WorldWideScience

Sample records for level set segmentation

  1. A level set method for multiple sclerosis lesion segmentation.

    Science.gov (United States)

    Zhao, Yue; Guo, Shuxu; Luo, Min; Shi, Xue; Bilello, Michel; Zhang, Shaoxiang; Li, Chunming

    2018-06-01

    In this paper, we present a level set method for multiple sclerosis (MS) lesion segmentation from FLAIR images in the presence of intensity inhomogeneities. We use a three-phase level set formulation of segmentation and bias field estimation to segment MS lesions and normal tissue region (including GM and WM) and CSF and the background from FLAIR images. To save computational load, we derive a two-phase formulation from the original multi-phase level set formulation to segment the MS lesions and normal tissue regions. The derived method inherits the desirable ability to precisely locate object boundaries of the original level set method, which simultaneously performs segmentation and estimation of the bias field to deal with intensity inhomogeneity. Experimental results demonstrate the advantages of our method over other state-of-the-art methods in terms of segmentation accuracy. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. A deep level set method for image segmentation

    OpenAIRE

    Tang, Min; Valipour, Sepehr; Zhang, Zichen Vincent; Cobzas, Dana; MartinJagersand

    2017-01-01

    This paper proposes a novel image segmentation approachthat integrates fully convolutional networks (FCNs) with a level setmodel. Compared with a FCN, the integrated method can incorporatesmoothing and prior information to achieve an accurate segmentation.Furthermore, different than using the level set model as a post-processingtool, we integrate it into the training phase to fine-tune the FCN. Thisallows the use of unlabeled data during training in a semi-supervisedsetting. Using two types o...

  3. 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.

  4. A new level set model for cell image segmentation

    International Nuclear Information System (INIS)

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

    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. (cross-disciplinary physics and related areas of science and technology)

  5. Level set method for image segmentation based on moment competition

    Science.gov (United States)

    Min, Hai; Wang, Xiao-Feng; Huang, De-Shuang; Jin, Jing; Wang, Hong-Zhi; Li, Hai

    2015-05-01

    We propose a level set method for image segmentation which introduces the moment competition and weakly supervised information into the energy functional construction. Different from the region-based level set methods which use force competition, the moment competition is adopted to drive the contour evolution. Here, a so-called three-point labeling scheme is proposed to manually label three independent points (weakly supervised information) on the image. Then the intensity differences between the three points and the unlabeled pixels are used to construct the force arms for each image pixel. The corresponding force is generated from the global statistical information of a region-based method and weighted by the force arm. As a result, the moment can be constructed and incorporated into the energy functional to drive the evolving contour to approach the object boundary. In our method, the force arm can take full advantage of the three-point labeling scheme to constrain the moment competition. Additionally, the global statistical information and weakly supervised information are successfully integrated, which makes the proposed method more robust than traditional methods for initial contour placement and parameter setting. Experimental results with performance analysis also show the superiority of the proposed method on segmenting different types of complicated images, such as noisy images, three-phase images, images with intensity inhomogeneity, and texture images.

  6. 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...

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

    DEFF Research Database (Denmark)

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

    . 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....

  8. 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

    to evaluate level set surfaces that are $C^2$ continuous, but are slow due to high computational burden. In this paper, we provide a higher order GPU based solver for fast and efficient segmentation of large volumetric images. We also extend the higher order method to multi-domain segmentation. Our streaming...

  9. Reconstruction of incomplete cell paths through a 3D-2D level set segmentation

    Science.gov (United States)

    Hariri, Maia; Wan, Justin W. L.

    2012-02-01

    Segmentation of fluorescent cell images has been a popular technique for tracking live cells. One challenge of segmenting cells from fluorescence microscopy is that cells in fluorescent images frequently disappear. When the images are stacked together to form a 3D image volume, the disappearance of the cells leads to broken cell paths. In this paper, we present a segmentation method that can reconstruct incomplete cell paths. The key idea of this model is to perform 2D segmentation in a 3D framework. The 2D segmentation captures the cells that appear in the image slices while the 3D segmentation connects the broken cell paths. The formulation is similar to the Chan-Vese level set segmentation which detects edges by comparing the intensity value at each voxel with the mean intensity values inside and outside of the level set surface. Our model, however, performs the comparison on each 2D slice with the means calculated by the 2D projected contour. The resulting effect is to segment the cells on each image slice. Unlike segmentation on each image frame individually, these 2D contours together form the 3D level set function. By enforcing minimum mean curvature on the level set surface, our segmentation model is able to extend the cell contours right before (and after) the cell disappears (and reappears) into the gaps, eventually connecting the broken paths. We will present segmentation results of C2C12 cells in fluorescent images to illustrate the effectiveness of our model qualitatively and quantitatively by different numerical examples.

  10. Image-guided regularization level set evolution for MR image segmentation and bias field correction.

    Science.gov (United States)

    Wang, Lingfeng; Pan, Chunhong

    2014-01-01

    Magnetic resonance (MR) image segmentation is a crucial step in surgical and treatment planning. In this paper, we propose a level-set-based segmentation method for MR images with intensity inhomogeneous problem. To tackle the initialization sensitivity problem, we propose a new image-guided regularization to restrict the level set function. The maximum a posteriori inference is adopted to unify segmentation and bias field correction within a single framework. Under this framework, both the contour prior and the bias field prior are fully used. As a result, the image intensity inhomogeneity can be well solved. Extensive experiments are provided to evaluate the proposed method, showing significant improvements in both segmentation and bias field correction accuracies as compared with other state-of-the-art approaches. Copyright © 2014 Elsevier Inc. All rights reserved.

  11. Automatic segmentation of Leishmania parasite in microscopic images using a modified CV level set method

    Science.gov (United States)

    Farahi, Maria; Rabbani, Hossein; Talebi, Ardeshir; Sarrafzadeh, Omid; Ensafi, Shahab

    2015-12-01

    Visceral Leishmaniasis is a parasitic disease that affects liver, spleen and bone marrow. According to World Health Organization report, definitive diagnosis is possible just by direct observation of the Leishman body in the microscopic image taken from bone marrow samples. We utilize morphological and CV level set method to segment Leishman bodies in digital color microscopic images captured from bone marrow samples. Linear contrast stretching method is used for image enhancement and morphological method is applied to determine the parasite regions and wipe up unwanted objects. Modified global and local CV level set methods are proposed for segmentation and a shape based stopping factor is used to hasten the algorithm. Manual segmentation is considered as ground truth to evaluate the proposed method. This method is tested on 28 samples and achieved 10.90% mean of segmentation error for global model and 9.76% for local model.

  12. 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.

  13. 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.

  14. Joint level-set and spatio-temporal motion detection for cell segmentation.

    Science.gov (United States)

    Boukari, Fatima; Makrogiannis, Sokratis

    2016-08-10

    Cell segmentation is a critical step for quantification and monitoring of cell cycle progression, cell migration, and growth control to investigate cellular immune response, embryonic development, tumorigenesis, and drug effects on live cells in time-lapse microscopy images. In this study, we propose a joint spatio-temporal diffusion and region-based level-set optimization approach for moving cell segmentation. Moving regions are initially detected in each set of three consecutive sequence images by numerically solving a system of coupled spatio-temporal partial differential equations. In order to standardize intensities of each frame, we apply a histogram transformation approach to match the pixel intensities of each processed frame with an intensity distribution model learned from all frames of the sequence during the training stage. After the spatio-temporal diffusion stage is completed, we compute the edge map by nonparametric density estimation using Parzen kernels. This process is followed by watershed-based segmentation and moving cell detection. We use this result as an initial level-set function to evolve the cell boundaries, refine the delineation, and optimize the final segmentation result. We applied this method to several datasets of fluorescence microscopy images with varying levels of difficulty with respect to cell density, resolution, contrast, and signal-to-noise ratio. We compared the results with those produced by Chan and Vese segmentation, a temporally linked level-set technique, and nonlinear diffusion-based segmentation. We validated all segmentation techniques against reference masks provided by the international Cell Tracking Challenge consortium. The proposed approach delineated cells with an average Dice similarity coefficient of 89 % over a variety of simulated and real fluorescent image sequences. It yielded average improvements of 11 % in segmentation accuracy compared to both strictly spatial and temporally linked Chan

  15. A Variational Level Set Approach Based on Local Entropy for Image Segmentation and Bias Field Correction.

    Science.gov (United States)

    Tang, Jian; Jiang, Xiaoliang

    2017-01-01

    Image segmentation has always been a considerable challenge in image analysis and understanding due to the intensity inhomogeneity, which is also commonly known as bias field. In this paper, we present a novel region-based approach based on local entropy for segmenting images and estimating the bias field simultaneously. Firstly, a local Gaussian distribution fitting (LGDF) energy function is defined as a weighted energy integral, where the weight is local entropy derived from a grey level distribution of local image. The means of this objective function have a multiplicative factor that estimates the bias field in the transformed domain. Then, the bias field prior is fully used. Therefore, our model can estimate the bias field more accurately. Finally, minimization of this energy function with a level set regularization term, image segmentation, and bias field estimation can be achieved. Experiments on images of various modalities demonstrated the superior performance of the proposed method when compared with other state-of-the-art approaches.

  16. 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.

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

    International Nuclear Information System (INIS)

    Hosntalab, Mohammad; Aghaeizadeh Zoroofi, Reza; Abbaspour Tehrani-Fard, Ali; Shirani, Gholamreza

    2008-01-01

    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.)

  18. 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.)

  19. 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

  20. [Cardiac Synchronization Function Estimation Based on ASM Level Set Segmentation Method].

    Science.gov (United States)

    Zhang, Yaonan; Gao, Yuan; Tang, Liang; He, Ying; Zhang, Huie

    At present, there is no accurate and quantitative methods for the determination of cardiac mechanical synchronism, and quantitative determination of the synchronization function of the four cardiac cavities with medical images has a great clinical value. This paper uses the whole heart ultrasound image sequence, and segments the left & right atriums and left & right ventricles of each frame. After the segmentation, the number of pixels in each cavity and in each frame is recorded, and the areas of the four cavities of the image sequence are therefore obtained. The area change curves of the four cavities are further extracted, and the synchronous information of the four cavities is obtained. Because of the low SNR of Ultrasound images, the boundary lines of cardiac cavities are vague, so the extraction of cardiac contours is still a challenging problem. Therefore, the ASM model information is added to the traditional level set method to force the curve evolution process. According to the experimental results, the improved method improves the accuracy of the segmentation. Furthermore, based on the ventricular segmentation, the right and left ventricular systolic functions are evaluated, mainly according to the area changes. The synchronization of the four cavities of the heart is estimated based on the area changes and the volume changes.

  1. 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

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

    International Nuclear Information System (INIS)

    Gan, Yangzhou; Zhao, Qunfei; Xia, Zeyang; Hu, Ying; Xiong, Jing; Zhang, Jianwei

    2015-01-01

    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 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 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 3 , 91.57 ± 0.82%, 0.27 ± 0.02 mm, 0.28 ± 0.03 mm

  3. 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.

  4. Characterization of mammographic masses based on level set segmentation with new image features and patient information

    International Nuclear Information System (INIS)

    Shi Jiazheng; Sahiner, Berkman; Chan Heangping; Ge Jun; Hadjiiski, Lubomir; Helvie, Mark A.; Nees, Alexis; Wu Yita; Wei Jun; Zhou Chuan; Zhang Yiheng; Cui Jing

    2008-01-01

    Computer-aided diagnosis (CAD) for characterization of mammographic masses as malignant or benign has the potential to assist radiologists in reducing the biopsy rate without increasing false negatives. The purpose of this study was to develop an automated method for mammographic mass segmentation and explore new image based features in combination with patient information in order to improve the performance of mass characterization. The authors' previous CAD system, which used the active contour segmentation, and morphological, textural, and spiculation features, has achieved promising results in mass characterization. The new CAD system is based on the level set method and includes two new types of image features related to the presence of microcalcifications with the mass and abruptness of the mass margin, and patient age. A linear discriminant analysis (LDA) classifier with stepwise feature selection was used to merge the extracted features into a classification score. The classification accuracy was evaluated using the area under the receiver operating characteristic curve. The authors' primary data set consisted of 427 biopsy-proven masses (200 malignant and 227 benign) in 909 regions of interest (ROIs) (451 malignant and 458 benign) from multiple mammographic views. Leave-one-case-out resampling was used for training and testing. The new CAD system based on the level set segmentation and the new mammographic feature space achieved a view-based A z value of 0.83±0.01. The improvement compared to the previous CAD system was statistically significant (p=0.02). When patient age was included in the new CAD system, view-based and case-based A z values were 0.85±0.01 and 0.87±0.02, respectively. The study also demonstrated the consistency of the newly developed CAD system by evaluating the statistics of the weights of the LDA classifiers in leave-one-case-out classification. Finally, an independent test on the publicly available digital database for screening

  5. CT liver volumetry using geodesic active contour segmentation with a level-set algorithm

    Science.gov (United States)

    Suzuki, Kenji; Epstein, Mark L.; Kohlbrenner, Ryan; Obajuluwa, Ademola; Xu, Jianwu; Hori, Masatoshi; Baron, Richard

    2010-03-01

    Automatic liver segmentation on CT images is challenging because the liver often abuts other organs of a similar density. Our purpose was to develop an accurate automated liver segmentation scheme for measuring liver volumes. We developed an automated volumetry scheme for the liver in CT based on a 5 step schema. First, an anisotropic smoothing filter was applied to portal-venous phase CT images to remove noise while preserving the liver structure, followed by an edge enhancer to enhance the liver boundary. By using the boundary-enhanced image as a speed function, a fastmarching algorithm generated an initial surface that roughly estimated the liver shape. A geodesic-active-contour segmentation algorithm coupled with level-set contour-evolution refined the initial surface so as to more precisely fit the liver boundary. The liver volume was calculated based on the refined liver surface. Hepatic CT scans of eighteen prospective liver donors were obtained under a liver transplant protocol with a multi-detector CT system. Automated liver volumes obtained were compared with those manually traced by a radiologist, used as "gold standard." The mean liver volume obtained with our scheme was 1,520 cc, whereas the mean manual volume was 1,486 cc, with the mean absolute difference of 104 cc (7.0%). CT liver volumetrics based on an automated scheme agreed excellently with "goldstandard" manual volumetrics (intra-class correlation coefficient was 0.95) with no statistically significant difference (p(F<=f)=0.32), and required substantially less completion time. Our automated scheme provides an efficient and accurate way of measuring liver volumes.

  6. Level-set segmentation of pulmonary nodules in megavolt electronic portal images using a CT prior

    International Nuclear Information System (INIS)

    Schildkraut, J. S.; Prosser, N.; Savakis, A.; Gomez, J.; Nazareth, D.; Singh, A. K.; Malhotra, H. K.

    2010-01-01

    Purpose: Pulmonary nodules present unique problems during radiation treatment due to nodule position uncertainty that is caused by respiration. The radiation field has to be enlarged to account for nodule motion during treatment. The purpose of this work is to provide a method of locating a pulmonary nodule in a megavolt portal image that can be used to reduce the internal target volume (ITV) during radiation therapy. A reduction in the ITV would result in a decrease in radiation toxicity to healthy tissue. Methods: Eight patients with nonsmall cell lung cancer were used in this study. CT scans that include the pulmonary nodule were captured with a GE Healthcare LightSpeed RT 16 scanner. Megavolt portal images were acquired with a Varian Trilogy unit equipped with an AS1000 electronic portal imaging device. The nodule localization method uses grayscale morphological filtering and level-set segmentation with a prior. The treatment-time portion of the algorithm is implemented on a graphical processing unit. Results: The method was retrospectively tested on eight cases that include a total of 151 megavolt portal image frames. The method reduced the nodule position uncertainty by an average of 40% for seven out of the eight cases. The treatment phase portion of the method has a subsecond execution time that makes it suitable for near-real-time nodule localization. Conclusions: A method was developed to localize a pulmonary nodule in a megavolt portal image. The method uses the characteristics of the nodule in a prior CT scan to enhance the nodule in the portal image and to identify the nodule region by level-set segmentation. In a retrospective study, the method reduced the nodule position uncertainty by an average of 40% for seven out of the eight cases studied.

  7. An improved level set method for brain MR images segmentation and bias correction.

    Science.gov (United States)

    Chen, Yunjie; Zhang, Jianwei; Macione, Jim

    2009-10-01

    Intensity inhomogeneities cause considerable difficulty in the quantitative analysis of magnetic resonance (MR) images. Thus, bias field estimation is a necessary step before quantitative analysis of MR data can be undertaken. This paper presents a variational level set approach to bias correction and segmentation for images with intensity inhomogeneities. Our method is based on an observation that intensities in a relatively small local region are separable, despite of the inseparability of the intensities in the whole image caused by the overall intensity inhomogeneity. We first define a localized K-means-type clustering objective function for image intensities in a neighborhood around each point. The cluster centers in this objective function have a multiplicative factor that estimates the bias within the neighborhood. The objective function is then integrated over the entire domain to define the data term into the level set framework. Our method is able to capture bias of quite general profiles. Moreover, it is robust to initialization, and thereby allows fully automated applications. The proposed method has been used for images of various modalities with promising results.

  8. Robust nuclei segmentation in cyto-histopathological images using statistical level set approach with topology preserving constraint

    Science.gov (United States)

    Taheri, Shaghayegh; Fevens, Thomas; Bui, Tien D.

    2017-02-01

    Computerized assessments for diagnosis or malignancy grading of cyto-histopathological specimens have drawn increased attention in the field of digital pathology. Automatic segmentation of cell nuclei is a fundamental step in such automated systems. Despite considerable research, nuclei segmentation is still a challenging task due noise, nonuniform illumination, and most importantly, in 2D projection images, overlapping and touching nuclei. In most published approaches, nuclei refinement is a post-processing step after segmentation, which usually refers to the task of detaching the aggregated nuclei or merging the over-segmented nuclei. In this work, we present a novel segmentation technique which effectively addresses the problem of individually segmenting touching or overlapping cell nuclei during the segmentation process. The proposed framework is a region-based segmentation method, which consists of three major modules: i) the image is passed through a color deconvolution step to extract the desired stains; ii) then the generalized fast radial symmetry transform is applied to the image followed by non-maxima suppression to specify the initial seed points for nuclei, and their corresponding GFRS ellipses which are interpreted as the initial nuclei borders for segmentation; iii) finally, these nuclei border initial curves are evolved through the use of a statistical level-set approach along with topology preserving criteria for segmentation and separation of nuclei at the same time. The proposed method is evaluated using Hematoxylin and Eosin, and fluorescent stained images, performing qualitative and quantitative analysis, showing that the method outperforms thresholding and watershed segmentation approaches.

  9. Efficient globally optimal segmentation of cells in fluorescence microscopy images using level sets and convex energy functionals.

    Science.gov (United States)

    Bergeest, Jan-Philip; Rohr, Karl

    2012-10-01

    In high-throughput applications, accurate and efficient segmentation of cells in fluorescence microscopy images is of central importance for the quantification of protein expression and the understanding of cell function. We propose an approach for segmenting cell nuclei which is based on active contours using level sets and convex energy functionals. Compared to previous work, our approach determines the global solution. Thus, the approach does not suffer from local minima and the segmentation result does not depend on the initialization. We consider three different well-known energy functionals for active contour-based segmentation and introduce convex formulations of these functionals. We also suggest a numeric approach for efficiently computing the solution. The performance of our approach has been evaluated using fluorescence microscopy images from different experiments comprising different cell types. We have also performed a quantitative comparison with previous segmentation approaches. Copyright © 2012 Elsevier B.V. All rights reserved.

  10. Automatic abdominal multi-organ segmentation using deep convolutional neural network and time-implicit level sets.

    Science.gov (United States)

    Hu, Peijun; Wu, Fa; Peng, Jialin; Bao, Yuanyuan; Chen, Feng; Kong, Dexing

    2017-03-01

    Multi-organ segmentation from CT images is an essential step for computer-aided diagnosis and surgery planning. However, manual delineation of the organs by radiologists is tedious, time-consuming and poorly reproducible. Therefore, we propose a fully automatic method for the segmentation of multiple organs from three-dimensional abdominal CT images. The proposed method employs deep fully convolutional neural networks (CNNs) for organ detection and segmentation, which is further refined by a time-implicit multi-phase evolution method. Firstly, a 3D CNN is trained to automatically localize and delineate the organs of interest with a probability prediction map. The learned probability map provides both subject-specific spatial priors and initialization for subsequent fine segmentation. Then, for the refinement of the multi-organ segmentation, image intensity models, probability priors as well as a disjoint region constraint are incorporated into an unified energy functional. Finally, a novel time-implicit multi-phase level-set algorithm is utilized to efficiently optimize the proposed energy functional model. Our method has been evaluated on 140 abdominal CT scans for the segmentation of four organs (liver, spleen and both kidneys). With respect to the ground truth, average Dice overlap ratios for the liver, spleen and both kidneys are 96.0, 94.2 and 95.4%, respectively, and average symmetric surface distance is less than 1.3 mm for all the segmented organs. The computation time for a CT volume is 125 s in average. The achieved accuracy compares well to state-of-the-art methods with much higher efficiency. A fully automatic method for multi-organ segmentation from abdominal CT images was developed and evaluated. The results demonstrated its potential in clinical usage with high effectiveness, robustness and efficiency.

  11. Automated volume analysis of head and neck lesions on CT scans using 3D level set segmentation

    International Nuclear Information System (INIS)

    Street, Ethan; Hadjiiski, Lubomir; Sahiner, Berkman; Gujar, Sachin; Ibrahim, Mohannad; Mukherji, Suresh K.; Chan, Heang-Ping

    2007-01-01

    The authors have developed a semiautomatic system for segmentation of a diverse set of lesions in head and neck CT scans. The system takes as input an approximate bounding box, and uses a multistage level set to perform the final segmentation. A data set consisting of 69 lesions marked on 33 scans from 23 patients was used to evaluate the performance of the system. The contours from automatic segmentation were compared to both 2D and 3D gold standard contours manually drawn by three experienced radiologists. Three performance metric measures were used for the comparison. In addition, a radiologist provided quality ratings on a 1 to 10 scale for all of the automatic segmentations. For this pilot study, the authors observed that the differences between the automatic and gold standard contours were larger than the interobserver differences. However, the system performed comparably to the radiologists, achieving an average area intersection ratio of 85.4% compared to an average of 91.2% between two radiologists. The average absolute area error was 21.1% compared to 10.8%, and the average 2D distance was 1.38 mm compared to 0.84 mm between the radiologists. In addition, the quality rating data showed that, despite the very lax assumptions made on the lesion characteristics in designing the system, the automatic contours approximated many of the lesions very well

  12. 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.

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

    Science.gov (United States)

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

    2013-01-01

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

  14. 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

  15. 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...

  16. Automatic optimal filament segmentation with sub-pixel accuracy using generalized linear models and B-spline level-sets.

