Physics and Chemistry, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP (Brazil); Sousa, Lucas O. [Department of Clinical Analyses, Toxicology and Food Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP (Brazil); Curti, Carlos [Department of Physics and Chemistry, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP (Brazil); Leopoldino, Andréia M., E-mail: andreiaml@usp.br [Department of Clinical Analyses, Toxicology and Food Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP (Brazil)

    2015-03-06

    We hypothesized that SET, a protein accumulated in some cancer types and Alzheimer disease, is involved in cell death through mitochondrial mechanisms. We addressed the mRNA and protein levels of the mitochondrial uncoupling proteins UCP1, UCP2 and UCP3 (S and L isoforms) by quantitative real-time PCR and immunofluorescence as well as other mitochondrial involvements, in HEK293 cells overexpressing the SET protein (HEK293/SET), either in the presence or absence of oxidative stress induced by the pro-oxidant t-butyl hydroperoxide (t-BHP). SET overexpression in HEK293 cells decreased UCP1 and increased UCP2 and UCP3 (S/L) mRNA and protein levels, whilst also preventing lipid peroxidation and decreasing the content of cellular ATP. SET overexpression also (i) decreased the area of mitochondria and increased the number of organelles and lysosomes, (ii) increased mitochondrial fission, as demonstrated by increased FIS1 mRNA and FIS-1 protein levels, an apparent accumulation of DRP-1 protein, and an increase in the VDAC protein level, and (iii) reduced autophagic flux, as demonstrated by a decrease in LC3B lipidation (LC3B-II) in the presence of chloroquine. Therefore, SET overexpression in HEK293 cells promotes mitochondrial fission and reduces autophagic flux in apparent association with up-regulation of UCP2 and UCP3; this implies a potential involvement in cellular processes that are deregulated such as in Alzheimer's disease and cancer. - Highlights: • SET, UCPs and autophagy prevention are correlated. • SET action has mitochondrial involvement. • UCP2/3 may reduce ROS and prevent autophagy. • SET protects cell from ROS via UCP2/3.

  14. SET overexpression in HEK293 cells regulates mitochondrial uncoupling proteins levels within a mitochondrial fission/reduced autophagic flux scenario.

    Science.gov (United States)

    Almeida, Luciana O; Goto, Renata N; Neto, Marinaldo P C; Sousa, Lucas O; Curti, Carlos; Leopoldino, Andréia M

    2015-03-01

    We hypothesized that SET, a protein accumulated in some cancer types and Alzheimer disease, is involved in cell death through mitochondrial mechanisms. We addressed the mRNA and protein levels of the mitochondrial uncoupling proteins UCP1, UCP2 and UCP3 (S and L isoforms) by quantitative real-time PCR and immunofluorescence as well as other mitochondrial involvements, in HEK293 cells overexpressing the SET protein (HEK293/SET), either in the presence or absence of oxidative stress induced by the pro-oxidant t-butyl hydroperoxide (t-BHP). SET overexpression in HEK293 cells decreased UCP1 and increased UCP2 and UCP3 (S/L) mRNA and protein levels, whilst also preventing lipid peroxidation and decreasing the content of cellular ATP. SET overexpression also (i) decreased the area of mitochondria and increased the number of organelles and lysosomes, (ii) increased mitochondrial fission, as demonstrated by increased FIS1 mRNA and FIS-1 protein levels, an apparent accumulation of DRP-1 protein, and an increase in the VDAC protein level, and (iii) reduced autophagic flux, as demonstrated by a decrease in LC3B lipidation (LC3B-II) in the presence of chloroquine. Therefore, SET overexpression in HEK293 cells promotes mitochondrial fission and reduces autophagic flux in apparent association with up-regulation of UCP2 and UCP3; this implies a potential involvement in cellular processes that are deregulated such as in Alzheimer's disease and cancer.

  15. A proposal for a set of Level 3 Basic Linear Algebra Subprograms

    Energy Technology Data Exchange (ETDEWEB)

    Dongarra, J.; Du Croz, J.; Duff, I.; Hammarling, S.

    1987-04-01

    This paper describes a proposal for Level 3 Basic Linear Algebra Subprograms (Level 3 BLAS). The Level 3 BLAS are targeted at matrix-matrix operations with the aim of providing more efficient, but portable, implementations of algorithms on high-performance computers, especially those with hierarchical memory and parallel processing capability.

  16. Automatic segmentation of human facial tissue by MRI-CT fusion: a feasibility study.

    Science.gov (United States)

    Kale, Emre H; Mumcuoglu, Erkan U; Hamcan, Salih

    2012-12-01

    The aim of this study was to develop automatic image segmentation methods to segment human facial tissue which contains very thin anatomic structures. The segmentation output can be used to construct a more realistic human face model for a variety of purposes like surgery planning, patient specific prosthesis design and facial expression simulation. Segmentation methods developed were based on Bayesian and Level Set frameworks, which were applied on three image types: magnetic resonance imaging (MRI), computerized tomography (CT) and fusion, in which case information from both modalities were utilized maximally for every tissue type. The results on human data indicated that fusion, thickness adaptive and postprocessing options provided the best muscle/fat segmentation scores in both Level Set and Bayesian methods. When the best Level Set and Bayesian methods were compared, scores of the latter were better. Number of algorithm parameters (to be trained) and computer run time measured were also in favour of the Bayesian method.

  17. Basis set limit geometries for ammonia at the SCF and MP2 levels of theory

    Science.gov (United States)

    Defrees, D. J.; Mclean, A. D.

    1984-01-01

    The controversy over the Hartree-Fock bond angle of NH3 is resolved and the convergence of the geometry for the molecule as the basis set is systematically improved with both SCF and correlated MP2 wave functions. The results of the geometrical optimizations, carried out in four stages with a series of uncontracted bases sets, are shown. The obtained structure for NH3 supports the results of Radom and Rodwell (1980) that the Hartree-Fock limit angle is significantly greater than was previously believed.

  18. Adjacent segment degeneration after single-level anterior cervical decompression and fusion: disc space distraction and its impact on clinical outcomes.

    Science.gov (United States)

    Li, Jia; Li, Yongqian; Kong, Fanlong; Zhang, Di; Zhang, Yingze; Shen, Yong

    2015-03-01

    The purpose of this study was to find whether excessive distraction of the disc space for cage insertion was a risk factor for adjacent segment degeneration (ASD) after anterior cervical decompression and fusion (ACDF). One hundred and sixteen consecutive patients who underwent ACDF for single-level cervical disc herniation between June 2006 and November 2008 were retrospectively reviewed. Preoperative, postoperative and final follow-up disc height (DH), sagittal segmental alignment (SSA), and sagittal alignment of the cervical spine (SACS) were measured and compared between the ASD group and non-ASD group. In 116 patients, ASD was radiographically proven in 28 (24.1%) patients. The clinical outcomes were significantly improved compared to the preoperative scores in both groups. However, the postoperative and final follow-up DH of the ASD group were significantly higher than in the non-ASD group (p<0.05). In addition, the postoperative DH was significantly correlated with the postoperative or final follow-up SSA (p<0.05). However, postoperative DH was not found to significantly correlate with postoperative or final follow-up SACS (p=0.072 and p=0.096, respectively). Multivariate analysis showed that postoperative DH was the most significant risk factor for ASD. The clinical outcomes of ACDF for single-level degenerative cervical disc disease were satisfactory. Postoperative DH (the distracted distance) had the greatest impact on the incidence of ASD. Excessive disc space distraction is a considerable risk factor for the development of radiographic ASD.

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

    Directory of Open Access Journals (Sweden)

    M. Danciu

    2013-04-01

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

  20. Implementation and evaluation of local-level priority setting for stroke.

    Science.gov (United States)

    Chappel, D; Bailey, J; Stacy, R; Rodgers, H; Thomson, R

    2001-01-01

    We aimed to develop and evaluate a prioritisation process to combine the evidence base with stakeholder involvement within a stroke programme for a Health Improvement Programme (HImP). Implementation involved: formation of a district stroke group (DSG); review of the evidence; survey of DSG members; survey of other key professionals; consensus within the DSG; consultation with local users of the service. Evaluation was through semi-structured interviews and documentary analysis. The process was accepted as appropriate and valuable by the majority of participants, and a district HImP implementation group allocated pound sterling 100 000 for stroke development as a result of this process. However, some felt that stroke itself had been an imposed, rather than an agreed, local priority. The priority setting process was not clear to all participants and change of personnel, particularly in the NHS trusts, led to some perceived lack of ownership. Professionals from secondary care participated, but later criticised the process when they felt that the priorities in the HImP could limit their ability to access money for other service developments. The user consultation days occurred too late to influence the 1999/2002 HImP. We have shown that it is possible to develop an approach that is broadly accepted by stakeholders and balance the evidence base with local ownership. The participation of stakeholders, clarity of procedures, local ownership and awareness of local politics are important in effective priority setting. The model developed will be of value in other settings.

  1. Fingerprint Segmentation

    OpenAIRE

    Jomaa, Diala

    2009-01-01

    In this thesis, a new algorithm has been proposed to segment the foreground of the fingerprint from the image under consideration. The algorithm uses three features, mean, variance and coherence. Based on these features, a rule system is built to help the algorithm to efficiently segment the image. In addition, the proposed algorithm combine split and merge with modified Otsu. Both enhancements techniques such as Gaussian filter and histogram equalization are applied to enhance and improve th...

  2. A Variational Framework for Joint Detection and Segmentation of Ovarian Cancer Metastases

    OpenAIRE

    Liu, Jianfei; Wang, Shijun; Linguraru, Marius George; Yao, Jianhua; Summers, Ronald M.

    2013-01-01

    Detection and segmentation of ovarian cancer metastases have great clinical impacts on women’s health. However, the random distribution and weak boundaries of metastases significantly complicate this task. This paper presents a variational framework that combines region competition based level set propagation and image matching flow computation to jointly detect and segment metastases. Image matching flow not only detects metastases, but also creates shape priors to reduce over-segmentation. ...

  3. Multi-level governance of climate change in Belgium. Modest subnational policies in a complex setting

    OpenAIRE

    Happaerts, Sander

    2013-01-01

    This paper analyzes subnational climate policies in Belgium as a crucial case of multi-level policy-making in Europe. In Belgian federalism, the subnational governments have a large autonomy to conduct their own climate policies, while the scope to act at the federal level is very limited. Moreover, the federal system had produced complex and ineffective coordination patterns, where the federal and the subnational governments each have the possibility to block agreements, e.g. on the intra-Be...

  4. A Semantic Connected Coherence Scheme for Efficient Image Segmentation

    Directory of Open Access Journals (Sweden)

    S.Pannirselvam

    2012-06-01

    Full Text Available Image processing is a comprehensively research topic with an elongated history. Segmenting an image is the most challenging and difficult task in image processing and analysis. The principal intricacy met in image segmentation is the ability of techniques to discover semantic objects efficiently from an image without any prior knowledge. One recent work presented connected coherence tree algorithm (CCTA for image segmentation (with no prior knowledge which discovered regions of semantic coherence based on neighbor coherence segmentation criteria. It deployed an adaptive spatial scale and a suitable intensity-difference scale to extract several sets of coherent neighboring pixels and maximize the probability of single image content and minimize complex backgrounds. However CCTA segmented images either consists of small, lengthy and slender objects or rigorously ruined by noise, irregular lighting, occlusion, poor illumination, and shadow.In this paper, we present a Cluster based Semantic Coherent Tree (CBSCT scheme for image segmentation. CBSCT’s initial work is on the semantic connected coherence criteria for the image segregation. Semantic coherent regions are clustered based on Bayesian nearest neighbor search of neighborhood pixels. The segmentation regions are extracted from the images based on the cluster object purity obtained through semantic coherent regions. The clustered image regions are post processed with non linear noise filters. Performance metrics used in the evaluation of CBSCT are semantic coherent pixel size, number of cluster objects, and purity levels of the cluster, segmented coherent region intensity threshold, and quality of segmented images in terms of image clarity with PSNR.