    Science.gov (United States)

    Xiao, Xun; Geyer, Veikko F; Bowne-Anderson, Hugo; Howard, Jonathon; Sbalzarini, Ivo F

    2016-08-01

    Biological filaments, such as actin filaments, microtubules, and cilia, are often imaged using different light-microscopy techniques. Reconstructing the filament curve from the acquired images constitutes the filament segmentation problem. Since filaments have lower dimensionality than the image itself, there is an inherent trade-off between tracing the filament with sub-pixel accuracy and avoiding noise artifacts. Here, we present a globally optimal filament segmentation method based on B-spline vector level-sets and a generalized linear model for the pixel intensity statistics. We show that the resulting optimization problem is convex and can hence be solved with global optimality. We introduce a simple and efficient algorithm to compute such optimal filament segmentations, and provide an open-source implementation as an ImageJ/Fiji plugin. We further derive an information-theoretic lower bound on the filament segmentation error, quantifying how well an algorithm could possibly do given the information in the image. We show that our algorithm asymptotically reaches this bound in the spline coefficients. We validate our method in comprehensive benchmarks, compare with other methods, and show applications from fluorescence, phase-contrast, and dark-field microscopy. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  17. SparCLeS: dynamic l₁ sparse classifiers with level sets for robust beard/moustache detection and segmentation.

    Science.gov (United States)

    Le, T Hoang Ngan; Luu, Khoa; Savvides, Marios

    2013-08-01

    Robust facial hair detection and segmentation is a highly valued soft biometric attribute for carrying out forensic facial analysis. In this paper, we propose a novel and fully automatic system, called SparCLeS, for beard/moustache detection and segmentation in challenging facial images. SparCLeS uses the multiscale self-quotient (MSQ) algorithm to preprocess facial images and deal with illumination variation. Histogram of oriented gradients (HOG) features are extracted from the preprocessed images and a dynamic sparse classifier is built using these features to classify a facial region as either containing skin or facial hair. A level set based approach, which makes use of the advantages of both global and local information, is then used to segment the regions of a face containing facial hair. Experimental results demonstrate the effectiveness of our proposed system in detecting and segmenting facial hair regions in images drawn from three databases, i.e., the NIST Multiple Biometric Grand Challenge (MBGC) still face database, the NIST Color Facial Recognition Technology FERET database, and the Labeled Faces in the Wild (LFW) database.

  18. Quantitative characterization of metastatic disease in the spine. Part I. Semiautomated segmentation using atlas-based deformable registration and the level set method

    International Nuclear Information System (INIS)

    Hardisty, M.; Gordon, L.; Agarwal, P.; Skrinskas, T.; Whyne, C.

    2007-01-01

    Quantitative assessment of metastatic disease in bone is often considered immeasurable and, as such, patients with skeletal metastases are often excluded from clinical trials. In order to effectively quantify the impact of metastatic tumor involvement in the spine, accurate segmentation of the vertebra is required. Manual segmentation can be accurate but involves extensive and time-consuming user interaction. Potential solutions to automating segmentation of metastatically involved vertebrae are demons deformable image registration and level set methods. The purpose of this study was to develop a semiautomated method to accurately segment tumor-bearing vertebrae using the aforementioned techniques. By maintaining morphology of an atlas, the demons-level set composite algorithm was able to accurately differentiate between trans-cortical tumors and surrounding soft tissue of identical intensity. The algorithm successfully segmented both the vertebral body and trabecular centrum of tumor-involved and healthy vertebrae. This work validates our approach as equivalent in accuracy to an experienced user

  19. 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.

  20. A segmentation and classification scheme for single tooth in MicroCT images based on 3D level set and k-means+.

    Science.gov (United States)

    Wang, Liansheng; Li, Shusheng; Chen, Rongzhen; Liu, Sze-Yu; Chen, Jyh-Cheng

    2017-04-01

    Accurate classification of different anatomical structures of teeth from medical images provides crucial information for the stress analysis in dentistry. Usually, the anatomical structures of teeth are manually labeled by experienced clinical doctors, which is time consuming. However, automatic segmentation and classification is a challenging task because the anatomical structures and surroundings of the tooth in medical images are rather complex. Therefore, in this paper, we propose an effective framework which is designed to segment the tooth with a Selective Binary and Gaussian Filtering Regularized Level Set (GFRLS) method improved by fully utilizing 3 dimensional (3D) information, and classify the tooth by employing unsupervised learning i.e., k-means++ method. In order to evaluate the proposed method, the experiments are conducted on the sufficient and extensive datasets of mandibular molars. The experimental results show that our method can achieve higher accuracy and robustness compared to other three clustering methods. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. 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....

  2. 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

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

    International Nuclear Information System (INIS)

    Suzuki, Kenji; Kohlbrenner, Ryan; Epstein, Mark L.; Obajuluwa, Ademola M.; Xu Jianwu; Hori, Masatoshi

    2010-01-01

    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 completion time

  4. Evaluation of Parallel Level Sets and Bowsher's Method as Segmentation-Free Anatomical Priors for Time-of-Flight PET Reconstruction.

    Science.gov (United States)

    Schramm, Georg; Holler, Martin; Rezaei, Ahmadreza; Vunckx, Kathleen; Knoll, Florian; Bredies, Kristian; Boada, Fernando; Nuyts, Johan

    2018-02-01

    In this article, we evaluate Parallel Level Sets (PLS) and Bowsher's method as segmentation-free anatomical priors for regularized brain positron emission tomography (PET) reconstruction. We derive the proximity operators for two PLS priors and use the EM-TV algorithm in combination with the first order primal-dual algorithm by Chambolle and Pock to solve the non-smooth optimization problem for PET reconstruction with PLS regularization. In addition, we compare the performance of two PLS versions against the symmetric and asymmetric Bowsher priors with quadratic and relative difference penalty function. For this aim, we first evaluate reconstructions of 30 noise realizations of simulated PET data derived from a real hybrid positron emission tomography/magnetic resonance imaging (PET/MR) acquisition in terms of regional bias and noise. Second, we evaluate reconstructions of a real brain PET/MR data set acquired on a GE Signa time-of-flight PET/MR in a similar way. The reconstructions of simulated and real 3D PET/MR data show that all priors were superior to post-smoothed maximum likelihood expectation maximization with ordered subsets (OSEM) in terms of bias-noise characteristics in different regions of interest where the PET uptake follows anatomical boundaries. Our implementation of the asymmetric Bowsher prior showed slightly superior performance compared with the two versions of PLS and the symmetric Bowsher prior. At very high regularization weights, all investigated anatomical priors suffer from the transfer of non-shared gradients.

  5. A Rough Set Approach for Customer Segmentation

    Directory of Open Access Journals (Sweden)

    Prabha Dhandayudam

    2014-04-01

    Full Text Available Customer segmentation is a process that divides a business's total customers into groups according to their diversity of purchasing behavior and characteristics. The data mining clustering technique can be used to accomplish this customer segmentation. This technique clusters the customers in such a way that the customers in one group behave similarly when compared to the customers in other groups. The customer related data are categorical in nature. However, the clustering algorithms for categorical data are few and are unable to handle uncertainty. Rough set theory (RST is a mathematical approach that handles uncertainty and is capable of discovering knowledge from a database. This paper proposes a new clustering technique called MADO (Minimum Average Dissimilarity between Objects for categorical data based on elements of RST. The proposed algorithm is compared with other RST based clustering algorithms, such as MMR (Min-Min Roughness, MMeR (Min Mean Roughness, SDR (Standard Deviation Roughness, SSDR (Standard deviation of Standard Deviation Roughness, and MADE (Maximal Attributes DEpendency. The results show that for the real customer data considered, the MADO algorithm achieves clusters with higher cohesion, lower coupling, and less computational complexity when compared to the above mentioned algorithms. The proposed algorithm has also been tested on a synthetic data set to prove that it is also suitable for high dimensional data.

  6. 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.

  7. A fully automated and reproducible level-set segmentation approach for generation of MR-based attenuation correction map of PET images in the brain employing single STE-MR imaging modality

    Energy Technology Data Exchange (ETDEWEB)

    Kazerooni, Anahita Fathi; Aarabi, Mohammad Hadi [Quantitative MR Imaging and Spectroscopy Group, Research Center for Cellular and Molecular Imaging, Tehran University of Medical Sciences, Tehran (Iran, Islamic Republic of); Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran (Iran, Islamic Republic of); Ay, Mohammadreza [Quantitative MR Imaging and Spectroscopy Group, Research Center for Cellular and Molecular Imaging, Tehran University of Medical Sciences, Tehran (Iran, Islamic Republic of); Medical Imaging Systems Group, Research Center for Cellular and Molecular Imaging, Tehran University of Medical Sciences, Tehran (Iran, Islamic Republic of); Rad, Hamidreza Saligheh [Quantitative MR Imaging and Spectroscopy Group, Research Center for Cellular and Molecular Imaging, Tehran University of Medical Sciences, Tehran (Iran, Islamic Republic of); Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran (Iran, Islamic Republic of)

    2014-07-29

    Generating MR-based attenuation correction map (μ-map) for quantitative reconstruction of PET images still remains a challenge in hybrid PET/MRI systems, mainly because cortical bone structures are indistinguishable from proximal air cavities in conventional MR images. Recently, development of short echo-time (STE) MR imaging sequences, has shown promise in differentiating cortical bone from air. However, on STE-MR images, the bone appears with discontinuous boundaries. Therefore, segmentation techniques based on intensity classification, such as thresholding or fuzzy C-means, fail to homogeneously delineate bone boundaries, especially in the presence of intrinsic noise and intensity inhomogeneity. Consequently, they cannot be fully automatized, must be fine-tuned on the case-by-case basis, and require additional morphological operations for segmentation refinement. To overcome the mentioned problems, in this study, we introduce a new fully automatic and reproducible STE-MR segmentation approach exploiting level-set in a clustering-based intensity inhomogeneity correction framework to reliably delineate bone from soft tissue and air.

  8. A fully automated and reproducible level-set segmentation approach for generation of MR-based attenuation correction map of PET images in the brain employing single STE-MR imaging modality

    International Nuclear Information System (INIS)

    Kazerooni, Anahita Fathi; Aarabi, Mohammad Hadi; Ay, Mohammadreza; Rad, Hamidreza Saligheh

    2014-01-01

    Generating MR-based attenuation correction map (μ-map) for quantitative reconstruction of PET images still remains a challenge in hybrid PET/MRI systems, mainly because cortical bone structures are indistinguishable from proximal air cavities in conventional MR images. Recently, development of short echo-time (STE) MR imaging sequences, has shown promise in differentiating cortical bone from air. However, on STE-MR images, the bone appears with discontinuous boundaries. Therefore, segmentation techniques based on intensity classification, such as thresholding or fuzzy C-means, fail to homogeneously delineate bone boundaries, especially in the presence of intrinsic noise and intensity inhomogeneity. Consequently, they cannot be fully automatized, must be fine-tuned on the case-by-case basis, and require additional morphological operations for segmentation refinement. To overcome the mentioned problems, in this study, we introduce a new fully automatic and reproducible STE-MR segmentation approach exploiting level-set in a clustering-based intensity inhomogeneity correction framework to reliably delineate bone from soft tissue and air.

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

    International Nuclear Information System (INIS)

    Kshetri, R; Bhattacharya, P

    2014-01-01

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

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

    Science.gov (United States)

    Mo, Juan; Zhang, Lei

    2017-12-01

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

  12. 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 Voron...

  13. 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.

  14. Fast Sparse Level Sets on Graphics Hardware

    NARCIS (Netherlands)

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

    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

  15. 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

  16. 3D variational brain tumor segmentation using Dirichlet priors on a clustered feature set.

    Science.gov (United States)

    Popuri, Karteek; Cobzas, Dana; Murtha, Albert; Jägersand, Martin

    2012-07-01

    Brain tumor segmentation is a required step before any radiation treatment or surgery. When performed manually, segmentation is time consuming and prone to human errors. Therefore, there have been significant efforts to automate the process. But, automatic tumor segmentation from MRI data is a particularly challenging task. Tumors have a large diversity in shape and appearance with intensities overlapping the normal brain tissues. In addition, an expanding tumor can also deflect and deform nearby tissue. In our work, we propose an automatic brain tumor segmentation method that addresses these last two difficult problems. We use the available MRI modalities (T1, T1c, T2) and their texture characteristics to construct a multidimensional feature set. Then, we extract clusters which provide a compact representation of the essential information in these features. The main idea in this work is to incorporate these clustered features into the 3D variational segmentation framework. In contrast to previous variational approaches, we propose a segmentation method that evolves the contour in a supervised fashion. The segmentation boundary is driven by the learned region statistics in the cluster space. We incorporate prior knowledge about the normal brain tissue appearance during the estimation of these region statistics. In particular, we use a Dirichlet prior that discourages the clusters from the normal brain region to be in the tumor region. This leads to a better disambiguation of the tumor from brain tissue. We evaluated the performance of our automatic segmentation method on 15 real MRI scans of brain tumor patients, with tumors that are inhomogeneous in appearance, small in size and in proximity to the major structures in the brain. Validation with the expert segmentation labels yielded encouraging results: Jaccard (58%), Precision (81%), Recall (67%), Hausdorff distance (24 mm). Using priors on the brain/tumor appearance, our proposed automatic 3D variational

  17. Hybrid approach for detection of dental caries based on the methods FCM and level sets

    Science.gov (United States)

    Chaabene, Marwa; Ben Ali, Ramzi; Ejbali, Ridha; Zaied, Mourad

    2017-03-01

    This paper presents a new technique for detection of dental caries that is a bacterial disease that destroys the tooth structure. In our approach, we have achieved a new segmentation method that combines the advantages of fuzzy C mean algorithm and level set method. The results obtained by the FCM algorithm will be used by Level sets algorithm to reduce the influence of the noise effect on the working of each of these algorithms, to facilitate level sets manipulation and to lead to more robust segmentation. The sensitivity and specificity confirm the effectiveness of proposed method for caries detection.

  18. 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.

  19. 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.

  20. 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.

  1. Jansen-MIDAS: A multi-level photomicrograph segmentation software based on isotropic undecimated wavelets.

    Science.gov (United States)

    de Siqueira, Alexandre Fioravante; Cabrera, Flávio Camargo; Nakasuga, Wagner Massayuki; Pagamisse, Aylton; Job, Aldo Eloizo

    2018-01-01

    Image segmentation, the process of separating the elements within a picture, is frequently used for obtaining information from photomicrographs. Segmentation methods should be used with reservations, since incorrect results can mislead when interpreting regions of interest (ROI). This decreases the success rate of extra procedures. Multi-Level Starlet Segmentation (MLSS) and Multi-Level Starlet Optimal Segmentation (MLSOS) were developed to be an alternative for general segmentation tools. These methods gave rise to Jansen-MIDAS, an open-source software. A scientist can use it to obtain several segmentations of hers/his photomicrographs. It is a reliable alternative to process different types of photomicrographs: previous versions of Jansen-MIDAS were used to segment ROI in photomicrographs of two different materials, with an accuracy superior to 89%. © 2017 Wiley Periodicals, Inc.

  2. Radiographic Results of Single Level Transforaminal Lumbar Interbody Fusion in Degenerative Lumbar Spine Disease: Focusing on Changes of Segmental Lordosis in Fusion Segment

    OpenAIRE

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

    2009-01-01

    Background 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. Methods 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. Results The segmental lordosi...

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

    International Nuclear Information System (INIS)

    Zhao, Tingting; Ruan, Dan

    2016-01-01

    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. (paper)

  4. 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

  5. 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.

  6. 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.

  7. Active Segmentation.

    Science.gov (United States)

    Mishra, Ajay; Aloimonos, Yiannis

    2009-01-01

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

  8. 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.

  9. Testing of the level density segment of the RIPL

    International Nuclear Information System (INIS)

    Capote, Roberto

    2000-01-01

    A comparison between RIPL phenomenological state density parameterizations and microscopical state density (SD) codes was performed for nickel and samarium isotopes. All the codes were shown to be complete. More work is needed on calculation of the collective enhancement of the level densities to improve currently used phenomenological recipes. It was shown that phenomenological closed formulae for particle-hole state density fails to describe microscopical calculation for magic nuclei. For deformed nuclei, like Sm-152, the agreement of Williams closed formulae considering Kalbach pairing correction with microscopical SID calculations was very good. (author)

  10. 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.

  11. Measurement of thermally ablated lesions in sonoelastographic images using level set methods

    Science.gov (United States)

    Castaneda, Benjamin; Tamez-Pena, Jose Gerardo; Zhang, Man; Hoyt, Kenneth; Bylund, Kevin; Christensen, Jared; Saad, Wael; Strang, John; Rubens, Deborah J.; Parker, Kevin J.

    2008-03-01

    The capability of sonoelastography to detect lesions based on elasticity contrast can be applied to monitor the creation of thermally ablated lesion. Currently, segmentation of lesions depicted in sonoelastographic images is performed manually which can be a time consuming process and prone to significant intra- and inter-observer variability. This work presents a semi-automated segmentation algorithm for sonoelastographic data. The user starts by planting a seed in the perceived center of the lesion. Fast marching methods use this information to create an initial estimate of the lesion. Subsequently, level set methods refine its final shape by attaching the segmented contour to edges in the image while maintaining smoothness. The algorithm is applied to in vivo sonoelastographic images from twenty five thermal ablated lesions created in porcine livers. The estimated area is compared to results from manual segmentation and gross pathology images. Results show that the algorithm outperforms manual segmentation in accuracy, inter- and intra-observer variability. The processing time per image is significantly reduced.

  12. A parametric level-set method for partially discrete tomography

    NARCIS (Netherlands)

    A. Kadu (Ajinkya); T. van Leeuwen (Tristan); K.J. Batenburg (Joost)

    2017-01-01

    textabstractThis paper introduces a parametric level-set method for tomographic reconstruction of partially discrete images. Such images consist of a continuously varying background and an anomaly with a constant (known) grey-value. We express the geometry of the anomaly using a level-set function,

  13. 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.

  14. 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.

  15. Novel gene sets improve set-level classification of prokaryotic gene expression data.

    Science.gov (United States)

    Holec, Matěj; Kuželka, Ondřej; Železný, Filip

    2015-10-28

    Set-level classification of gene expression data has received significant attention recently. In this setting, high-dimensional vectors of features corresponding to genes are converted into lower-dimensional vectors of features corresponding to biologically interpretable gene sets. The dimensionality reduction brings the promise of a decreased risk of overfitting, potentially resulting in improved accuracy of the learned classifiers. However, recent empirical research has not confirmed this expectation. Here we hypothesize that the reported unfavorable classification results in the set-level framework were due to the adoption of unsuitable gene sets defined typically on the basis of the Gene ontology and the KEGG database of metabolic networks. We explore an alternative approach to defining gene sets, based on regulatory interactions, which we expect to collect genes with more correlated expression. We hypothesize that such more correlated gene sets will enable to learn more accurate classifiers. We define two families of gene sets using information on regulatory interactions, and evaluate them on phenotype-classification tasks using public prokaryotic gene expression data sets. From each of the two gene-set families, we first select the best-performing subtype. The two selected subtypes are then evaluated on independent (testing) data sets against state-of-the-art gene sets and against the conventional gene-level approach. The novel gene sets are indeed more correlated than the conventional ones, and lead to significantly more accurate classifiers. The novel gene sets are indeed more correlated than the conventional ones, and lead to significantly more accurate classifiers. Novel gene sets defined on the basis of regulatory interactions improve set-level classification of gene expression data. The experimental scripts and other material needed to reproduce the experiments are available at http://ida.felk.cvut.cz/novelgenesets.tar.gz.

  16. 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....

  17. Multi person detection and tracking based on hierarchical level-set method

    Science.gov (United States)

    Khraief, Chadia; Benzarti, Faouzi; Amiri, Hamid

    2018-04-01

    In this paper, we propose an efficient unsupervised method for mutli-person tracking based on hierarchical level-set approach. The proposed method uses both edge and region information in order to effectively detect objects. The persons are tracked on each frame of the sequence by minimizing an energy functional that combines color, texture and shape information. These features are enrolled in covariance matrix as region descriptor. The present method is fully automated without the need to manually specify the initial contour of Level-set. It is based on combined person detection and background subtraction methods. The edge-based is employed to maintain a stable evolution, guide the segmentation towards apparent boundaries and inhibit regions fusion. The computational cost of level-set is reduced by using narrow band technique. Many experimental results are performed on challenging video sequences and show the effectiveness of the proposed method.

  18. 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

  19. Some numerical studies of interface advection properties of level set ...

    Indian Academy of Sciences (India)

    explicit computational elements moving through an Eulerian grid. ... location. The interface is implicitly defined (captured) as the location of the discontinuity in the ... This level set function is advected with the background flow field and thus ...

  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. 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.

  2. 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.

  3. Role of the B Allele of Influenza A Virus Segment 8 in Setting Mammalian Host Range and Pathogenicity.

    Science.gov (United States)

    Turnbull, Matthew L; Wise, Helen M; Nicol, Marlynne Q; Smith, Nikki; Dunfee, Rebecca L; Beard, Philippa M; Jagger, Brett W; Ligertwood, Yvonne; Hardisty, Gareth R; Xiao, Haixia; Benton, Donald J; Coburn, Alice M; Paulo, Joao A; Gygi, Steven P; McCauley, John W; Taubenberger, Jeffery K; Lycett, Samantha J; Weekes, Michael P; Dutia, Bernadette M; Digard, Paul

    2016-10-15

    Two alleles of segment 8 (NS) circulate in nonchiropteran influenza A viruses. The A allele is found in avian and mammalian viruses, but the B allele is viewed as being almost exclusively found in avian viruses. This might reflect the fact that one or both of its encoded proteins (NS1 and NEP) are maladapted for replication in mammalian hosts. To test this, a number of clade A and B avian virus-derived NS segments were introduced into human H1N1 and H3N2 viruses. In no case was the peak virus titer substantially reduced following infection of various mammalian cell types. Exemplar reassortant viruses also replicated to similar titers in mice, although mice infected with viruses with the avian virus-derived segment 8s had reduced weight loss compared to that achieved in mice infected with the A/Puerto Rico/8/1934 (H1N1) parent. In vitro, the viruses coped similarly with type I interferons. Temporal proteomics analysis of cellular responses to infection showed that the avian virus-derived NS segments provoked lower levels of expression of interferon-stimulated genes in cells than wild type-derived NS segments. Thus, neither the A nor the B allele of avian virus-derived NS segments necessarily attenuates virus replication in a mammalian host, although the alleles can attenuate disease. Phylogenetic analyses identified 32 independent incursions of an avian virus-derived A allele into mammals, whereas 6 introductions of a B allele were identified. However, A-allele isolates from birds outnumbered B-allele isolates, and the relative rates of Aves-to-Mammalia transmission were not significantly different. We conclude that while the introduction of an avian virus segment 8 into mammals is a relatively rare event, the dogma of the B allele being especially restricted is misleading, with implications in the assessment of the pandemic potential of avian influenza viruses. Influenza A virus (IAV) can adapt to poultry and mammalian species, inflicting a great socioeconomic

  4. Classification of Normal and Apoptotic Cells from Fluorescence Microscopy Images Using Generalized Polynomial Chaos and Level Set Function.

    Science.gov (United States)

    Du, Yuncheng; Budman, Hector M; Duever, Thomas A

    2016-06-01

    Accurate automated quantitative analysis of living cells based on fluorescence microscopy images can be very useful for fast evaluation of experimental outcomes and cell culture protocols. In this work, an algorithm is developed for fast differentiation of normal and apoptotic viable Chinese hamster ovary (CHO) cells. For effective segmentation of cell images, a stochastic segmentation algorithm is developed by combining a generalized polynomial chaos expansion with a level set function-based segmentation algorithm. This approach provides a probabilistic description of the segmented cellular regions along the boundary, from which it is possible to calculate morphological changes related to apoptosis, i.e., the curvature and length of a cell's boundary. These features are then used as inputs to a support vector machine (SVM) classifier that is trained to distinguish between normal and apoptotic viable states of CHO cell images. The use of morphological features obtained from the stochastic level set segmentation of cell images in combination with the trained SVM classifier is more efficient in terms of differentiation accuracy as compared with the original deterministic level set method.

  5. 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.

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

    International Nuclear Information System (INIS)

    Kwak, In Hae; Son, Minjun; Hagen, Stephen J.

    2012-01-01

    Highlights: ► We present a method for extracting gene expression data from images of bacterial cells. ► The method does not employ cell segmentation and does not require high magnification. ► Fluorescence and phase contrast images of the cells are correlated through the physics of phase contrast. ► 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.

  7. Exploring the level sets of quantum control landscapes

    International Nuclear Information System (INIS)

    Rothman, Adam; Ho, Tak-San; Rabitz, Herschel

    2006-01-01

    A quantum control landscape is defined by the value of a physical observable as a functional of the time-dependent control field E(t) for a given quantum-mechanical system. Level sets through this landscape are prescribed by a particular value of the target observable at the final dynamical time T, regardless of the intervening dynamics. We present a technique for exploring a landscape level set, where a scalar variable s is introduced to characterize trajectories along these level sets. The control fields E(s,t) accomplishing this exploration (i.e., that produce the same value of the target observable for a given system) are determined by solving a differential equation over s in conjunction with the time-dependent Schroedinger equation. There is full freedom to traverse a level set, and a particular trajectory is realized by making an a priori choice for a continuous function f(s,t) that appears in the differential equation for the control field. The continuous function f(s,t) can assume an arbitrary form, and thus a level set generally contains a family of controls, where each control takes the quantum system to the same final target value, but produces a distinct control mechanism. In addition, although the observable value remains invariant over the level set, other dynamical properties (e.g., the degree of robustness to control noise) are not specifically preserved and can vary greatly. Examples are presented to illustrate the continuous nature of level-set controls and their associated induced dynamical features, including continuously morphing mechanisms for population control in model quantum systems

  8. On multiple level-set regularization methods for inverse problems

    International Nuclear Information System (INIS)

    DeCezaro, A; Leitão, A; Tai, X-C

    2009-01-01

    We analyze a multiple level-set method for solving inverse problems with piecewise constant solutions. This method corresponds to an iterated Tikhonov method for a particular Tikhonov functional G α based on TV–H 1 penalization. We define generalized minimizers for our Tikhonov functional and establish an existence result. Moreover, we prove convergence and stability results of the proposed Tikhonov method. A multiple level-set algorithm is derived from the first-order optimality conditions for the Tikhonov functional G α , similarly as the iterated Tikhonov method. The proposed multiple level-set method is tested on an inverse potential problem. Numerical experiments show that the method is able to recover multiple objects as well as multiple contrast levels

  9. Failed back surgery syndrome: the role of symptomatic segmental single-level instability after lumbar microdiscectomy.

    Science.gov (United States)

    Schaller, B

    2004-05-01

    Segmental instability represents one of several different factors that may cause or contribute to the failed back surgery syndrome after lumbar microdiscectomy. As segmental lumbar instability poses diagnostic problems by lack of clear radiological and clinical criteria, only little is known about the occurrence of this phenomenon following primary microdiscectomy. Retrospectively, the records of 2,353 patients were reviewed according to postoperative symptomatic segmental single-level instability after lumbar microdiscectomy between 1989 and 1997. Progressive neurological deficits increased (mean of 24 months; SD: 12, range 1-70) after the initial surgical procedure in 12 patients. The mean age of the four men and eight women was 43 years (SD: 6, range 40-77). The main symptoms and signs of secondary neurological deterioration were radicular pain in 9 of 12 patients, increased motor weakness in 6 of 12 patients and sensory deficits in 4 of 12 patients. All 12 symptomatic patients had radiological evidence of segmental changes correlating with the clinical symptoms and signs. All but one patient showed a decrease in the disc height greater than 30% at the time of posterior spondylodesis compared with the preoperative images before lumbar microdiscectomy. All patients underwent secondary laminectomy and posterior lumbar sponylodesis. Postoperatively, pain improved in 8 of 9 patients, motor weakness in 3 of 6 patients, and sensory deficits in 2 of 4 patients. During the follow-up period of 72+/-7 months, one patient required a third operation to alleviate spinal stenosis at the upper end of the laminectomy. Patients with secondary segmental instability following microdiscectomy were mainly in their 40s. Postoperative narrowing of the intervertebral space following lumbar microdiscectomy is correlated to the degree of intervertebral disc resection. It can therefore be concluded that (1) patients in their 40s are prone to postoperative narrowing of the intervertebral

  10. 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.

  11. 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.

  12. Level Set Structure of an Integrable Cellular Automaton

    Directory of Open Access Journals (Sweden)

    Taichiro Takagi

    2010-03-01

    Full Text Available Based on a group theoretical setting a sort of discrete dynamical system is constructed and applied to a combinatorial dynamical system defined on the set of certain Bethe ansatz related objects known as the rigged configurations. This system is then used to study a one-dimensional periodic cellular automaton related to discrete Toda lattice. It is shown for the first time that the level set of this cellular automaton is decomposed into connected components and every such component is a torus.

  13. 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.

  14. 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.

  15. 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...

  16. Level set methods for inverse scattering—some recent developments

    International Nuclear Information System (INIS)

    Dorn, Oliver; Lesselier, Dominique

    2009-01-01

    We give an update on recent techniques which use a level set representation of shapes for solving inverse scattering problems, completing in that matter the exposition made in (Dorn and Lesselier 2006 Inverse Problems 22 R67) and (Dorn and Lesselier 2007 Deformable Models (New York: Springer) pp 61–90), and bringing it closer to the current state of the art

  17. Structural level set inversion for microwave breast screening

    International Nuclear Information System (INIS)

    Irishina, Natalia; Álvarez, Diego; Dorn, Oliver; Moscoso, Miguel

    2010-01-01

    We present a new inversion strategy for the early detection of breast cancer from microwave data which is based on a new multiphase level set technique. This novel structural inversion method uses a modification of the color level set technique adapted to the specific situation of structural breast imaging taking into account the high complexity of the breast tissue. We only use data of a few microwave frequencies for detecting the tumors hidden in this complex structure. Three level set functions are employed for describing four different types of breast tissue, where each of these four regions is allowed to have a complicated topology and to have an interior structure which needs to be estimated from the data simultaneously with the region interfaces. The algorithm consists of several stages of increasing complexity. In each stage more details about the anatomical structure of the breast interior is incorporated into the inversion model. The synthetic breast models which are used for creating simulated data are based on real MRI images of the breast and are therefore quite realistic. Our results demonstrate the potential and feasibility of the proposed level set technique for detecting, locating and characterizing a small tumor in its early stage of development embedded in such a realistic breast model. Both the data acquisition simulation and the inversion are carried out in 2D

  18. Level-Set Methodology on Adaptive Octree Grids

    Science.gov (United States)

    Gibou, Frederic; Guittet, Arthur; Mirzadeh, Mohammad; Theillard, Maxime

    2017-11-01

    Numerical simulations of interfacial problems in fluids require a methodology capable of tracking surfaces that can undergo changes in topology and capable to imposing jump boundary conditions in a sharp manner. In this talk, we will discuss recent advances in the level-set framework, in particular one that is based on adaptive grids.

  19. 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

  20. Discretisation Schemes for Level Sets of Planar Gaussian Fields

    Science.gov (United States)

    Beliaev, D.; Muirhead, S.

    2018-01-01

    Smooth random Gaussian functions play an important role in mathematical physics, a main example being the random plane wave model conjectured by Berry to give a universal description of high-energy eigenfunctions of the Laplacian on generic compact manifolds. Our work is motivated by questions about the geometry of such random functions, in particular relating to the structure of their nodal and level sets. We study four discretisation schemes that extract information about level sets of planar Gaussian fields. Each scheme recovers information up to a different level of precision, and each requires a maximum mesh-size in order to be valid with high probability. The first two schemes are generalisations and enhancements of similar schemes that have appeared in the literature (Beffara and Gayet in Publ Math IHES, 2017. https://doi.org/10.1007/s10240-017-0093-0; Mischaikow and Wanner in Ann Appl Probab 17:980-1018, 2007); these give complete topological information about the level sets on either a local or global scale. As an application, we improve the results in Beffara and Gayet (2017) on Russo-Seymour-Welsh estimates for the nodal set of positively-correlated planar Gaussian fields. The third and fourth schemes are, to the best of our knowledge, completely new. The third scheme is specific to the nodal set of the random plane wave, and provides global topological information about the nodal set up to `visible ambiguities'. The fourth scheme gives a way to approximate the mean number of excursion domains of planar Gaussian fields.

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

    Science.gov (United States)

    Kwak, In Hae; Son, Minjun; Hagen, Stephen J

    2012-05-11

    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. Copyright © 2012 Elsevier Inc. All rights reserved.

  2. Multi-segmental movement patterns reflect juggling complexity and skill level.

    Science.gov (United States)

    Zago, Matteo; Pacifici, Ilaria; Lovecchio, Nicola; Galli, Manuela; Federolf, Peter Andreas; Sforza, Chiarella

    2017-08-01

    The juggling action of six experts and six intermediates jugglers was recorded with a motion capture system and decomposed into its fundamental components through Principal Component Analysis. The aim was to quantify trends in movement dimensionality, multi-segmental patterns and rhythmicity as a function of proficiency level and task complexity. Dimensionality was quantified in terms of Residual Variance, while the Relative Amplitude was introduced to account for individual differences in movement components. We observed that: experience-related modifications in multi-segmental actions exist, such as the progressive reduction of error-correction movements, especially in complex task condition. The systematic identification of motor patterns sensitive to the acquisition of specific experience could accelerate the learning process. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. 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

  4. Gradient augmented level set method for phase change simulations

    Science.gov (United States)

    Anumolu, Lakshman; Trujillo, Mario F.

    2018-01-01

    A numerical method for the simulation of two-phase flow with phase change based on the Gradient-Augmented-Level-set (GALS) strategy is presented. Sharp capturing of the vaporization process is enabled by: i) identification of the vapor-liquid interface, Γ (t), at the subgrid level, ii) discontinuous treatment of thermal physical properties (except for μ), and iii) enforcement of mass, momentum, and energy jump conditions, where the gradients of the dependent variables are obtained at Γ (t) and are consistent with their analytical expression, i.e. no local averaging is applied. Treatment of the jump in velocity and pressure at Γ (t) is achieved using the Ghost Fluid Method. The solution of the energy equation employs the sub-grid knowledge of Γ (t) to discretize the temperature Laplacian using second-order one-sided differences, i.e. the numerical stencil completely resides within each respective phase. To carefully evaluate the benefits or disadvantages of the GALS approach, the standard level set method is implemented and compared against the GALS predictions. The results show the expected trend that interface identification and transport are predicted noticeably better with GALS over the standard level set. This benefit carries over to the prediction of the Laplacian and temperature gradients in the neighborhood of the interface, which are directly linked to the calculation of the vaporization rate. However, when combining the calculation of interface transport and reinitialization with two-phase momentum and energy, the benefits of GALS are to some extent neutralized, and the causes for this behavior are identified and analyzed. Overall the additional computational costs associated with GALS are almost the same as those using the standard level set technique.

  5. Election Districts and Precincts, PrecinctPoly-The data set is a polygon feature consisting of 220 segments representing voter precinct boundaries., Published in 1991, Davis County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Election Districts and Precincts dataset current as of 1991. PrecinctPoly-The data set is a polygon feature consisting of 220 segments representing voter precinct...

  6. 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. PMID:22275894

  7. 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.

  8. 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.

  9. 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...

  10. Skull defect reconstruction based on a new hybrid level set.

    Science.gov (United States)

    Zhang, Ziqun; Zhang, Ran; Song, Zhijian

    2014-01-01

    Skull defect reconstruction is an important aspect of surgical repair. Historically, a skull defect prosthesis was created by the mirroring technique, surface fitting, or formed templates. These methods are not based on the anatomy of the individual patient's skull, and therefore, the prosthesis cannot precisely correct the defect. This study presented a new hybrid level set model, taking into account both the global optimization region information and the local accuracy edge information, while avoiding re-initialization during the evolution of the level set function. Based on the new method, a skull defect was reconstructed, and the skull prosthesis was produced by rapid prototyping technology. This resulted in a skull defect prosthesis that well matched the skull defect with excellent individual adaptation.

  11. Level-set techniques for facies identification in reservoir modeling

    Science.gov (United States)

    Iglesias, Marco A.; McLaughlin, Dennis

    2011-03-01

    In this paper we investigate the application of level-set techniques for facies identification in reservoir models. The identification of facies is a geometrical inverse ill-posed problem that we formulate in terms of shape optimization. The goal is to find a region (a geologic facies) that minimizes the misfit between predicted and measured data from an oil-water reservoir. In order to address the shape optimization problem, we present a novel application of the level-set iterative framework developed by Burger in (2002 Interfaces Free Bound. 5 301-29 2004 Inverse Problems 20 259-82) for inverse obstacle problems. The optimization is constrained by (the reservoir model) a nonlinear large-scale system of PDEs that describes the reservoir dynamics. We reformulate this reservoir model in a weak (integral) form whose shape derivative can be formally computed from standard results of shape calculus. At each iteration of the scheme, the current estimate of the shape derivative is utilized to define a velocity in the level-set equation. The proper selection of this velocity ensures that the new shape decreases the cost functional. We present results of facies identification where the velocity is computed with the gradient-based (GB) approach of Burger (2002) and the Levenberg-Marquardt (LM) technique of Burger (2004). While an adjoint formulation allows the straightforward application of the GB approach, the LM technique requires the computation of the large-scale Karush-Kuhn-Tucker system that arises at each iteration of the scheme. We efficiently solve this system by means of the representer method. We present some synthetic experiments to show and compare the capabilities and limitations of the proposed implementations of level-set techniques for the identification of geologic facies.

  12. Level-set techniques for facies identification in reservoir modeling

    International Nuclear Information System (INIS)

    Iglesias, Marco A; McLaughlin, Dennis

    2011-01-01

    In this paper we investigate the application of level-set techniques for facies identification in reservoir models. The identification of facies is a geometrical inverse ill-posed problem that we formulate in terms of shape optimization. The goal is to find a region (a geologic facies) that minimizes the misfit between predicted and measured data from an oil–water reservoir. In order to address the shape optimization problem, we present a novel application of the level-set iterative framework developed by Burger in (2002 Interfaces Free Bound. 5 301–29; 2004 Inverse Problems 20 259–82) for inverse obstacle problems. The optimization is constrained by (the reservoir model) a nonlinear large-scale system of PDEs that describes the reservoir dynamics. We reformulate this reservoir model in a weak (integral) form whose shape derivative can be formally computed from standard results of shape calculus. At each iteration of the scheme, the current estimate of the shape derivative is utilized to define a velocity in the level-set equation. The proper selection of this velocity ensures that the new shape decreases the cost functional. We present results of facies identification where the velocity is computed with the gradient-based (GB) approach of Burger (2002) and the Levenberg–Marquardt (LM) technique of Burger (2004). While an adjoint formulation allows the straightforward application of the GB approach, the LM technique requires the computation of the large-scale Karush–Kuhn–Tucker system that arises at each iteration of the scheme. We efficiently solve this system by means of the representer method. We present some synthetic experiments to show and compare the capabilities and limitations of the proposed implementations of level-set techniques for the identification of geologic facies

  13. Level Set Approach to Anisotropic Wet Etching of Silicon

    Directory of Open Access Journals (Sweden)

    Branislav Radjenović

    2010-05-01

    Full Text Available In this paper a methodology for the three dimensional (3D modeling and simulation of the profile evolution during anisotropic wet etching of silicon based on the level set method is presented. Etching rate anisotropy in silicon is modeled taking into account full silicon symmetry properties, by means of the interpolation technique using experimentally obtained values for the etching rates along thirteen principal and high index directions in KOH solutions. The resulting level set equations are solved using an open source implementation of the sparse field method (ITK library, developed in medical image processing community, extended for the case of non-convex Hamiltonians. Simulation results for some interesting initial 3D shapes, as well as some more practical examples illustrating anisotropic etching simulation in the presence of masks (simple square aperture mask, convex corner undercutting and convex corner compensation, formation of suspended structures are shown also. The obtained results show that level set method can be used as an effective tool for wet etching process modeling, and that is a viable alternative to the Cellular Automata method which now prevails in the simulations of the wet etching process.

  14. Reevaluation of steam generator level trip set point

    Energy Technology Data Exchange (ETDEWEB)

    Shim, Yoon Sub; Soh, Dong Sub; Kim, Sung Oh; Jung, Se Won; Sung, Kang Sik; Lee, Joon [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    1994-06-01

    The reactor trip by the low level of steam generator water accounts for a substantial portion of reactor scrams in a nuclear plant and the feasibility of modification of the steam generator water level trip system of YGN 1/2 was evaluated in this study. The study revealed removal of the reactor trip function from the SG water level trip system is not possible because of plant safety but relaxation of the trip set point by 9 % is feasible. The set point relaxation requires drilling of new holes for level measurement to operating steam generators. Characteristics of negative neutron flux rate trip and reactor trip were also reviewed as an additional work. Since the purpose of the trip system modification for reduction of a reactor scram frequency is not to satisfy legal requirements but to improve plant performance and the modification yields positive and negative aspects, the decision of actual modification needs to be made based on the results of this study and also the policy of a plant owner. 37 figs, 6 tabs, 14 refs. (Author).

  15. Local Matrix Metalloproteinase 9 Level Determines Early Clinical Presentation of ST-Segment-Elevation Myocardial Infarction.

    Science.gov (United States)

    Nishiguchi, Tsuyoshi; Tanaka, Atsushi; Taruya, Akira; Emori, Hiroki; Ozaki, Yuichi; Orii, Makoto; Shiono, Yasutsugu; Shimamura, Kunihiro; Kameyama, Takeyoshi; Yamano, Takashi; Yamaguchi, Tomoyuki; Matsuo, Yoshiki; Ino, Yasushi; Kubo, Takashi; Hozumi, Takeshi; Hayashi, Yasushi; Akasaka, Takashi

    2016-12-01

    Early clinical presentation of ST-segment-elevation myocardial infarction (STEMI) and non-ST-segment-elevation myocardial infarction affects patient management. Although local inflammatory activities are involved in the onset of MI, little is known about their impact on early clinical presentation. This study aimed to investigate whether local inflammatory activities affect early clinical presentation. This study comprised 94 and 17 patients with MI (STEMI, 69; non-STEMI, 25) and stable angina pectoris, respectively. We simultaneously investigated the culprit lesion morphologies using optical coherence tomography and inflammatory activities assessed by shedding matrix metalloproteinase 9 (MMP-9) and myeloperoxidase into the coronary circulation before and after stenting. Prevalence of plaque rupture, thin-cap fibroatheroma, and lipid arc or macrophage count was higher in patients with STEMI and non-STEMI than in those with stable angina pectoris. Red thrombus was frequently observed in STEMI compared with others. Local MMP-9 levels were significantly higher than systemic levels (systemic, 42.0 [27.9-73.2] ng/mL versus prestent local, 69.1 [32.2-152.3] ng/mL versus poststent local, 68.0 [35.6-133.3] ng/mL; Pclinical presentation in patients with MI. Local inflammatory activity for atherosclerosis needs increased attention. © 2016 American Heart Association, Inc.

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

    International Nuclear Information System (INIS)

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

    2015-01-01

    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

  17. 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.

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

    Science.gov (United States)

    Mo, Jianqiang; Zhang, Wen; Zhong, Dongyan; Xu, Hao; Wang, Lan; Yu, Jia; Luo, Zongping

    2016-01-01

    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.

  19. Simultaneous reconstruction, segmentation, and edge enhancement of relatively piecewise continuous images with intensity-level information

    International Nuclear Information System (INIS)

    Liang, Z.; Jaszczak, R.; Coleman, R.; Johnson, V.

    1991-01-01

    A multinomial image model is proposed which uses intensity-level information for reconstruction of contiguous image regions. The intensity-level information assumes that image intensities are relatively constant within contiguous regions over the image-pixel array and that intensity levels of these regions are determined either empirically or theoretically by information criteria. These conditions may be valid, for example, for cardiac blood-pool imaging, where the intensity levels (or radionuclide activities) of myocardium, blood-pool, and background regions are distinct and the activities within each region of muscle, blood, or background are relatively uniform. To test the model, a mathematical phantom over a 64x64 array was constructed. The phantom had three contiguous regions. Each region had a different intensity level. Measurements from the phantom were simulated using an emission-tomography geometry. Fifty projections were generated over 180 degree, with 64 equally spaced parallel rays per projection. Projection data were randomized to contain Poisson noise. Image reconstructions were performed using an iterative maximum a posteriori probability procedure. The contiguous regions corresponding to the three intensity levels were automatically segmented. Simultaneously, the edges of the regions were sharpened. Noise in the reconstructed images was significantly suppressed. Convergence of the iterative procedure to the phantom was observed. Compared with maximum likelihood and filtered-backprojection approaches, the results obtained using the maximum a posteriori probability with the intensity-level information demonstrated qualitative and quantitative improvement in localizing the regions of varying intensities

  20. 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.

  1. A level set method for cupping artifact correction in cone-beam CT

    International Nuclear Information System (INIS)

    Xie, Shipeng; Li, Haibo; Ge, Qi; Li, Chunming

    2015-01-01

    Purpose: To reduce cupping artifacts and improve the contrast-to-noise ratio in cone-beam computed tomography (CBCT). Methods: A level set method is proposed to reduce cupping artifacts in the reconstructed image of CBCT. The authors derive a local intensity clustering property of the CBCT image and define a local clustering criterion function of the image intensities in a neighborhood of each point. This criterion function defines an energy in terms of the level set functions, which represent a segmentation result and the cupping artifacts. The cupping artifacts are estimated as a result of minimizing this energy. Results: The cupping artifacts in CBCT are reduced by an average of 90%. The results indicate that the level set-based algorithm is practical and effective for reducing the cupping artifacts and preserving the quality of the reconstructed image. Conclusions: The proposed method focuses on the reconstructed image without requiring any additional physical equipment, is easily implemented, and provides cupping correction through a single-scan acquisition. The experimental results demonstrate that the proposed method successfully reduces the cupping artifacts

  2. Automated species-level identification and segmentation of planktonic foraminifera using convolutional neural networks

    Science.gov (United States)

    Marchitto, T. M., Jr.; Mitra, R.; Zhong, B.; Ge, Q.; Kanakiya, B.; Lobaton, E.

    2017-12-01

    Identification and picking of foraminifera from sediment samples is often a laborious and repetitive task. Previous attempts to automate this process have met with limited success, but we show that recent advances in machine learning can be brought to bear on the problem. As a `proof of concept' we have developed a system that is capable of recognizing six species of extant planktonic foraminifera that are commonly used in paleoceanographic studies. Our pipeline begins with digital photographs taken under 16 different illuminations using an LED ring, which are then fused into a single 3D image. Labeled image sets were used to train various types of image classification algorithms, and performance on unlabeled image sets was measured in terms of precision (whether IDs are correct) and recall (what fraction of the target species are found). We find that Convolutional Neural Network (CNN) approaches achieve precision and recall values between 80 and 90%, which is similar precision and better recall than human expert performance using the same type of photographs. We have also trained a CNN to segment the 3D images into individual chambers and apertures, which can not only improve identification performance but also automate the measurement of foraminifera for morphometric studies. Given that there are only 35 species of extant planktonic foraminifera larger than 150 μm, we suggest that a fully automated characterization of this assemblage is attainable. This is the first step toward the realization of a foram picking robot.