  5. Topography Image Segmentation Based on Improved Chan-Vese Model

    Institute of Scientific and Technical Information of China (English)

    ZHAO Min-rong; ZHANG Xi-wen; JIANG Juan-na

    2013-01-01

    Aiming to solve the inefficient segmentation in traditional C-V model for complex topography image and time-consuming process caused by the level set function solving with partial differential, an improved Chan-Vese model is presented in this paper. With the good performances of maintaining topological properties of the traditional level set method and avoiding the numerical so-lution of partial differential, the same segmentation results could be easily obtained. Thus, a stable foundation for rapid segmenta-tion-based on image reconstruction identification is established.

  6. Hydrological drivers of record-setting water level rise on Earth's largest lake system

    Science.gov (United States)

    Gronewold, A. D.; Bruxer, J.; Durnford, D.; Smith, J. P.; Clites, A. H.; Seglenieks, F.; Qian, S. S.; Hunter, T. S.; Fortin, V.

    2016-05-01

    Between January 2013 and December 2014, water levels on Lake Superior and Lake Michigan-Huron, the two largest lakes on Earth by surface area, rose at the highest rate ever recorded for a 2 year period beginning in January and ending in December of the following year. This historic event coincided with below-average air temperatures and extensive winter ice cover across the Great Lakes. It also brought an end to a 15 year period of persistently below-average water levels on Lakes Superior and Michigan-Huron that included several months of record-low water levels. To differentiate hydrological drivers behind the recent water level rise, we developed a Bayesian Markov chain Monte Carlo (MCMC) routine for inferring historical estimates of the major components of each lake's water budget. Our results indicate that, in 2013, the water level rise on Lake Superior was driven by increased spring runoff and over-lake precipitation. In 2014, reduced over-lake evaporation played a more significant role in Lake Superior's water level rise. The water level rise on Lake Michigan-Huron in 2013 was also due to above-average spring runoff and persistent over-lake precipitation, while in 2014, it was due to a rare combination of below-average evaporation, above-average runoff and precipitation, and very high inflow rates from Lake Superior through the St. Marys River. We expect, in future research, to apply our new framework across the other Laurentian Great Lakes, and to Earth's other large freshwater basins as well.

  7. The critical size is set at a single-cell level by growth rate to attain homeostasis and adaptation.

    Science.gov (United States)

    Ferrezuelo, Francisco; Colomina, Neus; Palmisano, Alida; Garí, Eloi; Gallego, Carme; Csikász-Nagy, Attila; Aldea, Martí

    2012-01-01

    Budding yeast cells are assumed to trigger Start and enter the cell cycle only after they attain a critical size set by external conditions. However, arguing against deterministic models of cell size control, cell volume at Start displays great individual variability even under constant conditions. Here we show that cell size at Start is robustly set at a single-cell level by the volume growth rate in G1, which explains the observed variability. We find that this growth-rate-dependent sizer is intimately hardwired into the Start network and the Ydj1 chaperone is key for setting cell size as a function of the individual growth rate. Mathematical modelling and experimental data indicate that a growth-rate-dependent sizer is sufficient to ensure size homeostasis and, as a remarkable advantage over a rigid sizer mechanism, it reduces noise in G1 length and provides an immediate solution for size adaptation to external conditions at a population level.

  8. Increased circulating Th17 cells and elevated serum levels of TGF-beta and IL-21 are correlated with human non-segmental vitiligo development.

    Science.gov (United States)

    Zhou, Li; Shi, Yu-Ling; Li, Kai; Hamzavi, Iltefat; Gao, Tian-Wen; Huggins, Richard H; Lim, Henry W; Mi, Qing-Sheng

    2015-05-01

    Although non-segmental vitiligo (NSV) results from the autoimmune destruction of melanocytes, the detailed immune mechanisms have not yet been fully elucidated. Th17 cells have been identified to be implicated in human autoimmune diseases. In this study, the frequencies of peripheral blood Th17 cells and serum levels of IL-17A and Th17 cell-related cytokines were examined in 45 patients with active NSV compared to 45 race-, gender-, and age-matched healthy controls. Our results showed increased circulating Th17 cell frequencies and elevated serum IL-17A, TGF-β1, and IL-21 levels in patients with NSV. Meanwhile, the increased Th17 cell frequencies are positively correlated with serum TGF-β1 level, and the body surface area of lesions is positively correlated with elevated TGF-β1 and IL-21 levels and Th17 cell frequencies. Furthermore, positive correlation was identified between Th17 and Th1 cell frequencies in patients with NSV. These results further indicate the potential involvement of Th17 cells and the collaborative contribution of Th17 and Th1 in NSV development, and suggest that the elevated serum TGF-β1 and IL-21 levels could contribute to enhanced Th17 cell differentiation in NSV.

  9. Prognostic impact of intensive statin therapy on N-terminal pro-BNP level in non-ST-segment elevation acute myocardial infarction patients.

    Science.gov (United States)

    Shehata, Mohamed; Samir, Ayman; Dardiri, May

    2017-08-15

    This study explored the impact of intensive daily dosing of atorvastatin on in-hospital N-terminal pro-B-type natriuretic peptide level, left ventricular systolic function and incidence of major adverse cardiac events in non-ST-segment elevation myocardial infarction patients. Several studies showed that early initiation of statin therapy in acute coronary syndrome patients has a favorable prognostic impact. Hundred statin naive patients were prospectively enrolled. Once eligible, patients were randomly assigned to receive either a moderate daily dose that is, 20 mg (Group A) or an intensified daily dose that is, 80 mg (Group B) of atorvastatin, in addition to an equally divided loading dose given 24 and 12 h before coronary angiography (80 mg each). N-terminal pro-B-type natriuretic peptide levels were recorded before and after coronary intervention. Collected data after 3 months included; N-terminal pro-B-type natriuretic peptide levels, left ventricle systolic function and major adverse cardiac events. Mean age of the study cohort was 55 ± 10 years, 68% being males. There was no significant difference between both groups concerning procedural data. Group B patients showed a significantly lower N-terminal pro-B-type natriuretic peptide levels at both sampling occasions, i.e., after coronary intervention and 3 months later (P pro BNP level and higher LVEF after 3 months. © 2017, Wiley Periodicals, Inc.

  10. Wave energy level and geographic setting correlate with Florida beach water quality.

    Science.gov (United States)

    Feng, Zhixuan; Reniers, Ad; Haus, Brian K; Solo-Gabriele, Helena M; Kelly, Elizabeth A

    2016-03-15

    Many recreational beaches suffer from elevated levels of microorganisms, resulting in beach advisories and closures due to lack of compliance with Environmental Protection Agency guidelines. We conducted the first statewide beach water quality assessment by analyzing decadal records of fecal indicator bacteria (enterococci and fecal coliform) levels at 262 Florida beaches. The objectives were to depict synoptic patterns of beach water quality exceedance along the entire Florida shoreline and to evaluate their relationships with wave condition and geographic location. Percent exceedances based on enterococci and fecal coliform were negatively correlated with both long-term mean wave energy and beach slope. Also, Gulf of Mexico beaches exceeded the thresholds significantly more than Atlantic Ocean ones, perhaps partially due to the lower wave energy. A possible linkage between wave energy level and water quality is beach sand, a pervasive nonpoint source that tends to harbor more bacteria in the low-wave-energy environment.

  11. County-Level Poverty Is Equally Associated with Unmet Health Care Needs in Rural and Urban Settings

    Science.gov (United States)

    Peterson, Lars E.; Litaker, David G.

    2010-01-01

    Context: Regional poverty is associated with reduced access to health care. Whether this relationship is equally strong in both rural and urban settings or is affected by the contextual and individual-level characteristics that distinguish these areas, is unclear. Purpose: Compare the association between regional poverty with self-reported unmet…

  12. Supporting Diverse Young Adolescents: Cooperative Grouping in Inclusive Middle-Level Settings

    Science.gov (United States)

    Miller, Nicole C.; McKissick, Bethany R.; Ivy, Jessica T.; Moser, Kelly

    2017-01-01

    The middle level classroom presents unique challenges to educators who strive to provide opportunities that acknowledge learner diversity in terms of social, cognitive, physical, and emotional development. This is confounded even further within inclusive middle-school classrooms where the responsibility to differentiate instruction is even more…

  13. Setting-up nurse-led pilot clinics for the management of non-communicable diseases at primary health care level in resource-limited settings of Africa

    Directory of Open Access Journals (Sweden)

    Jean-Claude Mbanya

    2009-10-01

    Full Text Available BACKGROUND: This article describes the setting-up process for nurse-led pilot clinics for the management of four chronic diseases: asthma, type 2 diabetes mellitus, epilepsy and hypertension at the primary health care level in urban and rural Cameroon. METHODS: The Biyem-Assi urban and the Bafut rural health districts in Cameroon served as settings for this study. International and local guidelines were identified and adapted to the country's; circumstances. Training and follow-up tools were developed and nurses trained by experienced physicians in the management of the four conditions. Basic diagnostic and follow-up materials were provided and relevant essential drugs made available. RESULTS: Forty six nurses attended six training courses. By the second year of activity, three and four clinics were operational in the urban and the rural areas respectively. By then, 925 patients had been registered in the clinics. This represented a 68.5% increase from the first year. While the rural clinics relied mainly on essential drugs for their prescriptions, a prescription pattern combining generic and proprietary drugs was observed in the urban clinics. CONCLUSION: In the quest for cost-effective health care for NCD in sub-Saharan Africa, rethinking health workforce and service delivery has relevance. Nurse-led clinics, algorithm driven service delivery stands as alternatives to overcome the shortage of trained physicians and other issues relating to access to care.