  3. Surface-to-surface registration using level sets

    DEFF Research Database (Denmark)

    Hansen, Mads Fogtmann; Erbou, Søren G.; Vester-Christensen, Martin

    2007-01-01

    This paper presents a general approach for surface-to-surface registration (S2SR) with the Euclidean metric using signed distance maps. In addition, the method is symmetric such that the registration of a shape A to a shape B is identical to the registration of the shape B to the shape A. The S2SR...... problem can be approximated by the image registration (IR) problem of the signed distance maps (SDMs) of the surfaces confined to some narrow band. By shrinking the narrow bands around the zero level sets the solution to the IR problem converges towards the S2SR problem. It is our hypothesis...... that this approach is more robust and less prone to fall into local minima than ordinary surface-to-surface registration. The IR problem is solved using the inverse compositional algorithm. In this paper, a set of 40 pelvic bones of Duroc pigs are registered to each other w.r.t. the Euclidean transformation...

  4. THE EFFECT OF REVENUE AND MARKET SEGMENTATION LEVEL TOWARDS VENTURE CAPITAL INVESTMENT IN MOBILE APPLICATION BUSINESS

    Directory of Open Access Journals (Sweden)

    Dennis Adrian

    2014-05-01

    Full Text Available The development of mobile applications has mushroomed in local and foreign industries. This provides a tremendous opportunity for developers. For technopreneur developer, the capital to run the business is one of the biggest problems despite the fact that they may have great competence in the field. The fact that the business has big potential market in Indonesia has invited investors from local and overseas to invest as venture capital. However, due to the lack of knowledge on building collaboration with the investors and on understanding the market and investor needs in a long term, the developer finds difficulties to grow its business and to compete with bigger competitors. The research intends to seek the influence in selecting the level of revenue and market segmentation to support the investment decisions in the business of mobile applications, so that the mobile application developer is able to monetize their business to attract investors to invest in the venture capital.

  5. 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.

  6. IL-33 circulating serum levels are increased in patients with non-segmental generalized vitiligo.

    Science.gov (United States)

    Vaccaro, Mario; Cicero, Francesca; Mannucci, Carmen; Calapai, Gioacchino; Spatari, Giovanna; Barbuzza, Olga; Cannavò, Serafinella P; Gangemi, Sebastiano

    2016-09-01

    IL-33 is a recently identified cytokine, encoded by the IL-33 gene, which is a member of the IL-1 family that drives the production of T-helper-2 (Th-2)-associated cytokines. Serum levels of IL-33 have been reported to be up-regulated in various T-helper (Th)-1/Th-17-mediated diseases, such as psoriasis, rheumatoid arthritis, and inflammatory bowel. To investigate whether cytokine imbalance plays a role in the pathogenesis of vitiligo, we performed a case-control association study by enzyme-linked immunosorbent assay of IL-33 in our patients. IL-33 serum levels were measured by a quantitative enzyme immunoassay technique in patients with non-segmental generalized vitiligo and compared with those of healthy controls. IL-33 serum levels in patients with vitiligo were significantly increased than those in healthy controls. There was a positive correlation of IL-33 serum levels with extension of vitiligo and disease activity. This study suggests a possible systemic role of IL-33 in the pathogenesis of vitiligo. Inhibiting IL-33 activity might be a novel therapeutic strategy in the treatment of autoimmune inflammatory disease, like vitiligo.

  7. Fluoroscopy in paediatric fractures - Setting a local diagnostic reference level

    International Nuclear Information System (INIS)

    Pillai, A.; McAuley, A.; McMurray, K.; Jain, M.

    2006-01-01

    Background: The ionizing radiations (Medical Exposure) Regulation 2000 has made it mandatory to establish diagnostic reference levels (DRLs) for all typical radiological examinations. Objectives: We attempt to provide dose data for some common fluoroscopic procedures used in orthopaedic trauma that may be used as the basis for setting DRLs for paediatric patients. Materials and methods: The dose area product (DAP) in 865 paediatric trauma examinations was analysed. Median DAP values and screening times for each procedure type along with quartile values for each range are presented. Results: In the upper limb, elbow examinations had maximum exposure with a median DAP value of 1.21 cGy cm 2 . Median DAP values for forearm and wrist examinations were 0.708 and 0.538 cGy cm 2 , respectively. In lower limb, tibia and fibula examinations had a median DAP value of 3.23 cGy cm 2 followed by ankle examinations with a median DAP of 3.10 cGy cm 2 . The rounded third quartile DAP value for each distribution can be used as a provisional DRL for the specific procedure type. (authors)

  8. An objective method to optimize the MR sequence set for plaque classification in carotid vessel wall images using automated image segmentation.

    Directory of Open Access Journals (Sweden)

    Ronald van 't Klooster

    Full Text Available A typical MR imaging protocol to study the status of atherosclerosis in the carotid artery consists of the application of multiple MR sequences. Since scanner time is limited, a balance has to be reached between the duration of the applied MR protocol and the quantity and quality of the resulting images which are needed to assess the disease. In this study an objective method to optimize the MR sequence set for classification of soft plaque in vessel wall images of the carotid artery using automated image segmentation was developed. The automated method employs statistical pattern recognition techniques and was developed based on an extensive set of MR contrast weightings and corresponding manual segmentations of the vessel wall and soft plaque components, which were validated by histological sections. Evaluation of the results from nine contrast weightings showed the tradeoff between scan duration and automated image segmentation performance. For our dataset the best segmentation performance was achieved by selecting five contrast weightings. Similar performance was achieved with a set of three contrast weightings, which resulted in a reduction of scan time by more than 60%. The presented approach can help others to optimize MR imaging protocols by investigating the tradeoff between scan duration and automated image segmentation performance possibly leading to shorter scanning times and better image interpretation. This approach can potentially also be applied to other research fields focusing on different diseases and anatomical regions.

  9. On the Relationship between Variational Level Set-Based and SOM-Based Active Contours

    Science.gov (United States)

    Abdelsamea, Mohammed M.; Gnecco, Giorgio; Gaber, Mohamed Medhat; Elyan, Eyad

    2015-01-01

    Most Active Contour Models (ACMs) deal with the image segmentation problem as a functional optimization problem, as they work on dividing an image into several regions by optimizing a suitable functional. Among ACMs, variational level set methods have been used to build an active contour with the aim of modeling arbitrarily complex shapes. Moreover, they can handle also topological changes of the contours. Self-Organizing Maps (SOMs) have attracted the attention of many computer vision scientists, particularly in modeling an active contour based on the idea of utilizing the prototypes (weights) of a SOM to control the evolution of the contour. SOM-based models have been proposed in general with the aim of exploiting the specific ability of SOMs to learn the edge-map information via their topology preservation property and overcoming some drawbacks of other ACMs, such as trapping into local minima of the image energy functional to be minimized in such models. In this survey, we illustrate the main concepts of variational level set-based ACMs, SOM-based ACMs, and their relationship and review in a comprehensive fashion the development of their state-of-the-art models from a machine learning perspective, with a focus on their strengths and weaknesses. PMID:25960736

  10. The effects of creep and recovery on the in vitro biomechanical characteristics of human multi-level thoracolumbar spinal segments.

    Science.gov (United States)

    Busscher, Iris; van Dieën, Jaap H; van der Veen, Albert J; Kingma, Idsart; Meijer, Gerdine J M; Verkerke, Gijsbertus J; Veldhuizen, Albert G

    2011-06-01

    Several physiological and pathological conditions in daily life cause sustained static bending or torsion loads on the spine resulting in creep of spinal segments. The objective of this study was to determine the effects of creep and recovery on the range of motion, neutral zone, and neutral zone stiffness of thoracolumbar multi-level spinal segments in flexion, extension, lateral bending and axial rotation. Six human cadaveric spines (age at time of death 55-84 years) were sectioned in T1-T4, T5-T8, T9-T12, and L1-L4 segments and prepared for testing. Moments were applied of +4 to -4 N m in flexion-extension, lateral bending, and axial rotation. This was repeated after 30 min of creep loading at 2 N m in the tested direction and after 30 min of recovery. Displacement of individual motion segments was measured using a 3D optical movement registration system. The range of motion, neutral zone, and neutral zone stiffness of the middle motion segments were calculated from the moment-angular displacement data. The range of motion increased significantly after creep in extension, lateral bending and axial rotation (Pcreep showed an increasing trend as well, and the neutral zone after flexion creep increased by on average 36% (Pcreep in axial rotation (Pcreep loading. This higher flexibility of the spinal segments may be a risk factor for potential spinal instability or injury. Copyright © 2010 Elsevier Ltd. All rights reserved.

  11. Topology optimization of hyperelastic structures using a level set method

    Science.gov (United States)

    Chen, Feifei; Wang, Yiqiang; Wang, Michael Yu; Zhang, Y. F.

    2017-12-01

    Soft rubberlike materials, due to their inherent compliance, are finding widespread implementation in a variety of applications ranging from assistive wearable technologies to soft material robots. Structural design of such soft and rubbery materials necessitates the consideration of large nonlinear deformations and hyperelastic material models to accurately predict their mechanical behaviour. In this paper, we present an effective level set-based topology optimization method for the design of hyperelastic structures that undergo large deformations. The method incorporates both geometric and material nonlinearities where the strain and stress measures are defined within the total Lagrange framework and the hyperelasticity is characterized by the widely-adopted Mooney-Rivlin material model. A shape sensitivity analysis is carried out, in the strict sense of the material derivative, where the high-order terms involving the displacement gradient are retained to ensure the descent direction. As the design velocity enters into the shape derivative in terms of its gradient and divergence terms, we develop a discrete velocity selection strategy. The whole optimization implementation undergoes a two-step process, where the linear optimization is first performed and its optimized solution serves as the initial design for the subsequent nonlinear optimization. It turns out that this operation could efficiently alleviate the numerical instability and facilitate the optimization process. To demonstrate the validity and effectiveness of the proposed method, three compliance minimization problems are studied and their optimized solutions present significant mechanical benefits of incorporating the nonlinearities, in terms of remarkable enhancement in not only the structural stiffness but also the critical buckling load.

  12. 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.

  13. 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...

  14. Adaptable Value-Set Analysis for Low-Level Code

    OpenAIRE

    Brauer, Jörg; Hansen, René Rydhof; Kowalewski, Stefan; Larsen, Kim G.; Olesen, Mads Chr.

    2012-01-01

    This paper presents a framework for binary code analysis that uses only SAT-based algorithms. Within the framework, incremental SAT solving is used to perform a form of weakly relational value-set analysis in a novel way, connecting the expressiveness of the value sets to computational complexity. Another key feature of our framework is that it translates the semantics of binary code into an intermediate representation. This allows for a straightforward translation of the program semantics in...

  15. Goal oriented Mathematics Survey at Preparatory Level- Revised set ...

    African Journals Online (AJOL)

    This cross sectional study design on mathematical syllabi at preparatory levels of the high schools was to investigate the efficiency of the subject at preparatory level education serving as a basis for several streams, like Natural science, Technology, Computer Science, Health Science and Agriculture found at tertiary levels.

  16. GPU accelerated edge-region based level set evolution constrained by 2D gray-scale histogram.

    Science.gov (United States)

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

    2013-07-01

    Due to its intrinsic nature which allows to easily handle complex shapes and topological changes, the level set method (LSM) has been widely used in image segmentation. Nevertheless, LSM is computationally expensive, which limits its applications in real-time systems. For this purpose, we propose a new level set algorithm, which uses simultaneously edge, region, and 2D histogram information in order to efficiently segment objects of interest in a given scene. The computational complexity of the proposed LSM is greatly reduced by using the highly parallelizable lattice Boltzmann method (LBM) with a body force to solve the level set equation (LSE). The body force is the link with image data and is defined from the proposed LSE. The proposed LSM is then implemented using an NVIDIA graphics processing units to fully take advantage of the LBM local nature. The new algorithm is effective, robust against noise, independent to the initial contour, fast, and highly parallelizable. The edge and region information enable to detect objects with and without edges, and the 2D histogram information enable the effectiveness of the method in a noisy environment. Experimental results on synthetic and real images demonstrate subjectively and objectively the performance of the proposed method.

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

    International Nuclear Information System (INIS)

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

    2010-01-01

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

  18. Fast automatic 3D liver segmentation based on a three-level AdaBoost-guided active shape model

    Energy Technology Data Exchange (ETDEWEB)

    He, Baochun; Huang, Cheng; Zhou, Shoujun; Hu, Qingmao; Jia, Fucang, E-mail: fc.jia@siat.ac.cn [Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055 (China); Sharp, Gregory [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts 02114 (United States); Fang, Chihua; Fan, Yingfang [Department of Hepatology (I), Zhujiang Hospital, Southern Medical University, Guangzhou 510280 (China)

    2016-05-15

    Purpose: A robust, automatic, and rapid method for liver delineation is urgently needed for the diagnosis and treatment of liver disorders. Until now, the high variability in liver shape, local image artifacts, and the presence of tumors have complicated the development of automatic 3D liver segmentation. In this study, an automatic three-level AdaBoost-guided active shape model (ASM) is proposed for the segmentation of the liver based on enhanced computed tomography images in a robust and fast manner, with an emphasis on the detection of tumors. Methods: The AdaBoost voxel classifier and AdaBoost profile classifier were used to automatically guide three-level active shape modeling. In the first level of model initialization, fast automatic liver segmentation by an AdaBoost voxel classifier method is proposed. A shape model is then initialized by registration with the resulting rough segmentation. In the second level of active shape model fitting, a prior model based on the two-class AdaBoost profile classifier is proposed to identify the optimal surface. In the third level, a deformable simplex mesh with profile probability and curvature constraint as the external force is used to refine the shape fitting result. In total, three registration methods—3D similarity registration, probability atlas B-spline, and their proposed deformable closest point registration—are used to establish shape correspondence. Results: The proposed method was evaluated using three public challenge datasets: 3Dircadb1, SLIVER07, and Visceral Anatomy3. The results showed that our approach performs with promising efficiency, with an average of 35 s, and accuracy, with an average Dice similarity coefficient (DSC) of 0.94 ± 0.02, 0.96 ± 0.01, and 0.94 ± 0.02 for the 3Dircadb1, SLIVER07, and Anatomy3 training datasets, respectively. The DSC of the SLIVER07 testing and Anatomy3 unseen testing datasets were 0.964 and 0.933, respectively. Conclusions: The proposed automatic approach

  19. Fast automatic 3D liver segmentation based on a three-level AdaBoost-guided active shape model.

    Science.gov (United States)

    He, Baochun; Huang, Cheng; Sharp, Gregory; Zhou, Shoujun; Hu, Qingmao; Fang, Chihua; Fan, Yingfang; Jia, Fucang

    2016-05-01

    A robust, automatic, and rapid method for liver delineation is urgently needed for the diagnosis and treatment of liver disorders. Until now, the high variability in liver shape, local image artifacts, and the presence of tumors have complicated the development of automatic 3D liver segmentation. In this study, an automatic three-level AdaBoost-guided active shape model (ASM) is proposed for the segmentation of the liver based on enhanced computed tomography images in a robust and fast manner, with an emphasis on the detection of tumors. The AdaBoost voxel classifier and AdaBoost profile classifier were used to automatically guide three-level active shape modeling. In the first level of model initialization, fast automatic liver segmentation by an AdaBoost voxel classifier method is proposed. A shape model is then initialized by registration with the resulting rough segmentation. In the second level of active shape model fitting, a prior model based on the two-class AdaBoost profile classifier is proposed to identify the optimal surface. In the third level, a deformable simplex mesh with profile probability and curvature constraint as the external force is used to refine the shape fitting result. In total, three registration methods-3D similarity registration, probability atlas B-spline, and their proposed deformable closest point registration-are used to establish shape correspondence. The proposed method was evaluated using three public challenge datasets: 3Dircadb1, SLIVER07, and Visceral Anatomy3. The results showed that our approach performs with promising efficiency, with an average of 35 s, and accuracy, with an average Dice similarity coefficient (DSC) of 0.94 ± 0.02, 0.96 ± 0.01, and 0.94 ± 0.02 for the 3Dircadb1, SLIVER07, and Anatomy3 training datasets, respectively. The DSC of the SLIVER07 testing and Anatomy3 unseen testing datasets were 0.964 and 0.933, respectively. The proposed automatic approach achieves robust, accurate, and fast liver

  20. 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.

  1. 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.

  2. 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.

  3. Behaviour of culinary tourists: A segmentation study of diners at top-level restaurants

    Directory of Open Access Journals (Sweden)

    Natalia Daries

    2018-04-01

    Added value: The present research focuses on the study of the behaviour of the culinary tourist in an increasingly popular type of tourism with high added value. Culinary tourism is also enormously important in the economy of the destination and for territorial development.  Therefore, this work may be of interest both for public authorities and the managers of this type of restaurant, and to create synergies between the two. This work comes to fill a gap in the literature of segmentation in the restoration, since there are few research that focus on segmentation according to consumer's motivations and perceptions, and none focus on its relationship to tourism at the destination.

  4. Fully Automated Segmentation of Fluid/Cyst Regions in Optical Coherence Tomography Images With Diabetic Macular Edema Using Neutrosophic Sets and Graph Algorithms.

    Science.gov (United States)

    Rashno, Abdolreza; Koozekanani, Dara D; Drayna, Paul M; Nazari, Behzad; Sadri, Saeed; Rabbani, Hossein; Parhi, Keshab K

    2018-05-01

    This paper presents a fully automated algorithm to segment fluid-associated (fluid-filled) and cyst regions in optical coherence tomography (OCT) retina images of subjects with diabetic macular edema. The OCT image is segmented using a novel neutrosophic transformation and a graph-based shortest path method. In neutrosophic domain, an image is transformed into three sets: (true), (indeterminate) that represents noise, and (false). This paper makes four key contributions. First, a new method is introduced to compute the indeterminacy set , and a new -correction operation is introduced to compute the set in neutrosophic domain. Second, a graph shortest-path method is applied in neutrosophic domain to segment the inner limiting membrane and the retinal pigment epithelium as regions of interest (ROI) and outer plexiform layer and inner segment myeloid as middle layers using a novel definition of the edge weights . Third, a new cost function for cluster-based fluid/cyst segmentation in ROI is presented which also includes a novel approach in estimating the number of clusters in an automated manner. Fourth, the final fluid regions are achieved by ignoring very small regions and the regions between middle layers. The proposed method is evaluated using two publicly available datasets: Duke, Optima, and a third local dataset from the UMN clinic which is available online. The proposed algorithm outperforms the previously proposed Duke algorithm by 8% with respect to the dice coefficient and by 5% with respect to precision on the Duke dataset, while achieving about the same sensitivity. Also, the proposed algorithm outperforms a prior method for Optima dataset by 6%, 22%, and 23% with respect to the dice coefficient, sensitivity, and precision, respectively. Finally, the proposed algorithm also achieves sensitivity of 67.3%, 88.8%, and 76.7%, for the Duke, Optima, and the university of minnesota (UMN) datasets, respectively.

  5. 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.

  6. 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…

  7. 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...... 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....

  8. 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.)

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

    International Nuclear Information System (INIS)

    Bryant, Mark; Kauczor, Hans-Ulrich; Ley, Sebastian; Eberhardt, Ralf; Herth, Felix; Menezes, Ravi; Sedlaczek, Oliver; Ley-Zaporozhan, Julia

    2015-01-01

    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.)

  10. The Effect of Explicit and Implicit Corrective Feedback on Segmental Word-Level Pronunciation Errors

    Directory of Open Access Journals (Sweden)

    Mohammad Zohrabi

    2017-04-01

    Full Text Available Over the last few years, the realm of foreign language learning has witnessed an abundance of research concerning the effectiveness of corrective feedback on the acquisition of grammatical features, with the study of other target language subsystems, such as pronunciation, being few and far between. In order to bridge this gap, the present study intended to investigate and compare the immediate and delayed effect of explicit (overt and implicit (covert corrective feedback (CF on treating segmental word-level pronunciation errors committed by adult EFL learners of an institute in Tabriz named ALC. To this end, through a quasi-experimental study and random sampling, three groups were formed, an explicit, an implicit and a control group, each consisting of 20 low proficient EFL learners. Besides, considering the levels that learners were assigned to, based on the institute’s criteria, a Preliminary English Test (PET was administered in order to determine the proficiency level of learners. Having administered the pretest before treatment, to measure the longer-term effect of explicit vs. implicit CF on segmental word-level pronunciation errors, the study included delayed posttests in addition to immediate posttests all of which included reading passages containing 40 problematic words. The collected data were analyzed by ANCOVA and the obtained findings revealed that both explicit and implicit corrective feedback are effective in reducing pronunciation errors showing significant differences between experimental and control groups. Additionally, the outcomes showed that immediate implicit and immediate explicit corrective feedback have similar effects on reduction of pronunciation errors. The same result comes up regarding the delayed effect of explicit feedback in comparison with delayed effect of implicit feedback. However, the delayed effect of explicit and implicit CF lowered comparing to their immediate effect due to time effect. Pedagogically

  11. High-level waste tank farm set point document

    International Nuclear Information System (INIS)

    Anthony, J.A. III.

    1995-01-01

    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

  12. 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.

  13. 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.

  14. Multi-phase flow monitoring with electrical impedance tomography using level set based method

    International Nuclear Information System (INIS)

    Liu, Dong; Khambampati, Anil Kumar; Kim, Sin; Kim, Kyung Youn

    2015-01-01

    Highlights: • LSM has been used for shape reconstruction to monitor multi-phase flow using EIT. • Multi-phase level set model for conductivity is represented by two level set functions. • LSM handles topological merging and breaking naturally during evolution process. • To reduce the computational time, a narrowband technique was applied. • Use of narrowband and optimization approach results in efficient and fast method. - Abstract: In this paper, a level set-based reconstruction scheme is applied to multi-phase flow monitoring using electrical impedance tomography (EIT). The proposed scheme involves applying a narrowband level set method to solve the inverse problem of finding the interface between the regions having different conductivity values. The multi-phase level set model for the conductivity distribution inside the domain is represented by two level set functions. The key principle of the level set-based method is to implicitly represent the shape of interface as the zero level set of higher dimensional function and then solve a set of partial differential equations. The level set-based scheme handles topological merging and breaking naturally during the evolution process. It also offers several advantages compared to traditional pixel-based approach. Level set-based method for multi-phase flow is tested with numerical and experimental data. It is found that level set-based method has better reconstruction performance when compared to pixel-based method

  15. A Novel Approach for Bi-Level Segmentation of Tuberculosis Bacilli Based on Meta-Heuristic Algorithms

    Directory of Open Access Journals (Sweden)

    AYAS, S.

    2018-02-01

    Full Text Available Image thresholding is the most crucial step in microscopic image analysis to distinguish bacilli objects causing of tuberculosis disease. Therefore, several bi-level thresholding algorithms are widely used to increase the bacilli segmentation accuracy. However, bi-level microscopic image thresholding problem has not been solved using optimization algorithms. This paper introduces a novel approach for the segmentation problem using heuristic algorithms and presents visual and quantitative comparisons of heuristic and state-of-art thresholding algorithms. In this study, well-known heuristic algorithms such as Firefly Algorithm, Particle Swarm Optimization, Cuckoo Search, Flower Pollination are used to solve bi-level microscopic image thresholding problem, and the results are compared with the state-of-art thresholding algorithms such as K-Means, Fuzzy C-Means, Fast Marching. Kapur's entropy is chosen as the entropy measure to be maximized. Experiments are performed to make comparisons in terms of evaluation metrics and execution time. The quantitative results are calculated based on ground truth segmentation. According to the visual results, heuristic algorithms have better performance and the quantitative results are in accord with the visual results. Furthermore, experimental time comparisons show the superiority and effectiveness of the heuristic algorithms over traditional thresholding algorithms.

  16. Mind-sets, low-level exposures, and research

    International Nuclear Information System (INIS)

    Sagan, L.A.

    1993-01-01

    Much of our environmental policy is based on the notion that carcinogenic agents are harmful at even minuscule doses. From where does this thinking come? What is the scientific evidence that supports such policy? Moreover, why is the public willing to buy into this? Or is it the other way around: Has the scientific community bought into a paradigm that has its origins in public imagery? Or, most likely, are there interactions between the two? It is essential that we find out whether or not there are risks associated with low-level exposures to radiation. The author can see three obvious areas where the future depends on better information: The increasing radiation exposures resulting from the use of medical diagnostic and therapeutic practices need to be properly evaluated for safety; Environmental policies, which direct enormous resources to the reduction of small radiation exposures, needs to be put on a firmer scientific basis; The future of nuclear energy, dependent as it is on public acceptance, may well rely upon a better understanding of low-dose effects. Nuclear energy could provide an important solution of global warming and other possible environmental hazards, but will probably not be implemented as long as fear of low-dose radiation persists. Although an established paradigm has great resilience, it cannot resist the onslaught of inconsistent scientific observations or of the social value system that supports it. Only new research will enable us to determine if a paradigm shift is in order here

  17. Developing population segments with different levels of complexity and primary health care needs: An analysis using health administrative data in British Columbia, Canada

    Directory of Open Access Journals (Sweden)

    Julia Langton

    2017-04-01

    We developed population segments designed to account for patient complexity and primary health care needs; as such, segments provide more information than traditional indices of morbidity burden based on counts of chronic conditions. These segments will be used to report information on the quality of primary care. We plan to include conduct validation studies using additional variables (e.g, socio-economic factors, level of vulnerability from patient surveys so that segments more accurately represent the level of complexity and patients’ primary health care needs.

  18. Dynamic-thresholding level set: a novel computer-aided volumetry method for liver tumors in hepatic CT images

    Science.gov (United States)

    Cai, Wenli; Yoshida, Hiroyuki; Harris, Gordon J.

    2007-03-01

    Measurement of the volume of focal liver tumors, called liver tumor volumetry, is indispensable for assessing the growth of tumors and for monitoring the response of tumors to oncology treatments. Traditional edge models, such as the maximum gradient and zero-crossing methods, often fail to detect the accurate boundary of a fuzzy object such as a liver tumor. As a result, the computerized volumetry based on these edge models tends to differ from manual segmentation results performed by physicians. In this study, we developed a novel computerized volumetry method for fuzzy objects, called dynamic-thresholding level set (DT level set). An optimal threshold value computed from a histogram tends to shift, relative to the theoretical threshold value obtained from a normal distribution model, toward a smaller region in the histogram. We thus designed a mobile shell structure, called a propagating shell, which is a thick region encompassing the level set front. The optimal threshold calculated from the histogram of the shell drives the level set front toward the boundary of a liver tumor. When the volume ratio between the object and the background in the shell approaches one, the optimal threshold value best fits the theoretical threshold value and the shell stops propagating. Application of the DT level set to 26 hepatic CT cases with 63 biopsy-confirmed hepatocellular carcinomas (HCCs) and metastases showed that the computer measured volumes were highly correlated with those of tumors measured manually by physicians. Our preliminary results showed that DT level set was effective and accurate in estimating the volumes of liver tumors detected in hepatic CT images.

  19. Testing the robustness of best worst scaling for cross-national segmentation with different numbers of choice sets

    DEFF Research Database (Denmark)

    Mueller Loose, Simone; Lockshin, Larry

    2013-01-01

    The aim of the study is to showcase how cross-cultural research can take advantage of the measurement invariance of best-worst scales. The study utilises best-worst scaling (BWS) to assess the importance of environmental sustainability among other experience and credence product attributes...... for the purchase of wine across five countries. Three consumer segments with distinct product preferences were identified across all five countries, which differ in their relative size in each market. This case study demonstrates different analysis methods suitable for the analysis of BWS data on aggregated...

  20. 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.

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

    International Nuclear Information System (INIS)

    Ngo, Long Cu; Choi, Hyoung Gwon

    2016-01-01

    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

  2. Transport and diffusion of material quantities on propagating interfaces via level set methods

    CERN Document Server

    Adalsteinsson, D

    2003-01-01

    We develop theory and numerical algorithms to apply level set methods to problems involving the transport and diffusion of material quantities in a level set framework. Level set methods are computational techniques for tracking moving interfaces; they work by embedding the propagating interface as the zero level set of a higher dimensional function, and then approximate the solution of the resulting initial value partial differential equation using upwind finite difference schemes. The traditional level set method works in the trace space of the evolving interface, and hence disregards any parameterization in the interface description. Consequently, material quantities on the interface which themselves are transported under the interface motion are not easily handled in this framework. We develop model equations and algorithmic techniques to extend the level set method to include these problems. We demonstrate the accuracy of our approach through a series of test examples and convergence studies.

  3. Transport and diffusion of material quantities on propagating interfaces via level set methods

    International Nuclear Information System (INIS)

    Adalsteinsson, David; Sethian, J.A.

    2003-01-01

    We develop theory and numerical algorithms to apply level set methods to problems involving the transport and diffusion of material quantities in a level set framework. Level set methods are computational techniques for tracking moving interfaces; they work by embedding the propagating interface as the zero level set of a higher dimensional function, and then approximate the solution of the resulting initial value partial differential equation using upwind finite difference schemes. The traditional level set method works in the trace space of the evolving interface, and hence disregards any parameterization in the interface description. Consequently, material quantities on the interface which themselves are transported under the interface motion are not easily handled in this framework. We develop model equations and algorithmic techniques to extend the level set method to include these problems. We demonstrate the accuracy of our approach through a series of test examples and convergence studies

  4. 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.

  5. Road and Street Centerlines, Street-The data set is a line feature consisting of 13948 line segments representing streets. It was created to maintain the location of city and county based streets., Published in 1989, Davis County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Road and Street Centerlines dataset current as of 1989. Street-The data set is a line feature consisting of 13948 line segments representing streets. It was created...

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

    KAUST Repository

    Burger, Martin; Matevosyan, Norayr; Wolfram, Marie-Therese

    2011-01-01

    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

  7. A quantitative evaluation of pleural effusion on computed tomography scans using B-spline and local clustering level set.

    Science.gov (United States)

    Song, Lei; Gao, Jungang; Wang, Sheng; Hu, Huasi; Guo, Youmin

    2017-01-01

    Estimation of the pleural effusion's volume is an important clinical issue. The existing methods cannot assess it accurately when there is large volume of liquid in the pleural cavity and/or the patient has some other disease (e.g. pneumonia). In order to help solve this issue, the objective of this study is to develop and test a novel algorithm using B-spline and local clustering level set method jointly, namely BLL. The BLL algorithm was applied to a dataset involving 27 pleural effusions detected on chest CT examination of 18 adult patients with the presence of free pleural effusion. Study results showed that average volumes of pleural effusion computed using the BLL algorithm and assessed manually by the physicians were 586 ml±339 ml and 604±352 ml, respectively. For the same patient, the volume of the pleural effusion, segmented semi-automatically, was 101.8% ±4.6% of that was segmented manually. Dice similarity was found to be 0.917±0.031. The study demonstrated feasibility of applying the new BLL algorithm to accurately measure the volume of pleural effusion.

  8. AISLE: an automatic volumetric segmentation method for the study of lung allometry.

    Science.gov (United States)

    Ren, Hongliang; Kazanzides, Peter

    2011-01-01

    We developed a fully automatic segmentation method for volumetric CT (computer tomography) datasets to support construction of a statistical atlas for the study of allometric laws of the lung. The proposed segmentation method, AISLE (Automated ITK-Snap based on Level-set), is based on the level-set implementation from an existing semi-automatic segmentation program, ITK-Snap. AISLE can segment the lung field without human interaction and provide intermediate graphical results as desired. The preliminary experimental results show that the proposed method can achieve accurate segmentation, in terms of volumetric overlap metric, by comparing with the ground-truth segmentation performed by a radiologist.

  9. A level set approach for shock-induced α-γ phase transition of RDX

    Science.gov (United States)

    Josyula, Kartik; Rahul; De, Suvranu

    2018-02-01

    We present a thermodynamically consistent level sets approach based on regularization energy functional which can be directly incorporated into a Galerkin finite element framework to model interface motion. The regularization energy leads to a diffusive form of flux that is embedded within the level sets evolution equation which maintains the signed distance property of the level set function. The scheme is shown to compare well with the velocity extension method in capturing the interface position. The proposed level sets approach is employed to study the α-γphase transformation in RDX single crystal shocked along the (100) plane. Example problems in one and three dimensions are presented. We observe smooth evolution of the phase interface along the shock direction in both models. There is no diffusion of the interface during the zero level set evolution in the three dimensional model. The level sets approach is shown to capture the characteristics of the shock-induced α-γ phase transformation such as stress relaxation behind the phase interface and the finite time required for the phase transformation to complete. The regularization energy based level sets approach is efficient, robust, and easy to implement.

  10. Semiautomated hybrid algorithm for estimation of three-dimensional liver surface in CT using dynamic cellular automata and level-sets.

    Science.gov (United States)

    Dakua, Sarada Prasad; Abinahed, Julien; Al-Ansari, Abdulla

    2015-04-01

    Liver segmentation continues to remain a major challenge, largely due to its intense complexity with surrounding anatomical structures (stomach, kidney, and heart), high noise level and lack of contrast in pathological computed tomography (CT) data. We present an approach to reconstructing the liver surface in low contrast CT. The main contributions are: (1) a stochastic resonance-based methodology in discrete cosine transform domain is developed to enhance the contrast of pathological liver images, (2) a new formulation is proposed to prevent the object boundary, resulting from the cellular automata method, from leaking into the surrounding areas of similar intensity, and (3) a level-set method is suggested to generate intermediate segmentation contours from two segmented slices distantly located in a subject sequence. We have tested the algorithm on real datasets obtained from two sources, Hamad General Hospital and medical image computing and computer-assisted interventions grand challenge workshop. Various parameters in the algorithm, such as [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text], play imperative roles, thus their values are precisely selected. Both qualitative and quantitative evaluation performed on liver data show promising segmentation accuracy when compared with ground truth data reflecting the potential of the proposed method.

  11. Out-of-Core Computations of High-Resolution Level Sets by Means of Code Transformation

    DEFF Research Database (Denmark)

    Christensen, Brian Bunch; Nielsen, Michael Bang; Museth, Ken

    2012-01-01

    We propose a storage efficient, fast and parallelizable out-of-core framework for streaming computations of high resolution level sets. The fundamental techniques are skewing and tiling transformations of streamed level set computations which allow for the combination of interface propagation, re...... computations are now CPU bound and consequently the overall performance is unaffected by disk latency and bandwidth limitations. We demonstrate this with several benchmark tests that show sustained out-of-core throughputs close to that of in-core level set simulations....

  12. Behaviour of culinary tourists: A segmentation study of diners at top-level restaurants

    OpenAIRE

    Daries Ramón, Natalia; Cristobal-Fransi, Eduard; Ferrer-Rossell, Berta; Marine-Roig, Estela

    2018-01-01

    Purpose: The main aim of this research is to characterize the tourists visiting top-level restaurants to ascertain the profile of this type of customer, their behaviour and their influence on the destinations where they are located. Design/methodology: During the months of July to December 2016, a survey was conducted on a sample of 187 tourists who had visited Michelin-starred restaurants in order to highlight the most valued aspects during the process of choosing, consulting and booking the...

  13. 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.

  14. Track segment synthesis method for NTA film

    International Nuclear Information System (INIS)

    Kumazawa, Shigeru

    1980-03-01

    A method is presented for synthesizing track segments extracted from a gray-level digital picture of NTA film in automatic counting system. In order to detect each track in an arbitrary direction, even if it has some gaps, as a set of the track segments, the method links extracted segments along the track, in succession, to the linked track segments, according to whether each extracted segment bears a similarity of direction to the track or not and whether it is connected with the linked track segments or not. In the case of a large digital picture, the method is applied to each subpicture, which is a strip of the picture, and then concatenates subsets of track segments linked at each subpicture as a set of track segments belonging to a track. The method was applied to detecting tracks in various directions over the eight 364 x 40-pixel subpictures with the gray scale of 127/pixel (picture element) of the microphotograph of NTA film. It was proved to be able to synthesize track segments correctly for every track in the picture. (author)

  15. An accurate conservative level set/ghost fluid method for simulating turbulent atomization

    International Nuclear Information System (INIS)

    Desjardins, Olivier; Moureau, Vincent; Pitsch, Heinz

    2008-01-01

    This paper presents a novel methodology for simulating incompressible two-phase flows by combining an improved version of the conservative level set technique introduced in [E. Olsson, G. Kreiss, A conservative level set method for two phase flow, J. Comput. Phys. 210 (2005) 225-246] with a ghost fluid approach. By employing a hyperbolic tangent level set function that is transported and re-initialized using fully conservative numerical schemes, mass conservation issues that are known to affect level set methods are greatly reduced. In order to improve the accuracy of the conservative level set method, high order numerical schemes are used. The overall robustness of the numerical approach is increased by computing the interface normals from a signed distance function reconstructed from the hyperbolic tangent level set by a fast marching method. The convergence of the curvature calculation is ensured by using a least squares reconstruction. The ghost fluid technique provides a way of handling the interfacial forces and large density jumps associated with two-phase flows with good accuracy, while avoiding artificial spreading of the interface. Since the proposed approach relies on partial differential equations, its implementation is straightforward in all coordinate systems, and it benefits from high parallel efficiency. The robustness and efficiency of the approach is further improved by using implicit schemes for the interface transport and re-initialization equations, as well as for the momentum solver. The performance of the method is assessed through both classical level set transport tests and simple two-phase flow examples including topology changes. It is then applied to simulate turbulent atomization of a liquid Diesel jet at Re=3000. The conservation errors associated with the accurate conservative level set technique are shown to remain small even for this complex case

  16. A simple mass-conserved level set method for simulation of multiphase flows

    Science.gov (United States)

    Yuan, H.-Z.; Shu, C.; Wang, Y.; Shu, S.

    2018-04-01

    In this paper, a modified level set method is proposed for simulation of multiphase flows with large density ratio and high Reynolds number. The present method simply introduces a source or sink term into the level set equation to compensate the mass loss or offset the mass increase. The source or sink term is derived analytically by applying the mass conservation principle with the level set equation and the continuity equation of flow field. Since only a source term is introduced, the application of the present method is as simple as the original level set method, but it can guarantee the overall mass conservation. To validate the present method, the vortex flow problem is first considered. The simulation results are compared with those from the original level set method, which demonstrates that the modified level set method has the capability of accurately capturing the interface and keeping the mass conservation. Then, the proposed method is further validated by simulating the Laplace law, the merging of two bubbles, a bubble rising with high density ratio, and Rayleigh-Taylor instability with high Reynolds number. Numerical results show that the mass is a well-conserved by the present method.

  17. Evaluating healthcare priority setting at the meso level: A thematic review of empirical literature

    Science.gov (United States)

    Waithaka, Dennis; Tsofa, Benjamin; Barasa, Edwine

    2018-01-01

    Background: Decentralization of health systems has made sub-national/regional healthcare systems the backbone of healthcare delivery. These regions are tasked with the difficult responsibility of determining healthcare priorities and resource allocation amidst scarce resources. We aimed to review empirical literature that evaluated priority setting practice at the meso (sub-national) level of health systems. Methods: We systematically searched PubMed, ScienceDirect and Google scholar databases and supplemented these with manual searching for relevant studies, based on the reference list of selected papers. We only included empirical studies that described and evaluated, or those that only evaluated priority setting practice at the meso-level. A total of 16 papers were identified from LMICs and HICs. We analyzed data from the selected papers by thematic review. Results: Few studies used systematic priority setting processes, and all but one were from HICs. Both formal and informal criteria are used in priority-setting, however, informal criteria appear to be more perverse in LMICs compared to HICs. The priority setting process at the meso-level is a top-down approach with minimal involvement of the community. Accountability for reasonableness was the most common evaluative framework as it was used in 12 of the 16 studies. Efficiency, reallocation of resources and options for service delivery redesign were the most common outcome measures used to evaluate priority setting. Limitations: Our study was limited by the fact that there are very few empirical studies that have evaluated priority setting at the meso-level and there is likelihood that we did not capture all the studies. Conclusions: Improving priority setting practices at the meso level is crucial to strengthening health systems. This can be achieved through incorporating and adapting systematic priority setting processes and frameworks to the context where used, and making considerations of both process

  18. Interobserver-variability of lung nodule volumetry considering different segmentation algorithms and observer training levels

    International Nuclear Information System (INIS)

    Bolte, H.; Jahnke, T.; Schaefer, F.K.W.; Wenke, R.; Hoffmann, B.; Freitag-Wolf, S.; Dicken, V.; Kuhnigk, J.M.; Lohmann, J.; Voss, S.; Knoess, N.

    2007-01-01

    Objective: The aim of this study was to investigate the interobserver variability of CT based diameter and volumetric measurements of artificial pulmonary nodules. A special interest was the consideration of different measurement methods, observer experience and training levels. Materials and methods: For this purpose 46 artificial small solid nodules were examined in a dedicated ex-vivo chest phantom with multislice-spiral CT (20 mAs, 120 kV, collimation 16 mm x 0.75 mm, table feed 15 mm, reconstructed slice thickness 1 mm, reconstruction increment 0.7 mm, intermediate reconstruction kernel). Two observer groups of different radiologic experience (0 and more than 5 years of training, 3 observers each) analysed all lesions with digital callipers and 2 volumetry software packages (click-point depending and robust volumetry) in a semi-automatic and manually corrected mode. For data analysis the variation coefficient (VC) was calculated in per cent for each group and a Wilcoxon test was used for analytic statistics. Results: Click-point robust volumetry showed with a VC of <0.01% in both groups the smallest interobserver variability. Between experienced and un-experienced observers interobserver variability was significantly different for diameter measurements (p = 0.023) but not for semi-automatic and manual corrected volumetry. A significant training effect was revealed for diameter measurements (p = 0.003) and semi-automatic measurements of click-point depending volumetry (p = 0.007) in the un-experienced observer group. Conclusions: Compared to diameter measurements volumetry achieves a significantly smaller interobserver variance and advanced volumetry algorithms are independent of observer experience

  19. 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.

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

    Science.gov (United States)

    Barasa, Edwine W; Molyneux, Sassy; English, Mike; Cleary, Susan

    2015-09-16

    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. 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. 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. 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 these complementary schools of thought. © 2015

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

    Science.gov (United States)

    Barasa, Edwine W.; Molyneux, Sassy; English, Mike; Cleary, Susan

    2015-01-01

    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 these

  2. 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

  3. 76 FR 9004 - Public Comment on Setting Achievement Levels in Writing

    Science.gov (United States)

    2011-02-16

    ... DEPARTMENT OF EDUCATION Public Comment on Setting Achievement Levels in Writing AGENCY: U.S... Achievement Levels in Writing. SUMMARY: The National Assessment Governing Board (Governing Board) is... for NAEP in writing. This notice provides opportunity for public comment and submitting...

  4. Application of physiologically based pharmacokinetic modeling in setting acute exposure guideline levels for methylene chloride.

    NARCIS (Netherlands)

    Bos, Peter Martinus Jozef; Zeilmaker, Marco Jacob; Eijkeren, Jan Cornelis Henri van

    2006-01-01

    Acute exposure guideline levels (AEGLs) are derived to protect the human population from adverse health effects in case of single exposure due to an accidental release of chemicals into the atmosphere. AEGLs are set at three different levels of increasing toxicity for exposure durations ranging from

  5. Increased systemic and epidermal levels of IL-17A and IL-1β promotes progression of non-segmental vitiligo.

    Science.gov (United States)

    Bhardwaj, Supriya; Rani, Seema; Srivastava, Niharika; Kumar, Ravinder; Parsad, Davinder

    2017-03-01

    Non-segmental vitiligo (NSV) results from autoimmune destruction of melanocytes. The altered levels of various cytokines have been proposed in the pathogenesis of vitiligo. However, the exact immune mechanisms have not yet been fully elucidated. To investigate the role of epidermal and systemic cytokines in active and stable NSV patients. Serum levels of inflammatory cytokines were checked in 42 active and 30 stable NSV patients with 30 controls. The lesional, perilesional and normal skin sections were subjected to H&E staining. The mRNA expression of inflammatory cytokines and their respective receptors were assessed by quantitative PCR in lesional skin of both active and stable NSV skin. The MITF and IL-17A were immunolocalized in lesional, perilesional and normal skin tissue. Significant increase in the expression of inflammatory cytokines, IL-17A, IL-1β and TGF-β was observed in active patients, whereas no change was observed in stable patients. A marked reduction in epidermal thickness was observed in lesional skin sections. Significant increase in IL-17A and significant decrease in microphthalmia associated transcription factor (MITF) expression was observed in lesional and perilesional skin sections. Moreover, qPCR analysis showed significant alterations in the mRNA levels of IL-17A, IL-1β, IFN-γ, TGF-β and their respective receptors in active and stable vitiligo patient samples. Increased levels of IL-17A and IL-1β cytokines and decreased expression of MITF suggested a possible role of these cytokines in dysregulation of melanocytic activity in the lesional skin and hence might be responsible for the progression of active vitiligo. Copyright © 2016 Elsevier Ltd. All rights reserved.

  6. 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.

  7. Priority setting at the micro-, meso- and macro-levels in Canada, Norway and Uganda.

    Science.gov (United States)

    Kapiriri, Lydia; Norheim, Ole Frithjof; Martin, Douglas K

    2007-06-01

    The objectives of this study were (1) to describe the process of healthcare priority setting in Ontario-Canada, Norway and Uganda at the three levels of decision-making; (2) to evaluate the description using the framework for fair priority setting, accountability for reasonableness; so as to identify lessons of good practices. We carried out case studies involving key informant interviews, with 184 health practitioners and health planners from the macro-level, meso-level and micro-level from Canada-Ontario, Norway and Uganda (selected by virtue of their varying experiences in priority setting). Interviews were audio-recorded, transcribed and analyzed using a modified thematic approach. The descriptions were evaluated against the four conditions of "accountability for reasonableness", relevance, publicity, revisions and enforcement. Areas of adherence to these conditions were identified as lessons of good practices; areas of non-adherence were identified as opportunities for improvement. (i) at the macro-level, in all three countries, cabinet makes most of the macro-level resource allocation decisions and they are influenced by politics, public pressure, and advocacy. Decisions within the ministries of health are based on objective formulae and evidence. International priorities influenced decisions in Uganda. Some priority-setting reasons are publicized through circulars, printed documents and the Internet in Canada and Norway. At the meso-level, hospital priority-setting decisions were made by the hospital managers and were based on national priorities, guidelines, and evidence. Hospital departments that handle emergencies, such as surgery, were prioritized. Some of the reasons are available on the hospital intranet or presented at meetings. Micro-level practitioners considered medical and social worth criteria. These reasons are not publicized. Many practitioners lacked knowledge of the macro- and meso-level priority-setting processes. (ii) Evaluation

  8. Reconstruction of thin electromagnetic inclusions by a level-set method

    International Nuclear Information System (INIS)

    Park, Won-Kwang; Lesselier, Dominique

    2009-01-01

    In this contribution, we consider a technique of electromagnetic imaging (at a single, non-zero frequency) which uses the level-set evolution method for reconstructing a thin inclusion (possibly made of disconnected parts) with either dielectric or magnetic contrast with respect to the embedding homogeneous medium. Emphasis is on the proof of the concept, the scattering problem at hand being so far based on a two-dimensional scalar model. To do so, two level-set functions are employed; the first one describes location and shape, and the other one describes connectivity and length. Speeds of evolution of the level-set functions are calculated via the introduction of Fréchet derivatives of a least-square cost functional. Several numerical experiments on noiseless and noisy data as well illustrate how the proposed method behaves

  9. 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.