  14. Acute plasma biomarkers of T cell activation set-point levels and of disease progression in HIV-1 infection.

    Directory of Open Access Journals (Sweden)

    Anne-Sophie Liovat

    Full Text Available T cell activation levels, viral load and CD4(+ T cell counts at early stages of HIV-1 infection are predictive of the rate of progression towards AIDS. We evaluated whether the inflammatory profile during primary HIV-1 infection is predictive of the virological and immunological set-points and of disease progression. We quantified 28 plasma proteins during acute and post-acute HIV-1 infection in individuals with known disease progression profiles. Forty-six untreated patients, enrolled during primary HIV-1 infection, were categorized into rapid progressors, progressors and slow progressors according to their spontaneous progression profile over 42 months of follow-up. Already during primary infection, rapid progressors showed a higher number of increased plasma proteins than progressors or slow progressors. The plasma levels of TGF-β1 and IL-18 in primary HIV-1 infection were both positively associated with T cell activation level at set-point (6 months after acute infection and together able to predict 74% of the T cell activation variation at set-point. Plasma IP-10 was positively and negatively associated with, respectively, T cell activation and CD4(+ T cell counts at set-point and capable to predict 30% of the CD4(+ T cell count variation at set-point. Moreover, plasma IP-10 levels during primary infection were predictive of rapid progression. In primary infection, IP-10 was an even better predictor of rapid disease progression than viremia or CD4(+ T cell levels at this time point. The superior predictive capacity of IP-10 was confirmed in an independent group of 88 HIV-1 infected individuals. Altogether, this study shows that the inflammatory profile in primary HIV-1 infection is associated with T cell activation levels and CD4(+ T cell counts at set-point. Plasma IP-10 levels were of strong predictive value for rapid disease progression. The data suggest IP-10 being an earlier marker of disease progression than CD4(+ T cell counts or

  15. Assessment of the non-Gaussianity and non-linearity levels of simulated sEMG signals on stationary segments.

    Science.gov (United States)

    Messaoudi, Noureddine; Bekka, Raïs El'hadi; Ravier, Philippe; Harba, Rachid

    2017-02-01

    The purpose of this paper was to evaluate the effects of the longitudinal single differential (LSD), the longitudinal double differential (LDD) and the normal double differential (NDD) spatial filters, the electrode shape, the inter-electrode distance (IED) on non-Gaussianity and non-linearity levels of simulated surface EMG (sEMG) signals when the maximum voluntary contraction (MVC) varied from 10% to 100% by a step of 10%. The effects of recruitment range thresholds (RR), the firing rate (FR) strategy and the peak firing rate (PFR) of motor units were also considered. A cylindrical multilayer model of the volume conductor and a model of motor unit (MU) recruitment and firing rate were used to simulate sEMG signals in a pool of 120 MUs for 5s. Firstly, the stationarity of sEMG signals was tested by the runs, the reverse arrangements (RA) and the modified reverse arrangements (MRA) tests. Then the non-Gaussianity was characterised with bicoherence and kurtosis, and non-linearity levels was evaluated with linearity test. The kurtosis analysis showed that the sEMG signals detected by the LSD filter were the most Gaussian and those detected by the NDD filter were the least Gaussian. In addition, the sEMG signals detected by the LSD filter were the most linear. For a given filter, the sEMG signals detected by using rectangular electrodes were more Gaussian and more linear than that detected with circular electrodes. Moreover, the sEMG signals are less non-Gaussian and more linear with reverse onion-skin firing rate strategy than those with onion-skin strategy. The levels of sEMG signal Gaussianity and linearity increased with the increase of the IED, RR and PFR. Copyright © 2016 Elsevier Ltd. All rights reserved.

  16. PHISHING WEB IMAGE SEGMENTATION BASED ON IMPROVING SPECTRAL CLUSTERING

    Institute of Scientific and Technical Information of China (English)

    Li Yuancheng; Zhao Liujun; Jiao Runhai

    2011-01-01

    Abstract This paper proposes a novel phishing web image segmentation algorithm which based on improving spectral clustering.Firstly,we construct a set of points which are composed of spatial location pixels and gray levels from a given image.Secondly,the data is clustered in spectral space of the similar matrix of the set points,in order to avoid the drawbacks of K-means algorithm in the conventional spectral clustering method that is sensitive to initial clustering centroids and convergence to local optimal solution,we introduce the clone operator,Cauthy mutation to enlarge the scale of clustering centers,quantum-inspired evolutionary algorithm to find the global optimal clustering centroids.Compared with phishing web image segmentation based on K-means,experimental results show that the segmentation performance of our method gains much improvement.Moreover,our method can convergence to global optimal solution and is better in accuracy of phishing web segmentation.

  17. EU-CIS joint study project 2. Conceptual framework of intervention level setting

    Energy Technology Data Exchange (ETDEWEB)

    Hedemann Jensen, P. [Risoe National Laboratory, Roskilde (Denmark); Demin, V.F. [Russian Research Centre, Kurchatov Institute, Moscow (Russian Federation); Konstantinov, Y.O. [Research Institute of Radiation Hygiene, St. Petersburg (Russian Federation); Yatsalo, B.I. [Institute of Agricultural Radiology and Agroecology, Obninsk (Russian Federation)

    1994-01-01

    Long-term protective measures taken in the CIS following the Chernobyl accident included relocating people from the most contaminated areas as well as continuing the restrictions on using foodstuffs contaminated with {sup 137}Cs. The levels at which these countermeasures were introduced or still are being introduced for dose-saving purposes have been used to estimate avertable doses based on population distributions on both dose rate and surface contamination density of {sup 137}Cs in space and time. The averted and avertable doses have been quantified by parameters of these distributions and intervention levels for relocation and foodstuff restrictions. The countermeasure efficiencies in agricultural production and various protection strategies in the agrosphere in Russia have been investigated. In addition, methods for estimating avertable radiation risks as well as residual risk from continuing exposures in terms of age-dependent radiation risk factors have been suggested. The sensitivity of changing intervention levels expressed in terms of changes in costs and avertable collective doses have been explored. The application of the present methodology in the decision-making process following a nuclear accident is discussed. Suggestions are made for including the methodology in simple models to be used for aiding decision-making on introducing protective measures. (au) (12 tabs., 8 ills., 22 refs.).

  18. Gaining entry-level clinical competence outside of the acute care setting.

    Science.gov (United States)

    Lordly, Daphne; Taper, Janette

    2008-01-01

    Traditionally, an emphasis has been placed on dietetic interns' attainment of entry-level clinical competence in acute care facilities. The perceived risks and benefits of acquiring entry-level clinical competence within long-term and acute care clinical environments were examined. The study included a purposive sample of recent graduates and dietitians (n=14) involved in an integrated internship program. Study subjects participated in in-depth individual interviews. Data were thematically analyzed with the support of data management software QSR N6. Perceived risks and benefits were associated with receiving clinical training exclusively in either environment; risks in one area surfaced as benefits in the other. Themes that emerged included philosophy of care, approach to practice, working environment, depth and breadth of experience, relationships (both client and professional), practice outcomes, employment opportunities, and attitude. Entry-level clinical competence is achievable in both acute and long-term care environments; however, attention must be paid to identified risks. Interns who consider gaining clinical competence exclusively in one area can reduce risks and better position themselves for employment in either practice area by incorporating an affiliation in the other area into their internship program.

  19. B-Spline Active Contour with Handling of Topology Changes for Fast Video Segmentation

    Directory of Open Access Journals (Sweden)

    Frederic Precioso

    2002-06-01

    Full Text Available This paper deals with video segmentation for MPEG-4 and MPEG-7 applications. Region-based active contour is a powerful technique for segmentation. However most of these methods are implemented using level sets. Although level-set methods provide accurate segmentation, they suffer from large computational cost. We propose to use a regular B-spline parametric method to provide a fast and accurate segmentation. Our B-spline interpolation is based on a fixed number of points 2j depending on the level of the desired details. Through this spatial multiresolution approach, the computational cost of the segmentation is reduced. We introduce a length penalty. This results in improving both smoothness and accuracy. Then we show some experiments on real-video sequences.

  20. Quantifying the Industrial Facility-Level Emission Rate of Methane in Various Segments of the Natural Gas Industry

    Science.gov (United States)

    Herndon, S. C.; Roscioli, J. R.; Yacovitch, T. I.; Floerchinger, C. R.; Mitchell, A.; Tkacik, D. S.; Subramanian, R.; Robinson, A. L.; Martinez, D. M.; Vaughn, T. L.; Williams, L.; Zimmerle, D.; Marchese, A.

    2014-12-01

    Methane, the dominant component in natural gas, is a potent short-lived radiative forcer. Recent technological advances in the extraction of oil and gas have increased the production rate dramatically since early 2000. In the context of CO2 emissions per energy generated, natural gas promises a tantalizing thermodynamic advantage over coal and other hydrocarbons. Natural gas emissions to the atmosphere along the entire path from well to customer, however, can wipe out the radiative forcing advantage once they surpass a threshold fraction of distributed gas. Recent studies have been undertaken to assess the methane emissions at various types of facilities within different sectors of the oil and gas industry. The distribution of observed facility level emission rates along with other results and conclusions from those studies will be presented. The implications that these findings have on the emissions inventories from these sectors will be discussed.

  1. Oxidative stress elevated DNA damage and homocysteine level in normal pregnant women in a segment of Pakistani population.

    Science.gov (United States)

    Bukhari, Shazia A; Rajoka, Muhammad Ibrahim; Ibrahim, Z; Jalal, Fatima; Rana, Shahid Mahboob; Nagra, Saeed A

    2011-04-01

    Maternal oxidative stress during pregnancy may impair fetal growth and help in the development of diseases in adulthood. The aim of current study was to assess total oxidation status (TOS), related parameters and their relationship to DNA damage (%) and homocysteine level in normal pregnant women in low-income participants. In a cross-sectional study healthy women were grouped as normal, while age matched nulliparous and singleton pregnancies were included for first, second and third trimester groups. TOS (Phomocysteine (Ppregnant women were significantly higher as compared to normal healthy women. While serum total proteins (Phomocysteine (Phomocysteine with triglycerides (Ppregnant women. These changes were considered normal for pregnant women having optimum blood pressure and normal child birth. Hormonal influences and hemodilution may contribute towards the observed changes in this study.

  2. Implementing and measuring the level of laboratory service integration in a program setting in Nigeria.

    Directory of Open Access Journals (Sweden)

    Henry Mbah

    Full Text Available The surge of donor funds to fight HIV&AIDS epidemic inadvertently resulted in the setup of laboratories as parallel structures to rapidly respond to the identified need. However these parallel structures are a threat to the existing fragile laboratory systems. Laboratory service integration is critical to remedy this situation. This paper describes an approach to quantitatively measure and track integration of HIV-related laboratory services into the mainstream laboratory services and highlight some key intervention steps taken, to enhance service integration.A quantitative before-and-after study conducted in 122 Family Health International (FHI360 supported health facilities across Nigeria. A minimum service package was identified including management structure; trainings; equipment utilization and maintenance; information, commodity and quality management for laboratory integration. A check list was used to assess facilities at baseline and 3 months follow-up. Level of integration was assessed on an ordinal scale (0 = no integration, 1 = partial integration, 2 = full integration for each service package. A composite score grading expressed as a percentage of total obtainable score of 14 was defined and used to classify facilities (≤ 80% FULL, 25% to 79% PARTIAL and <25% NO integration. Weaknesses were noted and addressed.We analyzed 9 (7.4% primary, 104 (85.2% secondary and 9 (7.4% tertiary level facilities. There were statistically significant differences in integration levels between baseline and 3 months follow-up period (p<0.01. Baseline median total integration score was 4 (IQR 3 to 5 compared to 7 (IQR 4 to 9 at 3 months follow-up (p = 0.000. Partial and fully integrated laboratory systems were 64 (52.5% and 0 (0.0% at baseline, compared to 100 (82.0% and 3 (2.4% respectively at 3 months follow-up (p = 0.000.This project showcases our novel approach to measure the status of each laboratory on the integration continuum.