  10. 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.

  11. A parametric level-set approach for topology optimization of flow domains

    DEFF Research Database (Denmark)

    Pingen, Georg; Waidmann, Matthias; Evgrafov, Anton

    2010-01-01

    of the design variables in the traditional approaches is seen as a possible cause for the slow convergence. Non-smooth material distributions are suspected to trigger premature onset of instationary flows which cannot be treated by steady-state flow models. In the present work, we study whether the convergence...... and the versatility of topology optimization methods for fluidic systems can be improved by employing a parametric level-set description. In general, level-set methods allow controlling the smoothness of boundaries, yield a non-local influence of design variables, and decouple the material description from the flow...... field discretization. The parametric level-set method used in this study utilizes a material distribution approach to represent flow boundaries, resulting in a non-trivial mapping between design variables and local material properties. Using a hydrodynamic lattice Boltzmann method, we study...

  12. Setting-level influences on implementation of the responsive classroom approach.

    Science.gov (United States)

    Wanless, Shannon B; Patton, Christine L; Rimm-Kaufman, Sara E; Deutsch, Nancy L

    2013-02-01

    We used mixed methods to examine the association between setting-level factors and observed implementation of a social and emotional learning intervention (Responsive Classroom® approach; RC). In study 1 (N = 33 3rd grade teachers after the first year of RC implementation), we identified relevant setting-level factors and uncovered the mechanisms through which they related to implementation. In study 2 (N = 50 4th grade teachers after the second year of RC implementation), we validated our most salient Study 1 finding across multiple informants. Findings suggested that teachers perceived setting-level factors, particularly principal buy-in to the intervention and individualized coaching, as influential to their degree of implementation. Further, we found that intervention coaches' perspectives of principal buy-in were more related to implementation than principals' or teachers' perspectives. Findings extend the application of setting theory to the field of implementation science and suggest that interventionists may want to consider particular accounts of school setting factors before determining the likelihood of schools achieving high levels of implementation.

  13. Breast ultrasound image segmentation: an optimization approach based on super-pixels and high-level descriptors

    Science.gov (United States)

    Massich, Joan; Lemaître, Guillaume; Martí, Joan; Mériaudeau, Fabrice

    2015-04-01

    Breast cancer is the second most common cancer and the leading cause of cancer death among women. Medical imaging has become an indispensable tool for its diagnosis and follow up. During the last decade, the medical community has promoted to incorporate Ultra-Sound (US) screening as part of the standard routine. The main reason for using US imaging is its capability to differentiate benign from malignant masses, when compared to other imaging techniques. The increasing usage of US imaging encourages the development of Computer Aided Diagnosis (CAD) systems applied to Breast Ultra-Sound (BUS) images. However accurate delineations of the lesions and structures of the breast are essential for CAD systems in order to extract information needed to perform diagnosis. This article proposes a highly modular and flexible framework for segmenting lesions and tissues present in BUS images. The proposal takes advantage of optimization strategies using super-pixels and high-level descriptors, which are analogous to the visual cues used by radiologists. Qualitative and quantitative results are provided stating a performance within the range of the state-of-the-art.

  14. Reproducibility of F18-FDG PET radiomic features for different cervical tumor segmentation methods, gray-level discretization, and reconstruction algorithms.

    Science.gov (United States)

    Altazi, Baderaldeen A; Zhang, Geoffrey G; Fernandez, Daniel C; Montejo, Michael E; Hunt, Dylan; Werner, Joan; Biagioli, Matthew C; Moros, Eduardo G

    2017-11-01

    Site-specific investigations of the role of radiomics in cancer diagnosis and therapy are emerging. We evaluated the reproducibility of radiomic features extracted from 18 Flourine-fluorodeoxyglucose ( 18 F-FDG) PET images for three parameters: manual versus computer-aided segmentation methods, gray-level discretization, and PET image reconstruction algorithms. Our cohort consisted of pretreatment PET/CT scans from 88 cervical cancer patients. Two board-certified radiation oncologists manually segmented the metabolic tumor volume (MTV 1 and MTV 2 ) for each patient. For comparison, we used a graphical-based method to generate semiautomated segmented volumes (GBSV). To address any perturbations in radiomic feature values, we down-sampled the tumor volumes into three gray-levels: 32, 64, and 128 from the original gray-level of 256. Finally, we analyzed the effect on radiomic features on PET images of eight patients due to four PET 3D-reconstruction algorithms: maximum likelihood-ordered subset expectation maximization (OSEM) iterative reconstruction (IR) method, fourier rebinning-ML-OSEM (FOREIR), FORE-filtered back projection (FOREFBP), and 3D-Reprojection (3DRP) analytical method. We extracted 79 features from all segmentation method, gray-levels of down-sampled volumes, and PET reconstruction algorithms. The features were extracted using gray-level co-occurrence matrices (GLCM), gray-level size zone matrices (GLSZM), gray-level run-length matrices (GLRLM), neighborhood gray-tone difference matrices (NGTDM), shape-based features (SF), and intensity histogram features (IHF). We computed the Dice coefficient between each MTV and GBSV to measure segmentation accuracy. Coefficient values close to one indicate high agreement, and values close to zero indicate low agreement. We evaluated the effect on radiomic features by calculating the mean percentage differences (d¯) between feature values measured from each pair of parameter elements (i.e. segmentation methods: MTV

  15. 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. © The Author(s) 2014.

  16. 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%).

  17. 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

  18. Analysis of Forensic Autopsy in 120 Cases of Medical Disputes Among Different Levels of Institutional Settings.

    Science.gov (United States)

    Yu, Lin-Sheng; Ye, Guang-Hua; Fan, Yan-Yan; Li, Xing-Biao; Feng, Xiang-Ping; Han, Jun-Ge; Lin, Ke-Zhi; Deng, Miao-Wu; Li, Feng

    2015-09-01

    Despite advances in medical science, the causes of death can sometimes only be determined by pathologists after a complete autopsy. Few studies have investigated the importance of forensic autopsy in medically disputed cases among different levels of institutional settings. Our study aimed to analyze forensic autopsy in 120 cases of medical disputes among five levels of institutional settings between 2001 and 2012 in Wenzhou, China. The results showed an overall concordance rate of 55%. Of the 39% of clinically missed diagnosis, cardiovascular pathology comprises 55.32%, while respiratory pathology accounts for the remaining 44. 68%. Factors that increase the likelihood of missed diagnoses were private clinics, community settings, and county hospitals. These results support that autopsy remains an important tool in establishing causes of death in medically disputed case, which may directly determine or exclude the fault of medical care and therefore in helping in resolving these cases. © 2015 American Academy of Forensic Sciences.

  19. 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.

  20. An investigation of children's levels of inquiry in an informal science setting

    Science.gov (United States)

    Clark-Thomas, Beth Anne

    Elementary school students' understanding of both science content and processes are enhanced by the higher level thinking associated with inquiry-based science investigations. Informal science setting personnel, elementary school teachers, and curriculum specialists charged with designing inquiry-based investigations would be well served by an understanding of the varying influence of certain present factors upon the students' willingness and ability to delve into such higher level inquiries. This study examined young children's use of inquiry-based materials and factors which may influence the level of inquiry they engaged in during informal science activities. An informal science setting was selected as the context for the examination of student inquiry behaviors because of the rich inquiry-based environment present at the site and the benefits previously noted in the research regarding the impact of informal science settings upon the construction of knowledge in science. The study revealed several patterns of behavior among children when they are engaged in inquiry-based activities at informal science exhibits. These repeated behaviors varied in the children's apparent purposeful use of the materials at the exhibits. These levels of inquiry behavior were taxonomically defined as high/medium/low within this study utilizing a researcher-developed tool. Furthermore, in this study adult interventions, questions, or prompting were found to impact the level of inquiry engaged in by the children. This study revealed that higher levels of inquiry were preceded by task directed and physical feature prompts. Moreover, the levels of inquiry behaviors were haltered, even lowered, when preceded by a prompt that focused on a science content or concept question. Results of this study have implications for the enhancement of inquiry-based science activities in elementary schools as well as in informal science settings. These findings have significance for all science educators

  1. Education level inequalities and transportation injury mortality in the middle aged and elderly in European settings

    NARCIS (Netherlands)

    Borrell, C.; Plasència, A.; Huisman, M.; Costa, G.; Kunst, A.; Andersen, O.; Bopp, M.; Borgan, J.-K.; Deboosere, P.; Glickman, M.; Gadeyne, S.; Minder, C.; Regidor, E.; Spadea, T.; Valkonen, T.; Mackenbach, J. P.

    2005-01-01

    OBJECTIVE: To study the differential distribution of transportation injury mortality by educational level in nine European settings, among people older than 30 years, during the 1990s. METHODS: Deaths of men and women older than 30 years from transportation injuries were studied. Rate differences

  2. A thick level set interface model for simulating fatigue-drive delamination in composites

    NARCIS (Netherlands)

    Latifi, M.; Van der Meer, F.P.; Sluys, L.J.

    2015-01-01

    This paper presents a new damage model for simulating fatigue-driven delamination in composite laminates. This model is developed based on the Thick Level Set approach (TLS) and provides a favorable link between damage mechanics and fracture mechanics through the non-local evaluation of the energy

  3. Level of health care and services in a tertiary health setting in Nigeria

    African Journals Online (AJOL)

    Level of health care and services in a tertiary health setting in Nigeria. ... Background: There is a growing awareness and demand for quality health care across the world; hence the ... Doctors and nurses formed 64.3% of the study population.

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

    International Nuclear Information System (INIS)

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

    2005-01-01

    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)

  5. 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

    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...

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

    NARCIS (Netherlands)

    Novosel, J.; Wang, Ziyuan; De Jong, Henk; Vermeer, K.A.; van Vliet, L.J.; Styner, Martin A.; Angelini, Elsa D.

    2016-01-01

    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

  7. Scope of physician procedures independently billed by mid-level providers in the office setting.

    Science.gov (United States)

    Coldiron, Brett; Ratnarathorn, Mondhipa

    2014-11-01

    Mid-level providers (nurse practitioners and physician assistants) were originally envisioned to provide primary care services in underserved areas. This study details the current scope of independent procedural billing to Medicare of difficult, invasive, and surgical procedures by medical mid-level providers. To understand the scope of independent billing to Medicare for procedures performed by mid-level providers in an outpatient office setting for a calendar year. Analyses of the 2012 Medicare Physician/Supplier Procedure Summary Master File, which reflects fee-for-service claims that were paid by Medicare, for Current Procedural Terminology procedures independently billed by mid-level providers. Outpatient office setting among health care providers. The scope of independent billing to Medicare for procedures performed by mid-level providers. In 2012, nurse practitioners and physician assistants billed independently for more than 4 million procedures at our cutoff of 5000 paid claims per procedure. Most (54.8%) of these procedures were performed in the specialty area of dermatology. The findings of this study are relevant to safety and quality of care. Recently, the shortage of primary care clinicians has prompted discussion of widening the scope of practice for mid-level providers. It would be prudent to temper widening the scope of practice of mid-level providers by recognizing that mid-level providers are not solely limited to primary care, and may involve procedures for which they may not have formal training.

  8. INTEGRATED SFM TECHNIQUES USING DATA SET FROM GOOGLE EARTH 3D MODEL AND FROM STREET LEVEL

    Directory of Open Access Journals (Sweden)

    L. Inzerillo

    2017-08-01

    Full Text Available 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.

  9. Segment-scale, force-level theory of mesoscopic dynamic localization and entropic elasticity in entangled chain polymer liquids

    Science.gov (United States)

    Dell, Zachary E.; Schweizer, Kenneth S.

    2017-04-01

    We develop a segment-scale, force-based theory for the breakdown of the unentangled Rouse model and subsequent emergence of isotropic mesoscopic localization and entropic elasticity in chain polymer liquids in the absence of ergodicity-restoring anisotropic reptation or activated hopping motion. The theory is formulated in terms of a conformational N-dynamic-order-parameter generalized Langevin equation approach. It is implemented using a universal field-theoretic Gaussian thread model of polymer structure and closed at the level of the chain dynamic second moment matrix. The physical idea is that the isotropic Rouse model fails due to the dynamical emergence, with increasing chain length, of time-persistent intermolecular contacts determined by the combined influence of local uncrossability, long range polymer connectivity, and a self-consistent treatment of chain motion and the dynamic forces that hinder it. For long chain melts, the mesoscopic localization length (identified as the tube diameter) and emergent entropic elasticity predictions are in near quantitative agreement with experiment. Moreover, the onset chain length scales with the semi-dilute crossover concentration with a realistic numerical prefactor. Distinctive novel predictions are made for various off-diagonal correlation functions that quantify the full spatial structure of the dynamically localized polymer conformation. As the local excluded volume constraint and/or intrachain bonding spring are softened to allow chain crossability, the tube diameter is predicted to swell until it reaches the radius-of-gyration at which point mesoscopic localization vanishes in a discontinuous manner. A dynamic phase diagram for such a delocalization transition is constructed, which is qualitatively consistent with simulations and the classical concept of a critical entanglement degree of polymerization.

  10. 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.

  11. 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.

  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. A Cartesian Adaptive Level Set Method for Two-Phase Flows

    Science.gov (United States)

    Ham, F.; Young, Y.-N.

    2003-01-01

    In the present contribution we develop a level set method based on local anisotropic Cartesian adaptation as described in Ham et al. (2002). Such an approach should allow for the smallest possible Cartesian grid capable of resolving a given flow. The remainder of the paper is organized as follows. In section 2 the level set formulation for free surface calculations is presented and its strengths and weaknesses relative to the other free surface methods reviewed. In section 3 the collocated numerical method is described. In section 4 the method is validated by solving the 2D and 3D drop oscilation problem. In section 5 we present some results from more complex cases including the 3D drop breakup in an impulsively accelerated free stream, and the 3D immiscible Rayleigh-Taylor instability. Conclusions are given in section 6.

  14. A level-set method for two-phase flows with soluble surfactant

    Science.gov (United States)

    Xu, Jian-Jun; Shi, Weidong; Lai, Ming-Chih

    2018-01-01

    A level-set method is presented for solving two-phase flows with soluble surfactant. The Navier-Stokes equations are solved along with the bulk surfactant and the interfacial surfactant equations. In particular, the convection-diffusion equation for the bulk surfactant on the irregular moving domain is solved by using a level-set based diffusive-domain method. A conservation law for the total surfactant mass is derived, and a re-scaling procedure for the surfactant concentrations is proposed to compensate for the surfactant mass loss due to numerical diffusion. The whole numerical algorithm is easy for implementation. Several numerical simulations in 2D and 3D show the effects of surfactant solubility on drop dynamics under shear flow.

  15. Application of the level set method for multi-phase flow computation in fusion engineering

    International Nuclear Information System (INIS)

    Luo, X-Y.; Ni, M-J.; Ying, A.; Abdou, M.

    2006-01-01

    Numerical simulation of multi-phase flow is essential to evaluate the feasibility of a liquid protection scheme for the power plant chamber. The level set method is one of the best methods for computing and analyzing the motion of interface among the multi-phase flow. This paper presents a general formula for the second-order projection method combined with the level set method to simulate unsteady incompressible multi-phase flow with/out phase change flow encountered in fusion science and engineering. The third-order ENO scheme and second-order semi-implicit Crank-Nicholson scheme is used to update the convective and diffusion term. The numerical results show this method can handle the complex deformation of the interface and the effect of liquid-vapor phase change will be included in the future work

  16. 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.

  17. Level-set-based reconstruction algorithm for EIT lung images: first clinical results.

    Science.gov (United States)

    Rahmati, Peyman; Soleimani, Manuchehr; Pulletz, Sven; Frerichs, Inéz; Adler, Andy

    2012-05-01

    We show the first clinical results using the level-set-based reconstruction algorithm for electrical impedance tomography (EIT) data. The level-set-based reconstruction method (LSRM) allows the reconstruction of non-smooth interfaces between image regions, which are typically smoothed by traditional voxel-based reconstruction methods (VBRMs). We develop a time difference formulation of the LSRM for 2D images. The proposed reconstruction method is applied to reconstruct clinical EIT data of a slow flow inflation pressure-volume manoeuvre in lung-healthy and adult lung-injury patients. Images from the LSRM and the VBRM are compared. The results show comparable reconstructed images, but with an improved ability to reconstruct sharp conductivity changes in the distribution of lung ventilation using the LSRM.

  18. Level-set-based reconstruction algorithm for EIT lung images: first clinical results

    International Nuclear Information System (INIS)

    Rahmati, Peyman; Adler, Andy; Soleimani, Manuchehr; Pulletz, Sven; Frerichs, Inéz

    2012-01-01

    We show the first clinical results using the level-set-based reconstruction algorithm for electrical impedance tomography (EIT) data. The level-set-based reconstruction method (LSRM) allows the reconstruction of non-smooth interfaces between image regions, which are typically smoothed by traditional voxel-based reconstruction methods (VBRMs). We develop a time difference formulation of the LSRM for 2D images. The proposed reconstruction method is applied to reconstruct clinical EIT data of a slow flow inflation pressure–volume manoeuvre in lung-healthy and adult lung-injury patients. Images from the LSRM and the VBRM are compared. The results show comparable reconstructed images, but with an improved ability to reconstruct sharp conductivity changes in the distribution of lung ventilation using the LSRM. (paper)

  19. Kir2.1 channels set two levels of resting membrane potential with inward rectification.

    Science.gov (United States)

    Chen, Kuihao; Zuo, Dongchuan; Liu, Zheng; Chen, Haijun

    2018-04-01

    Strong inward rectifier K + channels (Kir2.1) mediate background K + currents primarily responsible for maintenance of resting membrane potential. Multiple types of cells exhibit two levels of resting membrane potential. Kir2.1 and K2P1 currents counterbalance, partially accounting for the phenomenon of human cardiomyocytes in subphysiological extracellular K + concentrations or pathological hypokalemic conditions. The mechanism of how Kir2.1 channels contribute to the two levels of resting membrane potential in different types of cells is not well understood. Here we test the hypothesis that Kir2.1 channels set two levels of resting membrane potential with inward rectification. Under hypokalemic conditions, Kir2.1 currents counterbalance HCN2 or HCN4 cation currents in CHO cells that heterologously express both channels, generating N-shaped current-voltage relationships that cross the voltage axis three times and reconstituting two levels of resting membrane potential. Blockade of HCN channels eliminated the phenomenon in K2P1-deficient Kir2.1-expressing human cardiomyocytes derived from induced pluripotent stem cells or CHO cells expressing both Kir2.1 and HCN2 channels. Weakly inward rectifier Kir4.1 or inward rectification-deficient Kir2.1•E224G mutant channels do not set such two levels of resting membrane potential when co-expressed with HCN2 channels in CHO cells or when overexpressed in human cardiomyocytes derived from induced pluripotent stem cells. These findings demonstrate a common mechanism that Kir2.1 channels set two levels of resting membrane potential with inward rectification by balancing inward currents through different cation channels such as hyperpolarization-activated HCN channels or hypokalemia-induced K2P1 leak channels.

  20. Computing the dynamics of biomembranes by combining conservative level set and adaptive finite element methods

    OpenAIRE

    Laadhari , Aymen; Saramito , Pierre; Misbah , Chaouqi

    2014-01-01

    International audience; The numerical simulation of the deformation of vesicle membranes under simple shear external fluid flow is considered in this paper. A new saddle-point approach is proposed for the imposition of the fluid incompressibility and the membrane inextensibility constraints, through Lagrange multipliers defined in the fluid and on the membrane respectively. Using a level set formulation, the problem is approximated by mixed finite elements combined with an automatic adaptive ...

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

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Shenggao, E-mail: sgzhou@suda.edu.cn, E-mail: bli@math.ucsd.edu [Department of Mathematics and Mathematical Center for Interdiscipline Research, Soochow University, 1 Shizi Street, Jiangsu, Suzhou 215006 (China); Sun, Hui; Cheng, Li-Tien [Department of Mathematics, University of California, San Diego, La Jolla, California 92093-0112 (United States); Dzubiella, Joachim [Soft Matter and Functional Materials, Helmholtz-Zentrum Berlin, 14109 Berlin, Germany and Institut für Physik, Humboldt-Universität zu Berlin, 12489 Berlin (Germany); Li, Bo, E-mail: sgzhou@suda.edu.cn, E-mail: bli@math.ucsd.edu [Department of Mathematics and Quantitative Biology Graduate Program, University of California, San Diego, La Jolla, California 92093-0112 (United States); McCammon, J. Andrew [Department of Chemistry and Biochemistry, Department of Pharmacology, Howard Hughes Medical Institute, University of California, San Diego, La Jolla, California 92093-0365 (United States)

    2016-08-07

    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

  2. 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.

  3. Level-set simulations of buoyancy-driven motion of single and multiple bubbles

    International Nuclear Information System (INIS)

    Balcázar, Néstor; Lehmkuhl, Oriol; Jofre, Lluís; Oliva, Assensi

    2015-01-01

    Highlights: • A conservative level-set method is validated and verified. • An extensive study of buoyancy-driven motion of single bubbles is performed. • The interactions of two spherical and ellipsoidal bubbles is studied. • The interaction of multiple bubbles is simulated in a vertical channel. - Abstract: This paper presents a numerical study of buoyancy-driven motion of single and multiple bubbles by means of the conservative level-set method. First, an extensive study of the hydrodynamics of single bubbles rising in a quiescent liquid is performed, including its shape, terminal velocity, drag coefficients and wake patterns. These results are validated against experimental and numerical data well established in the scientific literature. Then, a further study on the interaction of two spherical and ellipsoidal bubbles is performed for different orientation angles. Finally, the interaction of multiple bubbles is explored in a periodic vertical channel. The results show that the conservative level-set approach can be used for accurate modelling of bubble dynamics. Moreover, it is demonstrated that the present method is numerically stable for a wide range of Morton and Reynolds numbers.

  4. Stabilized Conservative Level Set Method with Adaptive Wavelet-based Mesh Refinement

    Science.gov (United States)

    Shervani-Tabar, Navid; Vasilyev, Oleg V.

    2016-11-01

    This paper addresses one of the main challenges of the conservative level set method, namely the ill-conditioned behavior of the normal vector away from the interface. An alternative formulation for reconstruction of the interface is proposed. Unlike the commonly used methods which rely on the unit normal vector, Stabilized Conservative Level Set (SCLS) uses a modified renormalization vector with diminishing magnitude away from the interface. With the new formulation, in the vicinity of the interface the reinitialization procedure utilizes compressive flux and diffusive terms only in the normal direction to the interface, thus, preserving the conservative level set properties, while away from the interfaces the directional diffusion mechanism automatically switches to homogeneous diffusion. The proposed formulation is robust and general. It is especially well suited for use with adaptive mesh refinement (AMR) approaches due to need for a finer resolution in the vicinity of the interface in comparison with the rest of the domain. All of the results were obtained using the Adaptive Wavelet Collocation Method, a general AMR-type method, which utilizes wavelet decomposition to adapt on steep gradients in the solution while retaining a predetermined order of accuracy.

  5. Considering Actionability at the Participant's Research Setting Level for Anticipatable Incidental Findings from Clinical Research.

    Science.gov (United States)

    Ortiz-Osorno, Alberto Betto; Ehler, Linda A; Brooks, Judith

    2015-01-01

    Determining what constitutes an anticipatable incidental finding (IF) from clinical research and defining whether, and when, this IF should be returned to the participant have been topics of discussion in the field of human subject protections for the last 10 years. It has been debated that implementing a comprehensive IF-approach that addresses both the responsibility of researchers to return IFs and the expectation of participants to receive them can be logistically challenging. IFs have been debated at different levels, such as the ethical reasoning for considering their disclosure or the need for planning for them during the development of the research study. Some authors have discussed the methods for re-contacting participants for disclosing IFs, as well as the relevance of considering the clinical importance of the IFs. Similarly, other authors have debated about when IFs should be disclosed to participants. However, no author has addressed how the "actionability" of the IFs should be considered, evaluated, or characterized at the participant's research setting level. This paper defines the concept of "Actionability at the Participant's Research Setting Level" (APRSL) for anticipatable IFs from clinical research, discusses some related ethical concepts to justify the APRSL concept, proposes a strategy to incorporate APRSL into the planning and management of IFs, and suggests a strategy for integrating APRSL at each local research setting. © 2015 American Society of Law, Medicine & Ethics, Inc.

  6. Records for radioactive waste management up to repository closure: Managing the primary level information (PLI) set

    International Nuclear Information System (INIS)

    2004-07-01

    The objective of this publication is to highlight the importance of the early establishment of a comprehensive records system to manage primary level information (PLI) as an integrated set of information, not merely as a collection of information, throughout all the phases of radioactive waste management. Early establishment of a comprehensive records system to manage Primary Level Information as an integrated set of information throughout all phases of radioactive waste management is important. In addition to the information described in the waste inventory record keeping system (WIRKS), the PLI of a radioactive waste repository consists of the entire universe of information, data and records related to any aspect of the repository's life cycle. It is essential to establish PLI requirements based on integrated set of needs from Regulators and Waste Managers involved in the waste management chain and to update these requirements as needs change over time. Information flow for radioactive waste management should be back-end driven. Identification of an Authority that will oversee the management of PLI throughout all phases of the radioactive waste management life cycle would guarantee the information flow to future generations. The long term protection of information essential to future generations can only be assured by the timely establishment of a comprehensive and effective RMS capable of capturing, indexing and evaluating all PLI. The loss of intellectual control over the PLI will make it very difficult to subsequently identify the ILI and HLI information sets. At all times prior to the closure of a radioactive waste repository, there should be an identifiable entity with a legally enforceable financial and management responsibility for the continued operation of a PLI Records Management System. The information presented in this publication will assist Member States in ensuring that waste and repository records, relevant for retention after repository closure

  7. Topological Hausdorff dimension and level sets of generic continuous functions on fractals

    International Nuclear Information System (INIS)

    Balka, Richárd; Buczolich, Zoltán; Elekes, Márton

    2012-01-01

    Highlights: ► We examine a new fractal dimension, the so called topological Hausdorff dimension. ► The generic continuous function has a level set of maximal Hausdorff dimension. ► This maximal dimension is the topological Hausdorff dimension minus one. ► Homogeneity implies that “most” level sets are of this dimension. ► We calculate the various dimensions of the graph of the generic function. - Abstract: In an earlier paper we introduced a new concept of dimension for metric spaces, the so called topological Hausdorff dimension. For a compact metric space K let dim H K and dim tH K denote its Hausdorff and topological Hausdorff dimension, respectively. We proved that this new dimension describes the Hausdorff dimension of the level sets of the generic continuous function on K, namely sup{ dim H f -1 (y):y∈R} =dim tH K-1 for the generic f ∈ C(K), provided that K is not totally disconnected, otherwise every non-empty level set is a singleton. We also proved that if K is not totally disconnected and sufficiently homogeneous then dim H f −1 (y) = dim tH K − 1 for the generic f ∈ C(K) and the generic y ∈ f(K). The most important goal of this paper is to make these theorems more precise. As for the first result, we prove that the supremum is actually attained on the left hand side of the first equation above, and also show that there may only be a unique level set of maximal Hausdorff dimension. As for the second result, we characterize those compact metric spaces for which for the generic f ∈ C(K) and the generic y ∈ f(K) we have dim H f −1 (y) = dim tH K − 1. We also generalize a result of B. Kirchheim by showing that if K is self-similar then for the generic f ∈ C(K) for every y∈intf(K) we have dim H f −1 (y) = dim tH K − 1. Finally, we prove that the graph of the generic f ∈ C(K) has the same Hausdorff and topological Hausdorff dimension as K.

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

    International Nuclear Information System (INIS)

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

    2012-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2012-03-15

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

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

    Science.gov (United States)

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

    2012-03-01

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

  11. A combined single-multiphase flow formulation of the premixing phase using the level set method

    International Nuclear Information System (INIS)

    Leskovar, M.; Marn, J.

    1999-01-01

    The premixing phase of a steam explosion covers the interaction of the melt jet or droplets with the water prior to any steam explosion occurring. To get a better insight of the hydrodynamic processes during the premixing phase beside hot premixing experiments, where the water evaporation is significant, also cold isothermal premixing experiments are performed. The specialty of isothermal premixing experiments is that three phases are involved: the water, the air and the spheres phase, but only the spheres phase mixes with the other two phases whereas the water and air phases do not mix and remain separated by a free surface. Our idea therefore was to treat the isothermal premixing process with a combined single-multiphase flow model. In this combined model the water and air phase are treated as a single phase with discontinuous phase properties at the water air interface, whereas the spheres are treated as usually with a multiphase flow model, where the spheres represent the dispersed phase and the common water-air phase represents the continuous phase. The common water-air phase was described with the front capturing method based on the level set formulation. In the level set formulation, the boundary of two-fluid interfaces is modeled as the zero set of a smooth signed normal distance function defined on the entire physical domain. The boundary is then updated by solving a nonlinear equation of the Hamilton-Jacobi type on the whole domain. With this single-multiphase flow model the Queos isothermal premixing Q08 has been simulated. A numerical analysis using different treatments of the water-air interface (level set, high-resolution and upwind) has been performed for the incompressible and compressible case and the results were compared to experimental measurements.(author)

  12. 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.

  13. Setting ozone critical levels for protecting horticultural Mediterranean crops: Case study of tomato

    International Nuclear Information System (INIS)

    González-Fernández, I.; Calvo, E.; Gerosa, G.; Bermejo, V.; Marzuoli, R.; Calatayud, V.; Alonso, R.

    2014-01-01

    Seven experiments carried out in Italy and Spain have been used to parameterising a stomatal conductance model and establishing exposure– and dose–response relationships for yield and quality of tomato with the main goal of setting O 3 critical levels (CLe). CLe with confidence intervals, between brackets, were set at an accumulated hourly O 3 exposure over 40 nl l −1 , AOT40 = 8.4 (1.2, 15.6) ppm h and a phytotoxic ozone dose above a threshold of 6 nmol m −2 s −1 , POD6 = 2.7 (0.8, 4.6) mmol m −2 for yield and AOT40 = 18.7 (8.5, 28.8) ppm h and POD6 = 4.1 (2.0, 6.2) mmol m −2 for quality, both indices performing equally well. CLe confidence intervals provide information on the quality of the dataset and should be included in future calculations of O 3 CLe for improving current methodologies. These CLe, derived for sensitive tomato cultivars, should not be applied for quantifying O 3 -induced losses at the risk of making important overestimations of the economical losses associated with O 3 pollution. -- Highlights: • Seven independent experiments from Italy and Spain were analysed. • O 3 critical levels are proposed for the protection of summer horticultural crops. • Exposure- and flux-based O 3 indices performed equally well. • Confidence intervals of the new O 3 critical levels are calculated. • A new method to estimate the degree risk of O 3 damage is proposed. -- Critical levels for tomato yield were set at AOT40 = 8.4 ppm h and POD6 = 2.7 mmol m −2 and confidence intervals should be used for improving O 3 risk assessment

  14. Numerical Modelling of Three-Fluid Flow Using The Level-set Method

    Science.gov (United States)

    Li, Hongying; Lou, Jing; Shang, Zhi

    2014-11-01

    This work presents a numerical model for simulation of three-fluid flow involving two different moving interfaces. These interfaces are captured using the level-set method via two different level-set functions. A combined formulation with only one set of conservation equations for the whole physical domain, consisting of the three different immiscible fluids, is employed. Numerical solution is performed on a fixed mesh using the finite volume method. Surface tension effect is incorporated using the Continuum Surface Force model. Validation of the present model is made against available results for stratified flow and rising bubble in a container with a free surface. Applications of the present model are demonstrated by a variety of three-fluid flow systems including (1) three-fluid stratified flow, (2) two-fluid stratified flow carrying the third fluid in the form of drops and (3) simultaneous rising and settling of two drops in a stationary third fluid. The work is supported by a Thematic and Strategic Research from A*STAR, Singapore (Ref. #: 1021640075).

  15. Sipunculans and segmentation

    DEFF Research Database (Denmark)

    Wanninger, Andreas; Kristof, Alen; Brinkmann, Nora

    2009-01-01

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

  16. 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.

  17. 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.

  18. Nurses' comfort level with spiritual assessment: a study among nurses working in diverse healthcare settings.

    Science.gov (United States)

    Cone, Pamela H; Giske, Tove

    2017-10-01

    To gain knowledge about nurses' comfort level in assessing spiritual matters and to learn what questions nurses use in practice related to spiritual assessment. Spirituality is important in holistic nursing care; however, nurses report feeling uncomfortable and ill-prepared to address this domain with patients. Education is reported to impact nurses' ability to engage in spiritual care. This cross-sectional exploratory survey reports on a mixed-method study examining how comfortable nurses are with spiritual assessment. In 2014, a 21-item survey with 10 demographic variables and three open-ended questions were distributed to Norwegian nurses working in diverse care settings with 172 nurse responses (72 % response rate). SPSS was used to analyse quantitative data; thematic analysis examined the open-ended questions. Norwegian nurses reported a high level of comfort with most questions even though spirituality is seen as private. Nurses with some preparation or experience in spiritual care were most comfortable assessing spirituality. Statistically significant correlations were found between the nurses' comfort level with spiritual assessment and their preparedness and sense of the importance of spiritual assessment. How well-prepared nurses felt was related to years of experience, degree of spirituality and religiosity, and importance of spiritual assessment. Many nurses are poorly prepared for spiritual assessment and care among patients in diverse care settings; educational preparation increases their comfort level with facilitating such care. Nurses who feel well prepared with spirituality feel more comfortable with the spiritual domain. By fostering a culture where patients' spirituality is discussed and reflected upon in everyday practice and in continued education, nurses' sense of preparedness, and thus their level of comfort, can increase. Clinical supervision and interprofessional collaboration with hospital chaplains and/or other spiritual leaders can

  19. 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

    . 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......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...

  20. A multilevel, level-set method for optimizing eigenvalues in shape design problems

    International Nuclear Information System (INIS)

    Haber, E.

    2004-01-01

    In this paper, we consider optimal design problems that involve shape optimization. The goal is to determine the shape of a certain structure such that it is either as rigid or as soft as possible. To achieve this goal we combine two new ideas for an efficient solution of the problem. First, we replace the eigenvalue problem with an approximation by using inverse iteration. Second, we use a level set method but rather than propagating the front we use constrained optimization methods combined with multilevel continuation techniques. Combining these two ideas we obtain a robust and rapid method for the solution of the optimal design problem

  1. Modeling Restrained Shrinkage Induced Cracking in Concrete Rings Using the Thick Level Set Approach

    Directory of Open Access Journals (Sweden)

    Rebecca Nakhoul

    2018-03-01

    Full Text Available Modeling restrained shrinkage-induced damage and cracking in concrete is addressed herein. The novel Thick Level Set (TLS damage growth and crack propagation model is used and adapted by introducing shrinkage contribution into the formulation. The TLS capacity to predict damage evolution, crack initiation and growth triggered by restrained shrinkage in absence of external loads is evaluated. A study dealing with shrinkage-induced cracking in elliptical concrete rings is presented herein. Key results such as the effect of rings oblateness on stress distribution and critical shrinkage strain needed to initiate damage are highlighted. In addition, crack positions are compared to those observed in experiments and are found satisfactory.

  2. Microwave imaging of dielectric cylinder using level set method and conjugate gradient algorithm

    International Nuclear Information System (INIS)

    Grayaa, K.; Bouzidi, A.; Aguili, T.

    2011-01-01

    In this paper, we propose a computational method for microwave imaging cylinder and dielectric object, based on combining level set technique and the conjugate gradient algorithm. By measuring the scattered field, we tried to retrieve the shape, localisation and the permittivity of the object. The forward problem is solved by the moment method, while the inverse problem is reformulate in an optimization one and is solved by the proposed scheme. It found that the proposed method is able to give good reconstruction quality in terms of the reconstructed shape and permittivity.

  3. 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.

  4. Implications of sea-level rise in a modern carbonate ramp setting

    Science.gov (United States)

    Lokier, Stephen W.; Court, Wesley M.; Onuma, Takumi; Paul, Andreas

    2018-03-01

    This study addresses a gap in our understanding of the effects of sea-level rise on the sedimentary systems and morphological development of recent and ancient carbonate ramp settings. Many ancient carbonate sequences are interpreted as having been deposited in carbonate ramp settings. These settings are poorly-represented in the Recent. The study documents the present-day transgressive flooding of the Abu Dhabi coastline at the southern shoreline of the Arabian/Persian Gulf, a carbonate ramp depositional system that is widely employed as a Recent analogue for numerous ancient carbonate systems. Fourteen years of field-based observations are integrated with historical and recent high-resolution satellite imagery in order to document and assess the onset of flooding. Predicted rates of transgression (i.e. landward movement of the shoreline) of 2.5 m yr- 1 (± 0.2 m yr- 1) based on global sea-level rise alone were far exceeded by the flooding rate calculated from the back-stepping of coastal features (10-29 m yr- 1). This discrepancy results from the dynamic nature of the flooding with increased water depth exposing the coastline to increased erosion and, thereby, enhancing back-stepping. A non-accretionary transgressive shoreline trajectory results from relatively rapid sea-level rise coupled with a low-angle ramp geometry and a paucity of sediments. The flooding is represented by the landward migration of facies belts, a range of erosive features and the onset of bioturbation. Employing Intergovernmental Panel on Climate Change (Church et al., 2013) predictions for 21st century sea-level rise, and allowing for the post-flooding lag time that is typical for the start-up of carbonate factories, it is calculated that the coastline will continue to retrograde for the foreseeable future. Total passive flooding (without considering feedback in the modification of the shoreline) by the year 2100 is calculated to likely be between 340 and 571 m with a flooding rate of 3

  5. Robust space-time extraction of ventricular surface evolution using multiphase level sets

    Science.gov (United States)

    Drapaca, Corina S.; Cardenas, Valerie; Studholme, Colin

    2004-05-01

    This paper focuses on the problem of accurately extracting the CSF-tissue boundary, particularly around the ventricular surface, from serial structural MRI of the brain acquired in imaging studies of aging and dementia. This is a challenging problem because of the common occurrence of peri-ventricular lesions which locally alter the appearance of white matter. We examine a level set approach which evolves a four dimensional description of the ventricular surface over time. This has the advantage of allowing constraints on the contour in the temporal dimension, improving the consistency of the extracted object over time. We follow the approach proposed by Chan and Vese which is based on the Mumford and Shah model and implemented using the Osher and Sethian level set method. We have extended this to the 4 dimensional case to propagate a 4D contour toward the tissue boundaries through the evolution of a 5D implicit function. For convergence we use region-based information provided by the image rather than the gradient of the image. This is adapted to allow intensity contrast changes between time frames in the MRI sequence. Results on time sequences of 3D brain MR images are presented and discussed.

  6. Topology optimization in acoustics and elasto-acoustics via a level-set method

    Science.gov (United States)

    Desai, J.; Faure, A.; Michailidis, G.; Parry, G.; Estevez, R.

    2018-04-01

    Optimizing the shape and topology (S&T) of structures to improve their acoustic performance is quite challenging. The exact position of the structural boundary is usually of critical importance, which dictates the use of geometric methods for topology optimization instead of standard density approaches. The goal of the present work is to investigate different possibilities for handling topology optimization problems in acoustics and elasto-acoustics via a level-set method. From a theoretical point of view, we detail two equivalent ways to perform the derivation of surface-dependent terms and propose a smoothing technique for treating problems of boundary conditions optimization. In the numerical part, we examine the importance of the surface-dependent term in the shape derivative, neglected in previous studies found in the literature, on the optimal designs. Moreover, we test different mesh adaptation choices, as well as technical details related to the implicit surface definition in the level-set approach. We present results in two and three-space dimensions.

  7. A mass conserving level set method for detailed numerical simulation of liquid atomization

    Energy Technology Data Exchange (ETDEWEB)

    Luo, Kun; Shao, Changxiao [State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou 310027 (China); Yang, Yue [State Key Laboratory of Turbulence and Complex Systems, Peking University, Beijing 100871 (China); Fan, Jianren, E-mail: fanjr@zju.edu.cn [State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou 310027 (China)

    2015-10-01

    An improved mass conserving level set method for detailed numerical simulations of liquid atomization is developed to address the issue of mass loss in the existing level set method. This method introduces a mass remedy procedure based on the local curvature at the interface, and in principle, can ensure the absolute mass conservation of the liquid phase in the computational domain. Three benchmark cases, including Zalesak's disk, a drop deforming in a vortex field, and the binary drop head-on collision, are simulated to validate the present method, and the excellent agreement with exact solutions or experimental results is achieved. It is shown that the present method is able to capture the complex interface with second-order accuracy and negligible additional computational cost. The present method is then applied to study more complex flows, such as a drop impacting on a liquid film and the swirling liquid sheet atomization, which again, demonstrates the advantages of mass conservation and the capability to represent the interface accurately.

  8. HPC in Basin Modeling: Simulating Mechanical Compaction through Vertical Effective Stress using Level Sets

    Science.gov (United States)

    McGovern, S.; Kollet, S. J.; Buerger, C. M.; Schwede, R. L.; Podlaha, O. G.

    2017-12-01

    In the context of sedimentary basins, we present a model for the simulation of the movement of ageological formation (layers) during the evolution of the basin through sedimentation and compactionprocesses. Assuming a single phase saturated porous medium for the sedimentary layers, the modelfocuses on the tracking of the layer interfaces, through the use of the level set method, as sedimentationdrives fluid-flow and reduction of pore space by compaction. On the assumption of Terzaghi's effectivestress concept, the coupling of the pore fluid pressure to the motion of interfaces in 1-D is presented inMcGovern, et.al (2017) [1] .The current work extends the spatial domain to 3-D, though we maintain the assumption ofvertical effective stress to drive the compaction. The idealized geological evolution is conceptualized asthe motion of interfaces between rock layers, whose paths are determined by the magnitude of a speedfunction in the direction normal to the evolving layer interface. The speeds normal to the interface aredependent on the change in porosity, determined through an effective stress-based compaction law,such as the exponential Athy's law. Provided with the speeds normal to the interface, the level setmethod uses an advection equation to evolve a potential function, whose zero level set defines theinterface. Thus, the moving layer geometry influences the pore pressure distribution which couplesback to the interface speeds. The flexible construction of the speed function allows extension, in thefuture, to other terms to represent different physical processes, analogous to how the compaction rulerepresents material deformation.The 3-D model is implemented using the generic finite element method framework Deal II,which provides tools, building on p4est and interfacing to PETSc, for the massively parallel distributedsolution to the model equations [2]. Experiments are being run on the Juelich Supercomputing Center'sJureca cluster. [1] McGovern, et.al. (2017

  9. Cache-Oblivious Red-Blue Line Segment Intersection

    DEFF Research Database (Denmark)

    Arge, Lars; Mølhave, Thomas; Zeh, Norbert

    2008-01-01

    We present an optimal cache-oblivious algorithm for finding all intersections between a set of non-intersecting red segments and a set of non-intersecting blue segments in the plane. Our algorithm uses $O(\\frac{N}{B}\\log_{M/B}\\frac{N}{B}+T/B)$ memory transfers, where N is the total number...... of segments, M and B are the memory and block transfer sizes of any two consecutive levels of any multilevel memory hierarchy, and T is the number of intersections....

  10. Fully convolutional network with cluster for semantic segmentation

    Science.gov (United States)

    Ma, Xiao; Chen, Zhongbi; Zhang, Jianlin

    2018-04-01

    At present, image semantic segmentation technology has been an active research topic for scientists in the field of computer vision and artificial intelligence. Especially, the extensive research of deep neural network in image recognition greatly promotes the development of semantic segmentation. This paper puts forward a method based on fully convolutional network, by cluster algorithm k-means. The cluster algorithm using the image's low-level features and initializing the cluster centers by the super-pixel segmentation is proposed to correct the set of points with low reliability, which are mistakenly classified in great probability, by the set of points with high reliability in each clustering regions. This method refines the segmentation of the target contour and improves the accuracy of the image segmentation.

  11. 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

  12. 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.

  13. Glycated albumin is set lower in relation to plasma glucose levels in patients with Cushing's syndrome.

    Science.gov (United States)

    Kitamura, Tetsuhiro; Otsuki, Michio; Tamada, Daisuke; Tabuchi, Yukiko; Mukai, Kosuke; Morita, Shinya; Kasayama, Soji; Shimomura, Iichiro; Koga, Masafumi

    2013-09-23

    Glycated albumin (GA) is an indicator of glycemic control, which has some specific characters in comparison with HbA1c. Since glucocorticoids (GC) promote protein catabolism including serum albumin, GC excess state would influence GA levels. We therefore investigated GA levels in patients with Cushing's syndrome. We studied 16 patients with Cushing's syndrome (8 patients had diabetes mellitus and the remaining 8 patients were non-diabetic). Thirty-two patients with type 2 diabetes mellitus and 32 non-diabetic subjects matched for age, sex and BMI were used as controls. In the patients with Cushing's syndrome, GA was significantly correlated with HbA1c, but the regression line shifted downwards as compared with the controls. The GA/HbA1c ratio in the patients with Cushing's syndrome was also significantly lower than the controls. HbA1c in the non-diabetic patients with Cushing's syndrome was not different from the non-diabetic controls, whereas GA was significantly lower. In 7 patients with Cushing's syndrome who performed self-monitoring of blood glucose, the measured HbA1c was matched with HbA1c estimated from mean blood glucose, whereas the measured GA was significantly lower than the estimated GA. We clarified that GA is set lower in relation to plasma glucose levels in patients with Cushing's syndrome. Copyright © 2013 Elsevier B.V. All rights reserved.