  3. Implementing and measuring the level of laboratory service integration in a program setting in Nigeria.

    Science.gov (United States)

    Mbah, Henry; Negedu-Momoh, Olubunmi Ruth; Adedokun, Oluwasanmi; Ikani, Patrick Anibbe; Balogun, Oluseyi; Sanwo, Olusola; Ochei, Kingsley; Ekanem, Maurice; Torpey, Kwasi

    2014-01-01

    The surge of donor funds to fight HIV&AIDS epidemic inadvertently resulted in the setup of laboratories as parallel structures to rapidly respond to the identified need. However these parallel structures are a threat to the existing fragile laboratory systems. Laboratory service integration is critical to remedy this situation. This paper describes an approach to quantitatively measure and track integration of HIV-related laboratory services into the mainstream laboratory services and highlight some key intervention steps taken, to enhance service integration. A quantitative before-and-after study conducted in 122 Family Health International (FHI360) supported health facilities across Nigeria. A minimum service package was identified including management structure; trainings; equipment utilization and maintenance; information, commodity and quality management for laboratory integration. A check list was used to assess facilities at baseline and 3 months follow-up. Level of integration was assessed on an ordinal scale (0 = no integration, 1 = partial integration, 2 = full integration) for each service package. A composite score grading expressed as a percentage of total obtainable score of 14 was defined and used to classify facilities (≤ 80% FULL, 25% to 79% PARTIAL and <25% NO integration). Weaknesses were noted and addressed. We analyzed 9 (7.4%) primary, 104 (85.2%) secondary and 9 (7.4%) tertiary level facilities. There were statistically significant differences in integration levels between baseline and 3 months follow-up period (p<0.01). Baseline median total integration score was 4 (IQR 3 to 5) compared to 7 (IQR 4 to 9) at 3 months follow-up (p = 0.000). Partial and fully integrated laboratory systems were 64 (52.5%) and 0 (0.0%) at baseline, compared to 100 (82.0%) and 3 (2.4%) respectively at 3 months follow-up (p = 0.000). This project showcases our novel approach to measure the status of each laboratory on the integration continuum.

  4. 4D MR phase and magnitude segmentations with GPU parallel computing.

    Science.gov (United States)

    Bergen, Robert V; Lin, Hung-Yu; Alexander, Murray E; Bidinosti, Christopher P

    2015-01-01

    The increasing size and number of data sets of large four dimensional (three spatial, one temporal) magnetic resonance (MR) cardiac images necessitates efficient segmentation algorithms. Analysis of phase-contrast MR images yields cardiac flow information which can be manipulated to produce accurate segmentations of the aorta. Phase contrast segmentation algorithms are proposed that use simple mean-based calculations and least mean squared curve fitting techniques. The initial segmentations are generated on a multi-threaded central processing unit (CPU) in 10 seconds or less, though the computational simplicity of the algorithms results in a loss of accuracy. A more complex graphics processing unit (GPU)-based algorithm fits flow data to Gaussian waveforms, and produces an initial segmentation in 0.5 seconds. Level sets are then applied to a magnitude image, where the initial conditions are given by the previous CPU and GPU algorithms. A comparison of results shows that the GPU algorithm appears to produce the most accurate segmentation.

  5. Required Levels of Catalysis for Emergence of Autocatalytic Sets in Models of Chemical Reaction Systems

    OpenAIRE

    2011-01-01

    The formation of a self-sustaining autocatalytic chemical network is a necessary but not sufficient condition for the origin of life. The question of whether such a network could form “by chance” within a sufficiently complex suite of molecules and reactions is one that we have investigated for a simple chemical reaction model based on polymer ligation and cleavage. In this paper, we extend this work in several further directions. In particular, we investigate in more detail the levels of cat...

  6. Segmentation and Tracking of Neural Stem Cell

    Institute of Scientific and Technical Information of China (English)

    TANG Chun-ming; ZHAO Chun-hui; Ewert Bengtsson

    2005-01-01

    In order to understand the development of stem cells into specialized mature cells it is necessary to study the growth of cells in culture. For this purpose it is very useful to have an efficient computerized cell tracking system. In this paper a prototype system for tracking neural stem cells in a sequence of images is described. In order to get reliable tracking results it is important to have good and robust segmentation of the cells. To achieve this we have implemented three levels of segmentation. The primary level, applied to all frames, is based on fuzzy threshold and watershed segmentation of a fuzzy gray weighted distance transformed image.The second level, applied to difficult frames where the first algorithm seems to have failed, is based on a fast geometric active contour model based on the level set algorithm. Finally, the automatic segmentation result on the crucial first frame can be interactively inspected and corrected. Visual inspection and correction can also be applied to other frames but this is generally not needed. For the tracking all cells are classified into inactive, active, dividing and clustered cells. Different algorithms are used to deal with the different cell categories. A special backtracking step is used to automatically correct for some common errors that appear in the initial forward tracking process.

  7. Land Surface Water Mapping Using Multi-Scale Level Sets and a Visual Saliency Model from SAR Images

    Directory of Open Access Journals (Sweden)

    Chuan Xu

    2016-05-01

    Full Text Available Land surface water mapping is one of the most basic classification tasks to distinguish water bodies from dry land surfaces. In this paper, a water mapping method was proposed based on multi-scale level sets and a visual saliency model (MLSVS, to overcome the lack of an operational solution for automatically, rapidly and reliably extracting water from large-area and fine spatial resolution Synthetic Aperture Radar (SAR images. This paper has two main contributions, as follows: (1 The method integrated the advantages of both level sets and the visual saliency model. First, the visual saliency map was applied to detect the suspected water regions (SWR, and then the level set method only needed to be applied to the SWR regions to accurately extract the water bodies, thereby yielding a simultaneous reduction in time cost and increase in accuracy; (2 In order to make the classical Itti model more suitable for extracting water in SAR imagery, an improved texture weighted with the Itti model (TW-Itti is employed to detect those suspected water regions, which take into account texture features generated by the Gray Level Co-occurrence Matrix (GLCM algorithm, Furthermore, a novel calculation method for center-surround differences was merged into this model. The proposed method was tested on both Radarsat-2 and TerraSAR-X images, and experiments demonstrated the effectiveness of the proposed method, the overall accuracy of water mapping is 98.48% and the Kappa coefficient is 0.856.

  8. RD50 value as the criterion for setting maximum admissible levels of occupational exposure to irritants in Poland.

    Science.gov (United States)

    Kupczewska-Dobecka, Małgorzata; Soćko, Renata; Czerczak, Sławomir

    2006-01-01

    The aim of this work is to analyse Maximum Admissible Concentration (MAC) values proposed for irritants by the Group of Experts for Chemical Agents in Poland, based on the RD50 value. In 1994-2004, MAC values for irritants based on the RD50 value were set for 17 chemicals. For the purpose of the analysis, 1/10 RD50, 1/100 RD50 and the MAC/RD50 ratio were calculated. The determined MAC values are within the 0.01-0.09 RD50 range. The RD50 value is a good rough criterion to set MAC values for irritants and it makes it possible to estimate quickly admissible exposure levels. It has become clear that, in some cases, simple setting the MAC value for an irritant at the level of 0.03 RD50 may be insufficient to determine precisely the possible hazard to workers' health. Other available toxicological data, such as NOAEL (No-Observed-Adverse-Effect Level) and LOAEL (Lowest-Observed-Adverse-Effect Level), should always be considered as well.

  9. Space-Time Unit-Level EBLUP for Large Data Sets

    Directory of Open Access Journals (Sweden)

    D’Aló Michele

    2017-03-01

    Full Text Available Most important large-scale surveys carried out by national statistical institutes are the repeated survey type, typically intended to produce estimates for several parameters of the whole population, as well as parameters related to some subpopulations. Small area estimation techniques are becoming more and more important for the production of official statistics where direct estimators are not able to produce reliable estimates. In order to exploit data from different survey cycles, unit-level linear mixed models with area and time random effects can be considered. However, the large amount of data to be processed may cause computational problems. To overcome the computational issues, a reformulation of predictors and the correspondent mean cross product estimator is given. The R code based on the new formulation enables the elaboration of about 7.2 millions of data records in a matter of minutes.

  10. Required levels of catalysis for emergence of autocatalytic sets in models of chemical reaction systems.

    Science.gov (United States)

    Hordijk, Wim; Kauffman, Stuart A; Steel, Mike

    2011-01-01

    The formation of a self-sustaining autocatalytic chemical network is a necessary but not sufficient condition for the origin of life. The question of whether such a network could form "by chance" within a sufficiently complex suite of molecules and reactions is one that we have investigated for a simple chemical reaction model based on polymer ligation and cleavage. In this paper, we extend this work in several further directions. In particular, we investigate in more detail the levels of catalysis required for a self-sustaining autocatalytic network to form. We study the size of chemical networks within which we might expect to find such an autocatalytic subset, and we extend the theoretical and computational analyses to models in which catalysis requires template matching.

  11. Required Levels of Catalysis for Emergence of Autocatalytic Sets in Models of Chemical Reaction Systems

    Directory of Open Access Journals (Sweden)

    Wim Hordijk

    2011-05-01

    Full Text Available The formation of a self-sustaining autocatalytic chemical network is a necessary but not sufficient condition for the origin of life. The question of whether such a network could form “by chance” within a sufficiently complex suite of molecules and reactions is one that we have investigated for a simple chemical reaction model based on polymer ligation and cleavage. In this paper, we extend this work in several further directions. In particular, we investigate in more detail the levels of catalysis required for a self-sustaining autocatalytic network to form. We study the size of chemical networks within which we might expect to find such an autocatalytic subset, and we extend the theoretical and computational analyses to models in which catalysis requires template matching.

  12. Mitochondrial diaphorases as NAD+ donors to segments of the citric acid cycle that support substrate-level phosphorylation yielding ATP during respiratory inhibition

    Science.gov (United States)

    Kiss, Gergely; Konrad, Csaba; Pour-Ghaz, Issa; Mansour, Josef J.; Németh, Beáta; Starkov, Anatoly A.; Adam-Vizi, Vera; Chinopoulos, Christos

    2014-01-01

    Substrate-level phosphorylation mediated by succinyl-CoA ligase in the mitochondrial matrix produces high-energy phosphates in the absence of oxidative phosphorylation. Furthermore, when the electron transport chain is dysfunctional, provision of succinyl-CoA by the α-ketoglutarate dehydrogenase complex (KGDHC) is crucial for maintaining the function of succinyl-CoA ligase yielding ATP, preventing the adenine nucleotide translocase from reversing. We addressed the source of the NAD+ supply for KGDHC under anoxic conditions and inhibition of complex I. Using pharmacologic tools and specific substrates and by examining tissues from pigeon liver exhibiting no diaphorase activity, we showed that mitochondrial diaphorases in the mouse liver contribute up to 81% to the NAD+ pool during respiratory inhibition. Under these conditions, KGDHC's function, essential for the provision of succinyl-CoA to succinyl-CoA ligase, is supported by NAD+ derived from diaphorases. Through this process, diaphorases contribute to the maintenance of substrate-level phosphorylation during respiratory inhibition, which is manifested in the forward operation of adenine nucleotide translocase. Finally, we show that reoxidation of the reducible substrates for the diaphorases is mediated by complex III of the respiratory chain.—Kiss, G., Konrad, C., Pour-Ghaz, I., Mansour, J. J., Németh, B., Starkov, A. A., Adam-Vizi, V., Chinopoulos, C. Mitochondrial diaphorases as NAD+ donors to segments of the citric acid cycle that support substrate-level phosphorylation yielding ATP during respiratory inhibition. PMID:24391134

  13. High Levels of Post-Abortion Complication in a Setting Where Abortion Service Is Not Legalized

    Science.gov (United States)

    Melese, Tadele; Habte, Dereje; Tsima, Billy M.; Mogobe, Keitshokile Dintle; Chabaesele, Kesegofetse; Rankgoane, Goabaone; Keakabetse, Tshiamo R.; Masweu, Mabole; Mokotedi, Mosidi; Motana, Mpho; Moreri-Ntshabele, Badani

    2017-01-01

    Background Maternal mortality due to abortion complications stands among the three leading causes of maternal death in Botswana where there is a restrictive abortion law. This study aimed at assessing the patterns and determinants of post-abortion complications. Methods A retrospective institution based cross-sectional study was conducted at four hospitals from January to August 2014. Data were extracted from patients’ records with regards to their socio-demographic variables, abortion complications and length of hospital stay. Descriptive statistics and bivariate analysis were employed. Result A total of 619 patients’ records were reviewed with a mean (SD) age of 27.12 (5.97) years. The majority of abortions (95.5%) were reported to be spontaneous and 3.9% of the abortions were induced by the patient. Two thirds of the patients were admitted as their first visit to the hospitals and one third were referrals from other health facilities. Two thirds of the patients were admitted as a result of incomplete abortion followed by inevitable abortion (16.8%). Offensive vaginal discharge (17.9%), tender uterus (11.3%), septic shock (3.9%) and pelvic peritonitis (2.4%) were among the physical findings recorded on admission. Clinically detectable anaemia evidenced by pallor was found to be the leading major complication in 193 (31.2%) of the cases followed by hypovolemic and septic shock 65 (10.5%). There were a total of 9 abortion related deaths with a case fatality rate of 1.5%. Self-induced abortion and delayed uterine evacuation of more than six hours were found to have significant association with post-abortion complications (p-values of 0.018 and 0.035 respectively). Conclusion Abortion related complications and deaths are high in our setting where abortion is illegal. Mechanisms need to be devised in the health facilities to evacuate the uterus in good time whenever it is indicated and to be equipped to handle the fatal complications. There is an indication for

  14. High Levels of Post-Abortion Complication in a Setting Where Abortion Service Is Not Legalized.

    Science.gov (United States)

    Melese, Tadele; Habte, Dereje; Tsima, Billy M; Mogobe, Keitshokile Dintle; Chabaesele, Kesegofetse; Rankgoane, Goabaone; Keakabetse, Tshiamo R; Masweu, Mabole; Mokotedi, Mosidi; Motana, Mpho; Moreri-Ntshabele, Badani

    2017-01-01

    Maternal mortality due to abortion complications stands among the three leading causes of maternal death in Botswana where there is a restrictive abortion law. This study aimed at assessing the patterns and determinants of post-abortion complications. A retrospective institution based cross-sectional study was conducted at four hospitals from January to August 2014. Data were extracted from patients' records with regards to their socio-demographic variables, abortion complications and length of hospital stay. Descriptive statistics and bivariate analysis were employed. A total of 619 patients' records were reviewed with a mean (SD) age of 27.12 (5.97) years. The majority of abortions (95.5%) were reported to be spontaneous and 3.9% of the abortions were induced by the patient. Two thirds of the patients were admitted as their first visit to the hospitals and one third were referrals from other health facilities. Two thirds of the patients were admitted as a result of incomplete abortion followed by inevitable abortion (16.8%). Offensive vaginal discharge (17.9%), tender uterus (11.3%), septic shock (3.9%) and pelvic peritonitis (2.4%) were among the physical findings recorded on admission. Clinically detectable anaemia evidenced by pallor was found to be the leading major complication in 193 (31.2%) of the cases followed by hypovolemic and septic shock 65 (10.5%). There were a total of 9 abortion related deaths with a case fatality rate of 1.5%. Self-induced abortion and delayed uterine evacuation of more than six hours were found to have significant association with post-abortion complications (p-values of 0.018 and 0.035 respectively). Abortion related complications and deaths are high in our setting where abortion is illegal. Mechanisms need to be devised in the health facilities to evacuate the uterus in good time whenever it is indicated and to be equipped to handle the fatal complications. There is an indication for clinical audit on post-abortion care to

  15. Gradient Augmented Level Set Method for Two Phase Flow Simulations with Phase Change

    Science.gov (United States)

    Anumolu, C. R. Lakshman; Trujillo, Mario F.

    2016-11-01

    A sharp interface capturing approach is presented for two-phase flow simulations with phase change. The Gradient Augmented Levelset method is coupled with the two-phase momentum and energy equations to advect the liquid-gas interface and predict heat transfer with phase change. The Ghost Fluid Method (GFM) is adopted for velocity to discretize the advection and diffusion terms in the interfacial region. Furthermore, the GFM is employed to treat the discontinuity in the stress tensor, velocity, and temperature gradient yielding an accurate treatment in handling jump conditions. Thermal convection and diffusion terms are approximated by explicitly identifying the interface location, resulting in a sharp treatment for the energy solution. This sharp treatment is extended to estimate the interfacial mass transfer rate. At the computational cell, a d-cubic Hermite interpolating polynomial is employed to describe the interface location, which is locally fourth-order accurate. This extent of subgrid level description provides an accurate methodology for treating various interfacial processes with a high degree of sharpness. The ability to predict the interface and temperature evolutions accurately is illustrated by comparing numerical results with existing 1D to 3D analytical solutions.

  16. Hydrogeologic setting east of a low-level radioactive-waste disposal site near Sheffield, Illinois

    Science.gov (United States)

    Foster, J.B.; Garklavs, George; Mackey, G.W.

    1984-01-01

    Core samples from 45 test wells and 4 borings were used to describe the glacial geology of the area east of the low-level radioactive-waste disposal site near Sheffield, Bureau County, Illinois. Previous work has shown that shallow ground water beneath the disposal site flows east through a pebbly-sand unit of the Toulon Member of the Glasford Formation. The pebbly sand was found in core samples from wells in an area extending northeast from the waste-disposal site to a strip-mine lake and east along the south side of the lake. Other stratigraphic units identified in the study area are correlated with units found on the disposal site. The pebbly-sand unit of the Toulon Member grades from a pebbly sand on site into a coarse gravel with sand and pebbles towards the lake. The Hulick Till Member, a key bed, underlies the Toulon Member throughout most of the study area. A narrow channel-like depression in the Hulick Till is filled with coarse gravelly sand of the Toulon Member. The filled depression extends eastward from near the northeast corner of the waste-disposal site to the strip-mine lake. (USGS)

  17. WriteSmoothing: Improving Lifetime of Non-volatile Caches Using Intra-set Wear-leveling

    Energy Technology Data Exchange (ETDEWEB)

    Mittal, Sparsh [ORNL; Vetter, Jeffrey S [ORNL; Li, Dong [ORNL

    2014-01-01

    Driven by the trends of increasing core-count and bandwidth-wall problem, the size of last level caches (LLCs) has greatly increased. Since SRAM consumes high leakage power, researchers have explored use of non-volatile memories (NVMs) for designing caches as they provide high density and consume low leakage power. However, since NVMs have low write-endurance and the existing cache management policies are write variation-unaware, effective wear-leveling techniques are required for achieving reasonable cache lifetimes using NVMs. We present WriteSmoothing, a technique for mitigating intra-set write variation in NVM caches. WriteSmoothing logically divides the cache-sets into multiple modules. For each module, WriteSmoothing collectively records number of writes in each way for any of the sets. It then periodically makes most frequently written ways in a module unavailable to shift the write-pressure to other ways in the sets of the module. Extensive simulation results have shown that on average, for single and dual-core system configurations, WriteSmoothing improves cache lifetime by 2.17X and 2.75X, respectively. Also, its implementation overhead is small and it works well for a wide range of algorithm and system parameters.

  18. A topology optimization method based on the level set method for the design of negative permeability dielectric metamaterials

    DEFF Research Database (Denmark)

    Otomori, Masaki; Yamada, Takayuki; Izui, Kazuhiro;

    2012-01-01

    are highly impractical from an engineering and manufacturing point of view. Therefore, a topology optimization method that can obtain clear optimized configurations is desirable. Here, a level set-based topology optimization method incorporating a fictitious interface energy is applied to a negative......This paper presents a level set-based topology optimization method for the design of negative permeability dielectric metamaterials. Metamaterials are artificial materials that display extraordinary physical properties that are unavailable with natural materials. The aim of the formulated...... optimization problem is to find optimized layouts of a dielectric material that achieve negative permeability. The presence of grayscale areas in the optimized configurations critically affects the performance of metamaterials, positively as well as negatively, but configurations that contain grayscale areas...

  19. Numerical simulation of mechanical deformation of semi-solid material using a level-set based finite element method

    Science.gov (United States)

    Sun, Zhidan; Bernacki, Marc; Logé, Roland; Gu, Guochao

    2017-09-01

    In this work, a level-set based finite element method was used to numerically evaluate the mechanical behavior in a small deformation range of semi-solid materials with different microstructure configurations. For this purpose, a finite element model of the semi-solid phase was built based on Voronoï diagram. Interfaces between the solid and the liquid phases were implicitly described by level-set functions coupled to an anisotropic meshing technique. The liquid phase was considered as a Newtonian fluid, whereas the behavior of the solid phase was described by a viscoplastic law. Simulations were performed to study the effect of different parameters such as solid phase fraction and solid bridging. Results show that the macroscopic mechanical behavior of semi-solid material strongly depends on the solid fraction and the local microstructure which play important roles in the formation of hot tearing. These results could provide valuable information for the processing of semi-solid materials.

  20. Full field modeling of dynamic recrystallization in a global level set framework, application to 304L stainless steel

    Directory of Open Access Journals (Sweden)

    Boulais-Sinou Romain

    2016-01-01

    Full Text Available A new full field numerical approach for the simulation of dynamic and post-dynamic recrystallization will be detailed. A level Set framework is employed to link a crystal plasticity finite element method with the modeling of recrystallization. Plasticity is calculated through the activation of slip systems and provides predictions for both SSDs and GNDs densities. These predictions control the activation and kinetics of recrystallization. All the developments are applied on 304L stainless steel.

  1. Performance of the Effective-characteristic-polynomial Pi2 Method for Diatomic Molecules: Basis-set Dependencies and Vibrational Levels

    OpenAIRE

    Homeier, H. H. H.; Neef, M. D.

    2000-01-01

    The performance of the recently introduced $\\Pi$2 method [1] is investigated for some diatomic molecules. For this end, ground state energies are calculated at the MP4 level for various basis sets of increasing size. With negligible extra effort, the $\\Pi$2, F4, and [2/2] estimators are obtained, together with information on the reliability of the basic perturbation series [1]. The results are compared to more expensive CCSD(T) results. Also, electronic energy hypersurfaces are calculated at ...

  2. Development of Image Segmentation Methods for Intracranial Aneurysms

    Directory of Open Access Journals (Sweden)

    Yuka Sen

    2013-01-01

    Full Text Available Though providing vital means for the visualization, diagnosis, and quantification of decision-making processes for the treatment of vascular pathologies, vascular segmentation remains a process that continues to be marred by numerous challenges. In this study, we validate eight aneurysms via the use of two existing segmentation methods; the Region Growing Threshold and Chan-Vese model. These methods were evaluated by comparison of the results obtained with a manual segmentation performed. Based upon this validation study, we propose a new Threshold-Based Level Set (TLS method in order to overcome the existing problems. With divergent methods of segmentation, we discovered that the volumes of the aneurysm models reached a maximum difference of 24%. The local artery anatomical shapes of the aneurysms were likewise found to significantly influence the results of these simulations. In contrast, however, the volume differences calculated via use of the TLS method remained at a relatively low figure, at only around 5%, thereby revealing the existence of inherent limitations in the application of cerebrovascular segmentation. The proposed TLS method holds the potential for utilisation in automatic aneurysm segmentation without the setting of a seed point or intensity threshold. This technique will further enable the segmentation of anatomically complex cerebrovascular shapes, thereby allowing for more accurate and efficient simulations of medical imagery.

  3. Individual and setting level predictors of the implementation of a skin cancer prevention program: a multilevel analysis

    Directory of Open Access Journals (Sweden)

    Brownson Ross C

    2010-05-01

    Full Text Available Abstract Background To achieve widespread cancer control, a better understanding is needed of the factors that contribute to successful implementation of effective skin cancer prevention interventions. This study assessed the relative contributions of individual- and setting-level characteristics to implementation of a widely disseminated skin cancer prevention program. Methods A multilevel analysis was conducted using data from the Pool Cool Diffusion Trial from 2004 and replicated with data from 2005. Implementation of Pool Cool by lifeguards was measured using a composite score (implementation variable, range 0 to 10 that assessed whether the lifeguard performed different components of the intervention. Predictors included lifeguard background characteristics, lifeguard sun protection-related attitudes and behaviors, pool characteristics, and enhanced (i.e., more technical assistance, tailored materials, and incentives are provided versus basic treatment group. Results The mean value of the implementation variable was 4 in both years (2004 and 2005; SD = 2 in 2004 and SD = 3 in 2005 indicating a moderate implementation for most lifeguards. Several individual-level (lifeguard characteristics and setting-level (pool characteristics and treatment group factors were found to be significantly associated with implementation of Pool Cool by lifeguards. All three lifeguard-level domains (lifeguard background characteristics, lifeguard sun protection-related attitudes and behaviors and six pool-level predictors (number of weekly pool visitors, intervention intensity, geographic latitude, pool location, sun safety and/or skin cancer prevention programs, and sun safety programs and policies were included in the final model. The most important predictors of implementation were the number of weekly pool visitors (inverse association and enhanced treatment group (positive association. That is, pools with fewer weekly visitors and pools in the enhanced

  4. Relationship between disseminated intravascular coagu-lation and levels of plasma thrombinogen segment 1+2,D-dimer, and thrombomodulin in patients with multiple injuries

    Institute of Scientific and Technical Information of China (English)

    ZHU Yu-jun; HUANG Xian-kai

    2009-01-01

    Objective: To explore the relationship between dis-seminated intravascular coagulation (DIC) and levels of plasma thrombinogen segment 1+2 (F1+2), D-dimer (D-D), and thrombomodulin (TM) in patients with severe multiple injuries.Methods: In this study, 66 patients (49 males and 17 females, aged 15-74 years, mean=38.4 years) with multiple injuries, who were admitted to our hospital within 24 hours after injury with no personal or family history of hematopathy or coagulopathy, were divided into a minor injury group (ISS≥16, n=45) according to the injury severity. The patients in the major injury group were divided into a subgroup complicated with DIC (DIC subgroup, n=12) and a subgroup compli-cated with no DIC (non-DIC subgroup, n=33). Ten healthy people (7 males and 3 females, aged 22-61 years, mean=36.5 years±9.0 years), who received somatoscopy and diagnosed as healthy, served as the control group. Venous blood samples were collected once in the control group and 1, 3 and 7 days after trauma in the injury groups. The F1+2 and TM concentrations were determined by enzyme linked immunosorbent assay (ELISA), and D-D concentrations were measured by automated latex enhanced immunoassay. Results: F1+2, D-D and TM levels were higher in the minor and major injury groups than in the control group.They were markedly higher in the major injury group than in the minor injury group. In the non-DIC subgroup, F1+2 levels declined gradually while D-D and TM levels declined continuously. In the DIC subgroup, F1+2 and D-D levels remained elevated while TM levels exhibited an early rise and subsequent decrease. Plasma F1+2, D-D and TM levels were higher in the DIC patients than in the non-DIC patients. Injury-induced increases in F1+2, D-D and TM plasma lev-els had significant positive correlation with each other at each time point.Conclusions: Besides being related to trauma severity, F1+2, D-D and TM levels correlate closely with the occur-rence of posttraumatic DIC. Therefore

  5. A volume-amending method to improve mass conservation of level set approach for incompressible two-phase flows

    Institute of Scientific and Technical Information of China (English)

    LI XiangYang; WANG YueFa; YU GengZhi; YANG Chao; MAO ZaiSha

    2008-01-01

    A volume-amending method is developed both to keep the level set function as an algebraic distance function and to preserve the bubble mass in a level set approach for incompressible two-phase flows with the significantly deformed free interface. After the traditional reinitialization procedure, a vol-ume-amending method is added for correcting the position of the interface according to mass loss/gain error until the mass error falls in the allowable range designated in advance. The level set approach with this volume-amending method incorporated has been validated by three test cases: the motion of a single axisymmetrical bubble or drop in liquid, the motion of a two-dimensional water drop falling through the air into a water pool, and the interactional motion of two buoyancy-driven three-dimensional deformable bubbles. The computational results with this volume-amending method in-corporated are in good agreement with the reported experimental data and the mass is well preserved in all cases.

  6. FRACTIONAL-STEP FINITE ELEMENT METHOD FOR CALCULATION OF 3-D FREE SURFACE PROBLEM USING LEVEL SET METHOD

    Institute of Scientific and Technical Information of China (English)

    ZHAO Lan-hao; LI Tong-chun; WANG Ling; HERREROS M. I.; PASTOR M.

    2006-01-01

    A two-step Taylor-Galerkin fractional-step finite element method, which is of second order accuracy in space and time, was proposed for the three-dimensional free surface problem. With this method, the intermediate velocity was explicitly obtained by neglecting pressure gradient term, and then the velocity was corrected by adding the effects of pressure once the pressure field had been obtained from the pressure Poisson equation. The level set approach was applied to track implicitly the free surface. In order to track the free surface, the transport equation of the level set function was solved at each time step and the level set function is reinitialized through iteration to maintain it as a distance function. The governing equations of the system were discretized by the two- step Taylor-Galerkin method, which is of high-order accuracy and easy to be used. The validity and reliability of this method in this article were proved by two numerical examples.

  7. A free energy-based surface tension force model for simulation of multiphase flows by level-set method

    Science.gov (United States)

    Yuan, H. Z.; Chen, Z.; Shu, C.; Wang, Y.; Niu, X. D.; Shu, S.

    2017-09-01

    In this paper, a free energy-based surface tension force (FESF) model is presented for accurately resolving the surface tension force in numerical simulation of multiphase flows by the level set method. By using the analytical form of order parameter along the normal direction to the interface in the phase-field method and the free energy principle, FESF model offers an explicit and analytical formulation for the surface tension force. The only variable in this formulation is the normal distance to the interface, which can be substituted by the distance function solved by the level set method. On one hand, as compared to conventional continuum surface force (CSF) model in the level set method, FESF model introduces no regularized delta function, due to which it suffers less from numerical diffusions and performs better in mass conservation. On the other hand, as compared to the phase field surface tension force (PFSF) model, the evaluation of surface tension force in FESF model is based on an analytical approach rather than numerical approximations of spatial derivatives. Therefore, better numerical stability and higher accuracy can be expected. Various numerical examples are tested to validate the robustness of the proposed FESF model. It turns out that FESF model performs better than CSF model and PFSF model in terms of accuracy, stability, convergence speed and mass conservation. It is also shown in numerical tests that FESF model can effectively simulate problems with high density/viscosity ratio, high Reynolds number and severe topological interfacial changes.

  8. A volume-amending method to improve mass conservation of level set approach for incompressible two-phase flows

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    A volume-amending method is developed both to keep the level set function as an algebraic distance function and to preserve the bubble mass in a level set approach for incompressible two-phase flows with the significantly deformed free interface. After the traditional reinitialization procedure, a vol-ume-amending method is added for correcting the position of the interface according to mass loss/gain error until the mass error falls in the allowable range designated in advance. The level set approach with this volume-amending method incorporated has been validated by three test cases: the motion of a single axisymmetrical bubble or drop in liquid, the motion of a two-dimensional water drop falling through the air into a water pool, and the interactional motion of two buoyancy-driven three- dimensional deformable bubbles. The computational results with this volume-amending method in-corporated are in good agreement with the reported experimental data and the mass is well preserved in all cases.

  9. Pulmonary Nodule Detection Model Based on SVM and CT Image Feature-Level Fusion with Rough Sets

    Science.gov (United States)

    Lu, Huiling; Zhang, Junjie; Shi, Hongbin

    2016-01-01

    In order to improve the detection accuracy of pulmonary nodules in CT image, considering two problems of pulmonary nodules detection model, including unreasonable feature structure and nontightness of feature representation, a pulmonary nodules detection algorithm is proposed based on SVM and CT image feature-level fusion with rough sets. Firstly, CT images of pulmonary nodule are analyzed, and 42-dimensional feature components are extracted, including six new 3-dimensional features proposed by this paper and others 2-dimensional and 3-dimensional features. Secondly, these features are reduced for five times with rough set based on feature-level fusion. Thirdly, a grid optimization model is used to optimize the kernel function of support vector machine (SVM), which is used as a classifier to identify pulmonary nodules. Finally, lung CT images of 70 patients with pulmonary nodules are collected as the original samples, which are used to verify the effectiveness and stability of the proposed model by four groups' comparative experiments. The experimental results show that the effectiveness and stability of the proposed model based on rough set feature-level fusion are improved in some degrees.

  10. An automatic cells detection and segmentation

    Science.gov (United States)

    Han, Ligong; Le, T. Hoang Ngan; Savvides, Marios

    2017-03-01

    This paper presents an end-to-end framework for automatically detecting and segmenting blood cells including normal red blood cells (RBCs), connected RBCs, abnormal RBCs (i.e. tear drop, burr cell, helmet, etc.) and white blood cells (WBCs). Our proposed system contains several components to solve different problems regarding RBCs and WBCs. We first design a novel blood cell color representation which is able to emphasize the RBCs and WBCs in separate channels. Template matching technique is then employed to individually detect RBCs and WBCs in our proposed representation. In order to automatically segment the RBCs and nuclei from WBCs, we develop an adaptive level set-based segmentation method which makes use of both local and global information. The detected and segmented RBCs, however, can be a single RBC, a connected RBC or an abnormal RBC. Therefore, we first separate and reconstruct RBCs from the connected RBCs by our suggested modified template matching. Shape matching by inner distance is later used to classify the abnormal RBCs from the normal RBCs. Our proposed method has been tested and evaluated on different images from ALL-IDB,10 WebPath,24 UPMC,23 Flicker datasets, and the one used by Mohamed et al.14 The precision and recall of RBCs detection are 98.43% and 94.99% respectively, whereas those of WBCs detection are 99.12% and 99.12%. The F-measure of our proposed WBCs segmentation gets up to 95.8%.

  11. Freehand 3D ultrasound breast tumor segmentation

    Science.gov (United States)

    Liu, Qi; Ge, Yinan; Ou, Yue; Cao, Biao

    2007-12-01

    It is very important for physicians to accurately determine breast tumor location, size and shape in ultrasound image. The precision of breast tumor volume quantification relies on the accurate segmentation of the images. Given the known location and orientation of the ultrasound probe, We propose using freehand three dimensional (3D) ultrasound to acquire original images of the breast tumor and the surrounding tissues in real-time, after preprocessing with anisotropic diffusion filtering, the segmentation operation is performed slice by slice based on the level set method in the image stack. For the segmentation on each slice, the user can adjust the parameters to fit the requirement in the specified image in order to get the satisfied result. By the quantification procedure, the user can know the tumor size varying in different images in the stack. Surface rendering and interpolation are used to reconstruct the 3D breast tumor image. And the breast volume is constructed by the segmented contours in the stack of images. After the segmentation, the volume of the breast tumor in the 3D image data can be obtained.

  12. Smart markers for watershed-based cell segmentation.

    Science.gov (United States)

    Koyuncu, Can Fahrettin; Arslan, Salim; Durmaz, Irem; Cetin-Atalay, Rengul; Gunduz-Demir, Cigdem

    2012-01-01

    Automated cell imaging systems facilitate fast and reliable analysis of biological events at the cellular level. In these systems, the first step is usually cell segmentation that greatly affects the success of the subsequent system steps. On the other hand, similar to other image segmentation problems, cell segmentation is an ill-posed problem that typically necessitates the use of domain-specific knowledge to obtain successful segmentations even by human subjects. The approaches that can incorporate this knowledge into their segmentation algorithms have potential to greatly improve segmentation results. In this work, we propose a new approach for the effective segmentation of live cells from phase contrast microscopy. This approach introduces a new set of "smart markers" for a marker-controlled watershed algorithm, for which the identification of its markers is critical. The proposed approach relies on using domain-specific knowledge, in the form of visual characteristics of the cells, to define the markers. We evaluate our approach on a total of 1,954 cells. The experimental results demonstrate that this approach, which uses the proposed definition of smart markers, is quite effective in identifying better markers compared to its counterparts. This will, in turn, be effective in improving the segmentation performance of a marker-controlled watershed algorithm.

  13. Smart markers for watershed-based cell segmentation.

    Directory of Open Access Journals (Sweden)

    Can Fahrettin Koyuncu

    Full Text Available Automated cell imaging systems facilitate fast and reliable analysis of biological events at the cellular level. In these systems, the first step is usually cell segmentation that greatly affects the success of the subsequent system steps. On the other hand, similar to other image segmentation problems, cell segmentation is an ill-posed problem that typically necessitates the use of domain-specific knowledge to obtain successful segmentations even by human subjects. The approaches that can incorporate this knowledge into their segmentation algorithms have potential to greatly improve segmentation results. In this work, we propose a new approach for the effective segmentation of live cells from phase contrast microscopy. This approach introduces a new set of "smart markers" for a marker-controlled watershed algorithm, for which the identification of its markers is critical. The proposed approach relies on using domain-specific knowledge, in the form of visual characteristics of the cells, to define the markers. We evaluate our approach on a total of 1,954 cells. The experimental results demonstrate that this approach, which uses the proposed definition of smart markers, is quite effective in identifying better markers compared to its counterparts. This will, in turn, be effective in improving the segmentation performance of a marker-controlled watershed algorithm.

  14. Levels of 8-OxodG Predict Hepatobiliary Pathology in Opisthorchis viverrini Endemic Settings in Thailand.

    Science.gov (United States)

    Saichua, Prasert; Yakovleva, Anna; Kamamia, Christine; Jariwala, Amar R; Sithithaworn, Jiraporn; Sripa, Banchob; Brindley, Paul J; Laha, Thewarach; Mairiang, Eimorn; Pairojkul, Chawalit; Khuntikeo, Narong; Mulvenna, Jason; Sithithaworn, Paiboon; Bethony, Jeffrey M

    2015-01-01

    Opisthorchis viverrini is distinct among helminth infections as it drives a chronic inflammatory response in the intrahepatic bile duct that progresses from advanced periductal fibrosis (APF) to cholangiocarcinoma (CCA). Extensive research shows that oxidative stress (OS) plays a critical role in the transition from chronic O. viverrini infection to CCA. OS also results in the excision of a modified DNA lesion (8-oxodG) into urine, the levels of which can be detected by immunoassay. Herein, we measured concentrations of urine 8-oxodG by immunoassay from the following four groups in the Khon Kaen Cancer Cohort study: (1) O. viverrini negative individuals, (2) O. viverrini positive individuals with no APF as determined by abdominal ultrasound, (3) O. viverrini positive individuals with APF as determined by abdominal ultrasound, and (4) O. viverrini induced cases of CCA. A logistic regression model was used to evaluate the utility of creatinine-adjusted urinary 8-oxodG among these groups, along with demographic, behavioral, and immunological risk factors. Receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive accuracy of urinary 8-oxodG for APF and CCA. Elevated concentrations of 8-oxodG in urine positively associated with APF and CCA in a strongly dose-dependent manner. Urinary 8-oxodG concentrations also accurately predicted whether an individual presented with APF or CCA compared to O. viverrini infected individuals without these pathologies. In conclusion, urinary 8-oxodG is a robust 'candidate' biomarker of the progression of APF and CCA from chronic opisthorchiasis, which is indicative of the critical role that OS plays in both of these advanced hepatobiliary pathologies. The findings also confirm our previous observations that severe liver pathology occurs early and asymptomatically in residents of O. viverrini endemic regions, where individuals are infected for years (often decades) with this food-borne pathogen. These

  15. Levels of 8-OxodG Predict Hepatobiliary Pathology in Opisthorchis viverrini Endemic Settings in Thailand.

    Directory of Open Access Journals (Sweden)

    Prasert Saichua

    Full Text Available Opisthorchis viverrini is distinct among helminth infections as it drives a chronic inflammatory response in the intrahepatic bile duct that progresses from advanced periductal fibrosis (APF to cholangiocarcinoma (CCA. Extensive research shows that oxidative stress (OS plays a critical role in the transition from chronic O. viverrini infection to CCA. OS also results in the excision of a modified DNA lesion (8-oxodG into urine, the levels of which can be detected by immunoassay. Herein, we measured concentrations of urine 8-oxodG by immunoassay from the following four groups in the Khon Kaen Cancer Cohort study: (1 O. viverrini negative individuals, (2 O. viverrini positive individuals with no APF as determined by abdominal ultrasound, (3 O. viverrini positive individuals with APF as determined by abdominal ultrasound, and (4 O. viverrini induced cases of CCA. A logistic regression model was used to evaluate the utility of creatinine-adjusted urinary 8-oxodG among these groups, along with demographic, behavioral, and immunological risk factors. Receiver operating characteristic (ROC curve analysis was used to evaluate the predictive accuracy of urinary 8-oxodG for APF and CCA. Elevated concentrations of 8-oxodG in urine positively associated with APF and CCA in a strongly dose-dependent manner. Urinary 8-oxodG concentrations also accurately predicted whether an individual presented with APF or CCA compared to O. viverrini infected individuals without these pathologies. In conclusion, urinary 8-oxodG is a robust 'candidate' biomarker of the progression of APF and CCA from chronic opisthorchiasis, which is indicative of the critical role that OS plays in both of these advanced hepatobiliary pathologies. The findings also confirm our previous observations that severe liver pathology occurs early and asymptomatically in residents of O. viverrini endemic regions, where individuals are infected for years (often decades with this food-borne pathogen

  16. Wavelet-based improved Chan-Vese model for image segmentation

    Science.gov (United States)

    Zhao, Xiaoli; Zhou, Pucheng; Xue, Mogen

    2016-10-01

    In this paper, a kind of image segmentation approach which based on improved Chan-Vese (CV) model and wavelet transform was proposed. Firstly, one-level wavelet decomposition was adopted to get the low frequency approximation image. And then, the improved CV model, which contains the global term, local term and the regularization term, was utilized to segment the low frequency approximation image, so as to obtain the coarse image segmentation result. Finally, the coarse segmentation result was interpolated into the fine scale as an initial contour, and the improved CV model was utilized again to get the fine scale segmentation result. Experimental results show that our method can segment low contrast images and/or inhomogeneous intensity images more effectively than traditional level set methods.

  17. Influence of nuclei segmentation on breast cancer malignancy classification

    Science.gov (United States)

    Jelen, Lukasz; Fevens, Thomas; Krzyzak, Adam

    2009-02-01

    Breast Cancer is one of the most deadly cancers affecting middle-aged women. Accurate diagnosis and prognosis are crucial to reduce the high death rate. Nowadays there are numerous diagnostic tools for breast cancer diagnosis. In this paper we discuss a role of nuclear segmentation from fine needle aspiration biopsy (FNA) slides and its influence on malignancy classification. Classification of malignancy plays a very important role during the diagnosis process of breast cancer. Out of all cancer diagnostic tools, FNA slides provide the most valuable information about the cancer malignancy grade which helps to choose an appropriate treatment. This process involves assessing numerous nuclear features and therefore precise segmentation of nuclei is very important. In this work we compare three powerful segmentation approaches and test their impact on the classification of breast cancer malignancy. The studied approaches involve level set segmentation, fuzzy c-means segmentation and textural segmentation based on co-occurrence matrix. Segmented nuclei were used to extract nuclear features for malignancy classification. For classification purposes four different classifiers were trained and tested with previously extracted features. The compared classifiers are Multilayer Perceptron (MLP), Self-Organizing Maps (SOM), Principal Component-based Neural Network (PCA) and Support Vector Machines (SVM). The presented results show that level set segmentation yields the best results over the three compared approaches and leads to a good feature extraction with a lowest average error rate of 6.51% over four different classifiers. The best performance was recorded for multilayer perceptron with an error rate of 3.07% using fuzzy c-means segmentation.

  18. A multi-scale approach to mass segmentation using active contour models

    Science.gov (United States)

    Yu, Hongwei; Li, Lihua; Xu, Weidong; Liu, Wei

    2010-03-01

    As an important step of mass classification, mass segmentation plays an important role in computer-aided diagnosis (CAD). In this paper, we propose a novel scheme for breast mass segmentation in mammograms, which is based on level set method and multi-scale analysis. Mammogram is firstly decomposed by Gaussian pyramid into a sequence of images from fine to coarse, the C-V model is then applied at the coarse scale, and the obtained rough contour is used as the initial contour for segmentation at the fine scale. A local active contour (LAC) model based on image local information is utilized to refine the rough contour locally at the fine scale. In addition, the feature of area and gray level extracted from coarse segmentation is used to set the parameters of LAC model automatically to improve the adaptivity of our method. The results show the higher accuracy and robustness of the proposed multi-scale segmentation method than the conventional ones.

  19. An ICA-based method for the segmentation of pigmented skin lesions in macroscopic images.

    Science.gov (United States)

    Cavalcanti, Pablo G; Scharcanski, Jacob; Di Persia, Leandro E; Milone, Diego H

    2011-01-01

    Segmentation is an important step in computer-aided diagnostic systems for pigmented skin lesions, since that a good definition of the lesion area and its boundary at the image is very important to distinguish benign from malignant cases. In this paper a new skin lesion segmentation method is proposed. This method uses Independent Component Analysis to locate skin lesions in the image, and this location information is further refined by a Level-set segmentation method. Our method was evaluated in 141 images and achieved an average segmentation error of 16.55%, lower than the results for comparable state-of-the-art methods proposed in literature.

  20. Low-Level Tragus Stimulation for the Treatment of Ischemia and Reperfusion Injury in Patients With ST-Segment Elevation Myocardial Infarction: A Proof-of-Concept Study.

    Science.gov (United States)

    Yu, Lilei; Huang, Bing; Po, Sunny S; Tan, Tuantuan; Wang, Menglong; Zhou, Liping; Meng, Guannan; Yuan, Shenxu; Zhou, Xiaoya; Li, Xuefei; Wang, Zhuo; Wang, Songyun; Jiang, Hong

    2017-08-14

    The aim of this study was to investigate whether low-level tragus stimulation (LL-TS) treatment could reduce myocardial ischemia-reperfusion injury in patients with ST-segment elevation myocardial infarction (STEMI). The authors' previous studies suggested that LL-TS could reduce the size of myocardial injury induced by ischemia. Patients who presented with STEMI within 12 h of symptom onset, treated with primary percutaneous coronary intervention, were randomized to the LL-TS group (n = 47) or the control group (with sham stimulation [n = 48]). LL-TS, 50% lower than the electric current that slowed the sinus rate, was delivered to the right tragus once the patients arrived in the catheterization room and lasted for 2 h after balloon dilatation (reperfusion). All patients were followed for 7 days. The occurrence of reperfusion-related arrhythmia, blood levels of creatine kinase-MB, myoglobin, N-terminal pro-B-type natriuretic peptide and inflammatory markers, and echocardiographic characteristics were evaluated. The incidence of reperfusion-related ventricular arrhythmia during the first 24 h was significantly attenuated by LL-TS. In addition, the area under the curve for creatine kinase-MB and myoglobin over 72 h was smaller in the LL-TS group than the control group. Furthermore, blood levels of inflammatory markers were decreased by LL-TS. Cardiac function, as demonstrated by the level of N-terminal pro-B-type natriuretic peptide, the left ventricular ejection fraction, and the wall motion index, was markedly improved by LL-TS. LL-TS reduces myocardial ischemia-reperfusion injury in patients with STEMI. This proof-of-concept study raises the possibility that this noninvasive strategy may be used to treat patients with STEMI undergoing primary percutaneous coronary intervention. Copyright © 2017. Published by Elsevier Inc.

  1. Segmented conjugated polymers

    Indian Academy of Sciences (India)

    G Padmanaban; S Ramakrishnan

    2003-08-01

    Segmented conjugated polymers, wherein the conjugation is randomly truncated by varying lengths of non-conjugated segments, form an interesting class of polymers as they not only represent systems of varying stiffness, but also ones where the backbone can be construed as being made up of chromophores of varying excitation energies. The latter feature, especially when the chromophores are fluorescent, like in MEHPPV, makes these systems particularly interesting from the photophysics point of view. Segmented MEHPPV- samples, where x represents the mole fraction of conjugated segments, were prepared by a novel approach that utilizes a suitable precursor wherein selective elimination of one of the two eliminatable groups is affected; the uneliminated units serve as conjugation truncations. Control of the composition x of the precursor therefore permits one to prepare segmented MEHPPV- samples with varying levels of conjugation (elimination). Using fluorescence spectroscopy, we have seen that even in single isolated polymer chains, energy migration from the shorter (higher energy) chromophores to longer (lower energy) ones occurs – the extent of which depends on the level of conjugation. Further, by varying the solvent composition, it is seen that the extent of energy transfer and the formation of poorly emissive inter-chromophore excitons are greatly enhanced with increasing amounts of non-solvent. A typical S-shaped curve represents the variation of emission yields as a function of composition suggestive of a cooperative collapse of the polymer coil, reminiscent of conformational transitions seen in biological macromolecules.

  2. Segment Level Based Heuristic for Workflow Cost-time Optimization in Grids%基于启发式分段的网格工作流费用优化方法

    Institute of Scientific and Technical Information of China (English)

    龙浩; 邸瑞华; 梁毅

    2011-01-01

    针对有向无环图(directed acrylic graph,DAG)表示的截止期约束下的网格工作流费用优化问题,提出启发式分段(segment level,SL)费用优化算法.通过分析DAG图中活动的并行和同步特征,算法对活动进行分段,时间浮差按比例分配到各段,段内的费用优化采用动态规划的求解策略实现.通过将工作流截止期转换为段截止时间,扩大了活动的费用优化区间,通过大量模拟实验将SL算法和MCP(minimum critcal path)、DTL (deadline top level)、DBL(deadline bottom level)算法比较,证明了SL算法的有效性.%Workflow scheduling with the objective of time-cost optimization is a fundamental problem in grids and generally the problem is NP-hard. In this paper, a novel heuristics called SL (Segment Level ) for workflows represented by DAG (Directed Acyclic Graph ) is proposed. Considering the parallel and synchronization properties, the workflow application is divided into segments, and the workflow deadline is transformed into the time intervals and appointed to different segments. The floating time is prorated to each segment to enlarge costtime duration, and a dynamic programming method is implemented to optimize cost for each segment. By comparing SL with MCP (Minimum Critical Path), DTL(Deadline Top Level), DBL(Deadline Bottom Level), the heuristics' efficiency is verified by experimental results.

  3. [Segmental neurofibromatosis].

    Science.gov (United States)

    Zulaica, A; Peteiro, C; Pereiro, M; Pereiro Ferreiros, M; Quintas, C; Toribio, J

    1989-01-01

    Four cases of segmental neurofibromatosis (SNF) are reported. It is a rare entity considered to be a localized variant of neurofibromatosis (NF)-Riccardi's type V. Two cases are male and two female. The lesions are located to the head in a patient and the other three cases in the trunk. No family history nor transmission to progeny were manifested. The rest of the organs are undamaged.

  4. Accurate segmentation of dense nanoparticles by partially discrete electron tomography

    Energy Technology Data Exchange (ETDEWEB)

    Roelandts, T., E-mail: tom.roelandts@ua.ac.be [IBBT-Vision Lab University of Antwerp, Universiteitsplein 1, 2610 Wilrijk (Belgium); Batenburg, K.J. [IBBT-Vision Lab University of Antwerp, Universiteitsplein 1, 2610 Wilrijk (Belgium); Centrum Wiskunde and Informatica, Science Park 123, 1098 XG Amsterdam (Netherlands); Biermans, E. [EMAT, University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp (Belgium); Kuebel, C. [Institute of Nanotechnology, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen (Germany); Bals, S. [EMAT, University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp (Belgium); Sijbers, J. [IBBT-Vision Lab University of Antwerp, Universiteitsplein 1, 2610 Wilrijk (Belgium)

    2012-03-15

    Accurate segmentation of nanoparticles within various matrix materials is a difficult problem in electron tomography. Due to artifacts related to image series acquisition and reconstruction, global thresholding of reconstructions computed by established algorithms, such as weighted backprojection or SIRT, may result in unreliable and subjective segmentations. In this paper, we introduce the Partially Discrete Algebraic Reconstruction Technique (PDART) for computing accurate segmentations of dense nanoparticles of constant composition. The particles are segmented directly by the reconstruction algorithm, while the surrounding regions are reconstructed using continuously varying gray levels. As no properties are assumed for the other compositions of the sample, the technique can be applied to any sample where dense nanoparticles must be segmented, regardless of the surrounding compositions. For both experimental and simulated data, it is shown that PDART yields significantly more accurate segmentations than those obtained by optimal global thresholding of the SIRT reconstruction. -- Highlights: Black-Right-Pointing-Pointer We present a novel reconstruction method for partially discrete electron tomography. Black-Right-Pointing-Pointer It accurately segments dense nanoparticles directly during reconstruction. Black-Right-Pointing-Pointer The gray level to use for the nanoparticles is determined objectively. Black-Right-Pointing-Pointer The method expands the set of samples for which discrete tomography can be applied.

  5. Intervening at the Setting Level to Prevent Behavioral Incidents in Residential Child Care: Efficacy of the CARE Program Model.

    Science.gov (United States)

    Izzo, Charles V; Smith, Elliott G; Holden, Martha J; Norton, Catherine I; Nunno, Michael A; Sellers, Deborah E

    2016-07-01

    The current study examined the impact of a setting-level intervention on the prevention of aggressive or dangerous behavioral incidents involving youth living in group care environments. Eleven group care agencies implemented Children and Residential Experiences (CARE), a principle-based program that helps agencies use a set of evidence-informed principles to guide programming and enrich the relational dynamics throughout the agency. All agencies served mostly youth referred from child welfare. The 3-year implementation of CARE involved intensive agency-wide training and on-site consultation to agency leaders and managers around supporting and facilitating day-to-day application of the principles in both childcare and staff management arenas. Agencies provided data over 48 months on the monthly frequency of behavioral incidents most related to program objectives. Using multiple baseline interrupted time series analysis to assess program effects, we tested whether trends during the program implementation period declined significantly compared to the 12 months before implementation. Results showed significant program effects on incidents involving youth aggression toward adult staff, property destruction, and running away. Effects on aggression toward peers and self-harm were also found but were less consistent. Staff ratings of positive organizational social context (OSC) predicted fewer incidents, but there was no clear relationship between OSC and observed program effects. Findings support the potential efficacy of the CARE model and illustrate that intervening "upstream" at the setting level may help to prevent coercive caregiving patterns and increase opportunities for healthy social interactions.

  6. Investigation of indoor air volatile organic compounds concentration levels in dental settings and some related methodological issues.

    Science.gov (United States)

    Santarsiero, Anna; Fuselli, Sergio; Piermattei, Alessandro; Morlino, Roberta; De Blasio, Giorgia; De Felice, Marco; Ortolani, Emanuela

    2009-01-01

    The assessment of indoor air volatile organic compounds (VOCs) concentration levels in dental settings has a big health relevance for the potentially massive occupational exposure to a lot of diverse contaminants. The comparison of the VOCs profile relative to indoor conditions and to the corresponding outdoor concentrations, as well as the discovery of possible correlations between specific dental activities and VOCs concentration variations are of utmost importance for offering a reliable characterization of risk for dentists and dental staff health. In this study we review the most relevant environmental studies addressing the VOCs contamination level in dental settings. We analyze the methodological problems this kind of study must face and we report preliminary results of an indoor air investigation, carried out at dental hospital in Italy, the "Ospedale odontoiatrico George Eastman" of Rome, in which general lines for the analysis of dental settings in environmental terms are sketched. The aim of this work is to identify the kind of problems a typical enclosed (non-industrial) environment indoor air investigation has to cope with by means of the analysis of a case study.

  7. Bud development, flowering and fruit set of Moringa oleifera Lam. (Horseradish Tree as affected by various irrigation levels

    Directory of Open Access Journals (Sweden)

    Quintin Ernst Muhl

    2013-12-01

    Full Text Available Moringa oleifera is becoming increasingly popular as an industrial crop due to its multitude of useful attributes as water purifier, nutritional supplement and biofuel feedstock. Given its tolerance to sub-optimal growing conditions, most of the current and anticipated cultivation areas are in medium to low rainfall areas. This study aimed to assess the effect of various irrigation levels on floral initiation, flowering and fruit set. Three treatments namely, a 900 mm (900IT, 600 mm (600IT and 300 mm (300IT per annum irrigation treatment were administered through drip irrigation, simulating three total annual rainfall amounts. Individual inflorescences from each treatment were tagged during floral initiation and monitored throughout until fruit set. Flower bud initiation was highest at the 300IT and lowest at the 900IT for two consecuti