  14. CT Findings of Disease with Elevated Serum D-Dimer Levels in an Emergency Room Setting

    International Nuclear Information System (INIS)

    Choi, Ji Youn; Kwon, Woo Cheol; Kim, Young Ju

    2012-01-01

    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.

  15. Transport equations, Level Set and Eulerian mechanics. Application to fluid-structure coupling

    International Nuclear Information System (INIS)

    Maitre, E.

    2008-11-01

    My works were devoted to numerical analysis of non-linear elliptic-parabolic equations, to neutron transport equation and to the simulation of fabrics draping. More recently I developed an Eulerian method based on a level set formulation of the immersed boundary method to deal with fluid-structure coupling problems arising in bio-mechanics. Some of the more efficient algorithms to solve the neutron transport equation make use of the splitting of the transport operator taking into account its characteristics. In the present work we introduced a new algorithm based on this splitting and an adaptation of minimal residual methods to infinite dimensional case. We present the case where the velocity space is of dimension 1 (slab geometry) and 2 (plane geometry) because the splitting is simpler in the former

  16. Numerical simulation of overflow at vertical weirs using a hybrid level set/VOF method

    Science.gov (United States)

    Lv, Xin; Zou, Qingping; Reeve, Dominic

    2011-10-01

    This paper presents the applications of a newly developed free surface flow model to the practical, while challenging overflow problems for weirs. Since the model takes advantage of the strengths of both the level set and volume of fluid methods and solves the Navier-Stokes equations on an unstructured mesh, it is capable of resolving the time evolution of very complex vortical motions, air entrainment and pressure variations due to violent deformations following overflow of the weir crest. In the present study, two different types of vertical weir, namely broad-crested and sharp-crested, are considered for validation purposes. The calculated overflow parameters such as pressure head distributions, velocity distributions, and water surface profiles are compared against experimental data as well as numerical results available in literature. A very good quantitative agreement has been obtained. The numerical model, thus, offers a good alternative to traditional experimental methods in the study of weir problems.

  17. Level set method for optimal shape design of MRAM core. Micromagnetic approach

    International Nuclear Information System (INIS)

    Melicher, Valdemar; Cimrak, Ivan; Keer, Roger van

    2008-01-01

    We aim at optimizing the shape of the magnetic core in MRAM memories. The evolution of the magnetization during the writing process is described by the Landau-Lifshitz equation (LLE). The actual shape of the core in one cell is characterized by the coefficient γ. Cost functional f=f(γ) expresses the quality of the writing process having in mind the competition between the full-select and the half-select element. We derive an explicit form of the derivative F=∂f/∂γ which allows for the use of gradient-type methods for the actual computation of the optimized shape (e.g., steepest descend method). The level set method (LSM) is employed for the representation of the piecewise constant coefficient γ

  18. Level-set dynamics and mixing efficiency of passive and active scalars in DNS and LES of turbulent mixing layers

    NARCIS (Netherlands)

    Geurts, Bernard J.; Vreman, Bert; Kuerten, Hans; Luo, Kai H.

    2001-01-01

    The mixing efficiency in a turbulent mixing layer is quantified by monitoring the surface-area of level-sets of scalar fields. The Laplace transform is applied to numerically calculate integrals over arbitrary level-sets. The analysis includes both direct and large-eddy simulation and is used to

  19. Analysis of Fundus Fluorescein Angiogram Based on the Hessian Matrix of Directional Curvelet Sub-bands and Distance Regularized Level Set Evolution.

    Science.gov (United States)

    Soltanipour, Asieh; Sadri, Saeed; Rabbani, Hossein; Akhlaghi, Mohammad Reza

    2015-01-01

    This paper presents a new procedure for automatic extraction of the blood vessels and optic disk (OD) in fundus fluorescein angiogram (FFA). In order to extract blood vessel centerlines, the algorithm of vessel extraction starts with the analysis of directional images resulting from sub-bands of fast discrete curvelet transform (FDCT) in the similar directions and different scales. For this purpose, each directional image is processed by using information of the first order derivative and eigenvalues obtained from the Hessian matrix. The final vessel segmentation is obtained using a simple region growing algorithm iteratively, which merges centerline images with the contents of images resulting from modified top-hat transform followed by bit plane slicing. After extracting blood vessels from FFA image, candidates regions for OD are enhanced by removing blood vessels from the FFA image, using multi-structure elements morphology, and modification of FDCT coefficients. Then, canny edge detector and Hough transform are applied to the reconstructed image to extract the boundary of candidate regions. At the next step, the information of the main arc of the retinal vessels surrounding the OD region is used to extract the actual location of the OD. Finally, the OD boundary is detected by applying distance regularized level set evolution. The proposed method was tested on the FFA images from angiography unit of Isfahan Feiz Hospital, containing 70 FFA images from different diabetic retinopathy stages. The experimental results show the accuracy more than 93% for vessel segmentation and more than 87% for OD boundary extraction.

  20. 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.

  1. A hybrid interface tracking - level set technique for multiphase flow with soluble surfactant

    Science.gov (United States)

    Shin, Seungwon; Chergui, Jalel; Juric, Damir; Kahouadji, Lyes; Matar, Omar K.; Craster, Richard V.

    2018-04-01

    A formulation for soluble surfactant transport in multiphase flows recently presented by Muradoglu and Tryggvason (JCP 274 (2014) 737-757) [17] is adapted to the context of the Level Contour Reconstruction Method, LCRM, (Shin et al. IJNMF 60 (2009) 753-778, [8]) which is a hybrid method that combines the advantages of the Front-tracking and Level Set methods. Particularly close attention is paid to the formulation and numerical implementation of the surface gradients of surfactant concentration and surface tension. Various benchmark tests are performed to demonstrate the accuracy of different elements of the algorithm. To verify surfactant mass conservation, values for surfactant diffusion along the interface are compared with the exact solution for the problem of uniform expansion of a sphere. The numerical implementation of the discontinuous boundary condition for the source term in the bulk concentration is compared with the approximate solution. Surface tension forces are tested for Marangoni drop translation. Our numerical results for drop deformation in simple shear are compared with experiments and results from previous simulations. All benchmarking tests compare well with existing data thus providing confidence that the adapted LCRM formulation for surfactant advection and diffusion is accurate and effective in three-dimensional multiphase flows with a structured mesh. We also demonstrate that this approach applies easily to massively parallel simulations.

  2. Natural setting of Japanese islands and geologic disposal of high-level waste

    International Nuclear Information System (INIS)

    Koide, Hitoshi

    1991-01-01

    The Japanese islands are a combination of arcuate islands along boundaries between four major plates: Eurasia, North America, Pacific and Philippine Sea plates. The interaction among the four plates formed complex geological structures which are basically patchworks of small blocks of land and sea-floor sediments piled up by the subduction of oceanic plates along the margin of the Eurasia continent. Although frequent earthquakes and volcanic eruptions clearly indicate active crustal deformation, the distribution of active faults and volcanoes is localized regionally in the Japanese islands. Crustal displacement faster than 1 mm/year takes place only in restricted regions near plate boundaries or close to major active faults. Volcanic activity is absent in the region between the volcanic front and the subduction zone. The site selection is especially important in Japan. The scenarios for the long-term performance assessment of high-level waste disposal are discussed with special reference to the geological setting of Japan. The long-term prediction of tectonic disturbance, evaluation of faults and fractures in rocks and estimation of long-term water-rock interaction are key issues in the performance assessment of the high-level waste disposal in the Japanese islands. (author)

  3. 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.

  4. Using multimodal information for the segmentation of fluorescent micrographs with application to virology and microbiology.

    Science.gov (United States)

    Held, Christian; Wenzel, Jens; Webel, Rike; Marschall, Manfred; Lang, Roland; Palmisano, Ralf; Wittenberg, Thomas

    2011-01-01

    In order to improve reproducibility and objectivity of fluorescence microscopy based experiments and to enable the evaluation of large datasets, flexible segmentation methods are required which are able to adapt to different stainings and cell types. This adaption is usually achieved by the manual adjustment of the segmentation methods parameters, which is time consuming and challenging for biologists with no knowledge on image processing. To avoid this, parameters of the presented methods automatically adapt to user generated ground truth to determine the best method and the optimal parameter setup. These settings can then be used for segmentation of the remaining images. As robust segmentation methods form the core of such a system, the currently used watershed transform based segmentation routine is replaced by a fast marching level set based segmentation routine which incorporates knowledge on the cell nuclei. Our evaluations reveal that incorporation of multimodal information improves segmentation quality for the presented fluorescent datasets.

  5. Relationships between college settings and student alcohol use before, during and after events: a multi-level study.

    Science.gov (United States)

    Paschall, Mallie J; Saltz, Robert F

    2007-11-01

    We examined how alcohol risk is distributed based on college students' drinking before, during and after they go to certain settings. Students attending 14 California public universities (N=10,152) completed a web-based or mailed survey in the fall 2003 semester, which included questions about how many drinks they consumed before, during and after the last time they went to six settings/events: fraternity or sorority party, residence hall party, campus event (e.g. football game), off-campus party, bar/restaurant and outdoor setting (referent). Multi-level analyses were conducted in hierarchical linear modeling (HLM) to examine relationships between type of setting and level of alcohol use before, during and after going to the setting, and possible age and gender differences in these relationships. Drinking episodes (N=24,207) were level 1 units, students were level 2 units and colleges were level 3 units. The highest drinking levels were observed during all settings/events except campus events, with the highest number of drinks being consumed at off-campus parties, followed by residence hall and fraternity/sorority parties. The number of drinks consumed before a fraternity/sorority party was higher than other settings/events. Age group and gender differences in relationships between type of setting/event and 'before,''during' and 'after' drinking levels also were observed. For example, going to a bar/restaurant (relative to an outdoor setting) was positively associated with 'during' drinks among students of legal drinking age while no relationship was observed for underage students. Findings of this study indicate differences in the extent to which college settings are associated with student drinking levels before, during and after related events, and may have implications for intervention strategies targeting different types of settings.

  6. Segmentation: Identification of consumer segments

    DEFF Research Database (Denmark)

    Høg, Esben

    2005-01-01

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

  7. Generalized cost-effectiveness analysis for national-level priority-setting in the health sector

    Directory of Open Access Journals (Sweden)

    Edejer Tessa

    2003-12-01

    Full Text Available Abstract Cost-effectiveness analysis (CEA is potentially an important aid to public health decision-making but, with some notable exceptions, its use and impact at the level of individual countries is limited. A number of potential reasons may account for this, among them technical shortcomings associated with the generation of current economic evidence, political expediency, social preferences and systemic barriers to implementation. As a form of sectoral CEA, Generalized CEA sets out to overcome a number of these barriers to the appropriate use of cost-effectiveness information at the regional and country level. Its application via WHO-CHOICE provides a new economic evidence base, as well as underlying methodological developments, concerning the cost-effectiveness of a range of health interventions for leading causes of, and risk factors for, disease. The estimated sub-regional costs and effects of different interventions provided by WHO-CHOICE can readily be tailored to the specific context of individual countries, for example by adjustment to the quantity and unit prices of intervention inputs (costs or the coverage, efficacy and adherence rates of interventions (effectiveness. The potential usefulness of this information for health policy and planning is in assessing if current intervention strategies represent an efficient use of scarce resources, and which of the potential additional interventions that are not yet implemented, or not implemented fully, should be given priority on the grounds of cost-effectiveness. Health policy-makers and programme managers can use results from WHO-CHOICE as a valuable input into the planning and prioritization of services at national level, as well as a starting point for additional analyses of the trade-off between the efficiency of interventions in producing health and their impact on other key outcomes such as reducing inequalities and improving the health of the poor.

  8. Segmental Vitiligo.

    Science.gov (United States)

    van Geel, Nanja; Speeckaert, Reinhart

    2017-04-01

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

  9. Innovative visualization and segmentation approaches for telemedicine

    Science.gov (United States)

    Nguyen, D.; Roehrig, Hans; Borders, Marisa H.; Fitzpatrick, Kimberly A.; Roveda, Janet

    2014-09-01

    In health care applications, we obtain, manage, store and communicate using high quality, large volume of image data through integrated devices. In this paper we propose several promising methods that can assist physicians in image data process and communication. We design a new semi-automated segmentation approach for radiological images, such as CT and MRI to clearly identify the areas of interest. This approach combines the advantages from both the region-based method and boundary-based methods. It has three key steps compose: coarse segmentation by using fuzzy affinity and homogeneity operator, image division and reclassification using the Voronoi Diagram, and refining boundary lines using the level set model.

  10. 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, padvantage 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 block in the first set and in the reception in the third and fifth sets.

  11. On the modeling of bubble evolution and transport using coupled level-set/CFD method

    International Nuclear Information System (INIS)

    Bartlomiej Wierzbicki; Steven P Antal; Michael Z Podowski

    2005-01-01

    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

  12. [Atorvastatin improves reflow after percutaneous coronary intervention in patients with acute ST-segment elevation myocardial infarction by decreasing serum uric acid level].

    Science.gov (United States)

    Yan, Ling; Ye, Lu; Wang, Kun; Zhou, Jie; Zhu, Chunjia

    2016-05-25

    Objective: To investigate the effect of atorvastatin on reflow in patients with acute ST-segment elevation myocardial infarction (STEMI) after percutaneous coronary intervention (PCI) and its relation to serum uric acid levels. Methods: One hundred and fourteen STEMI patients undergoing primary PCI were enrolled and randomly divided into two groups:55 cases received oral atorvastatin 20 mg before PCI (routine dose group) and 59 cases received oral atorvastatin 80 mg before PCI (high dose group). According to the initial serum uric acid level, patients in two groups were further divided into normal uric acid subgroup and hyperuricemia subgroup. The changes of uric acid level and coronary artery blood flow after PCI were observed. Correlations between the decrease of uric acid, the dose of atorvastatin and the blood flow of coronary artery after PCI were analyzed. Results: Serum uric acid levels were decreased after treatment in both groups (all P uric acid level ( P uric acid level in patients with hyperuricemia decreased more significantly in the high dose group ( P uric acid levels in two groups ( P >0.05). Among 114 patients, there were 19 cases without reflow after PCI (16.7%). In the routine dose group, there were 12 patients without reflow, in which 3 had normal uric acid and 9 had high uric acid levels ( P uric acid and 5 had high uric acid ( P uric acid levels and improve reflow after PCI in patients with STEMI.

  13. Fluoroscopy-guided insertion of nasojejunal tubes in children - setting local diagnostic reference levels

    International Nuclear Information System (INIS)

    Vitta, Lavanya; Raghavan, Ashok; Sprigg, Alan; Morrell, Rachel

    2009-01-01

    Little is known about the radiation burden from fluoroscopy-guided insertions of nasojejunal tubes (NJTs) in children. There are no recommended or published standards of diagnostic reference levels (DRLs) available. To establish reference dose area product (DAP) levels for the fluoroscopy-guided insertion of nasojejunal tubes as a basis for setting DRLs for children. In addition, we wanted to assess our local practice and determine the success and complication rates associated with this procedure. Children who had NJT insertion procedures were identified retrospectively from the fluoroscopy database. The age of the child at the time of the procedure, DAP, screening time, outcome of the procedure, and any complications were recorded for each procedure. As the radiation dose depends on the size of the child, the children were assigned to three different age groups. The sample size, mean, median and third-quartile DAPs were calculated for each group. The third-quartile values were used to establish the DRLs. Of 186 procedures performed, 172 were successful on the first attempt. These were performed in a total of 43 children with 60% having multiple insertions over time. The third-quartile DAPs were as follows for each age group: 0-12 months, 2.6 cGy cm 2 ; 1-7 years, 2.45 cGy cm 2 ; >8 years, 14.6 cGy cm 2 . High DAP readings were obtained in the 0-12 months (n = 4) and >8 years (n = 2) age groups. No immediate complications were recorded. Fluoroscopy-guided insertion of NJTs is a highly successful procedure in a selected population of children and is associated with a low complication rate. The radiation dose per procedure is relatively low. (orig.)

  14. 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.

  15. An integrated extended Kalman filter–implicit level set algorithm for monitoring planar hydraulic fractures

    International Nuclear Information System (INIS)

    Peirce, A; Rochinha, F

    2012-01-01

    We describe a novel approach to the inversion of elasto-static tiltmeter measurements to monitor planar hydraulic fractures propagating within three-dimensional elastic media. The technique combines the extended Kalman filter (EKF), which predicts and updates state estimates using tiltmeter measurement time-series, with a novel implicit level set algorithm (ILSA), which solves the coupled elasto-hydrodynamic equations. The EKF and ILSA are integrated to produce an algorithm to locate the unknown fracture-free boundary. A scaling argument is used to derive a strategy to tune the algorithm parameters to enable measurement information to compensate for unmodeled dynamics. Synthetic tiltmeter data for three numerical experiments are generated by introducing significant changes to the fracture geometry by altering the confining geological stress field. Even though there is no confining stress field in the dynamic model used by the new EKF-ILSA scheme, it is able to use synthetic data to arrive at remarkably accurate predictions of the fracture widths and footprints. These experiments also explore the robustness of the algorithm to noise and to placement of tiltmeter arrays operating in the near-field and far-field regimes. In these experiments, the appropriate parameter choices and strategies to improve the robustness of the algorithm to significant measurement noise are explored. (paper)

  16. Automatic Fontanel Extraction from Newborns' CT Images Using Variational Level Set

    Science.gov (United States)

    Kazemi, Kamran; Ghadimi, Sona; Lyaghat, Alireza; Tarighati, Alla; Golshaeyan, Narjes; Abrishami-Moghaddam, Hamid; Grebe, Reinhard; Gondary-Jouet, Catherine; Wallois, Fabrice

    A realistic head model is needed for source localization methods used for the study of epilepsy in neonates applying Electroencephalographic (EEG) measurements from the scalp. The earliest models consider the head as a series of concentric spheres, each layer corresponding to a different tissue whose conductivity is assumed to be homogeneous. The results of the source reconstruction depend highly on the electric conductivities of the tissues forming the head.The most used model is constituted of three layers (scalp, skull, and intracranial). Most of the major bones of the neonates’ skull are ossified at birth but can slightly move relative to each other. This is due to the sutures, fibrous membranes that at this stage of development connect the already ossified flat bones of the neurocranium. These weak parts of the neurocranium are called fontanels. Thus it is important to enter the exact geometry of fontaneles and flat bone in a source reconstruction because they show pronounced in conductivity. Computer Tomography (CT) imaging provides an excellent tool for non-invasive investigation of the skull which expresses itself in high contrast to all other tissues while the fontanels only can be identified as absence of bone, gaps in the skull formed by flat bone. Therefore, the aim of this paper is to extract the fontanels from CT images applying a variational level set method. We applied the proposed method to CT-images of five different subjects. The automatically extracted fontanels show good agreement with the manually extracted ones.

  17. Two-phase electro-hydrodynamic flow modeling by a conservative level set model.

    Science.gov (United States)

    Lin, Yuan

    2013-03-01

    The principles of electro-hydrodynamic (EHD) flow have been known for more than a century and have been adopted for various industrial applications, for example, fluid mixing and demixing. Analytical solutions of such EHD flow only exist in a limited number of scenarios, for example, predicting a small deformation of a single droplet in a uniform electric field. Numerical modeling of such phenomena can provide significant insights about EHDs multiphase flows. During the last decade, many numerical results have been reported to provide novel and useful tools of studying the multiphase EHD flow. Based on a conservative level set method, the proposed model is able to simulate large deformations of a droplet by a steady electric field, which is beyond the region of theoretic prediction. The model is validated for both leaky dielectrics and perfect dielectrics, and is found to be in excellent agreement with existing analytical solutions and numerical studies in the literature. Furthermore, simulations of the deformation of a water droplet in decyl alcohol in a steady electric field match better with published experimental data than the theoretical prediction for large deformations. Therefore the proposed model can serve as a practical and accurate tool for simulating two-phase EHD flow. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. Modeling of Two-Phase Flow in Rough-Walled Fracture Using Level Set Method

    Directory of Open Access Journals (Sweden)

    Yunfeng Dai

    2017-01-01

    Full Text Available To describe accurately the flow characteristic of fracture scale displacements of immiscible fluids, an incompressible two-phase (crude oil and water flow model incorporating interfacial forces and nonzero contact angles is developed. The roughness of the two-dimensional synthetic rough-walled fractures is controlled with different fractal dimension parameters. Described by the Navier–Stokes equations, the moving interface between crude oil and water is tracked using level set method. The method accounts for differences in densities and viscosities of crude oil and water and includes the effect of interfacial force. The wettability of the rough fracture wall is taken into account by defining the contact angle and slip length. The curve of the invasion pressure-water volume fraction is generated by modeling two-phase flow during a sudden drainage. The volume fraction of water restricted in the rough-walled fracture is calculated by integrating the water volume and dividing by the total cavity volume of the fracture while the two-phase flow is quasistatic. The effect of invasion pressure of crude oil, roughness of fracture wall, and wettability of the wall on two-phase flow in rough-walled fracture is evaluated.

  19. Tokunaga and Horton self-similarity for level set trees of Markov chains

    International Nuclear Information System (INIS)

    Zaliapin, Ilia; Kovchegov, Yevgeniy

    2012-01-01

    Highlights: ► Self-similar properties of the level set trees for Markov chains are studied. ► Tokunaga and Horton self-similarity are established for symmetric Markov chains and regular Brownian motion. ► Strong, distributional self-similarity is established for symmetric Markov chains with exponential jumps. ► It is conjectured that fractional Brownian motions are Tokunaga self-similar. - Abstract: The Horton and Tokunaga branching laws provide a convenient framework for studying self-similarity in random trees. The Horton self-similarity is a weaker property that addresses the principal branching in a tree; it is a counterpart of the power-law size distribution for elements of a branching system. The stronger Tokunaga self-similarity addresses so-called side branching. The Horton and Tokunaga self-similarity have been empirically established in numerous observed and modeled systems, and proven for two paradigmatic models: the critical Galton–Watson branching process with finite progeny and the finite-tree representation of a regular Brownian excursion. This study establishes the Tokunaga and Horton self-similarity for a tree representation of a finite symmetric homogeneous Markov chain. We also extend the concept of Horton and Tokunaga self-similarity to infinite trees and establish self-similarity for an infinite-tree representation of a regular Brownian motion. We conjecture that fractional Brownian motions are also Tokunaga and Horton self-similar, with self-similarity parameters depending on the Hurst exponent.

  20. Delineating Facies Spatial Distribution by Integrating Ensemble Data Assimilation and Indicator Geostatistics with Level Set Transformation.

    Energy Technology Data Exchange (ETDEWEB)

    Hammond, Glenn Edward; Song, Xuehang; Ye, Ming; Dai, Zhenxue; Zachara, John; Chen, Xingyuan

    2017-03-01

    A new approach is developed to delineate the spatial distribution of discrete facies (geological units that have unique distributions of hydraulic, physical, and/or chemical properties) conditioned not only on direct data (measurements directly related to facies properties, e.g., grain size distribution obtained from borehole samples) but also on indirect data (observations indirectly related to facies distribution, e.g., hydraulic head and tracer concentration). Our method integrates for the first time ensemble data assimilation with traditional transition probability-based geostatistics. The concept of level set is introduced to build shape parameterization that allows transformation between discrete facies indicators and continuous random variables. The spatial structure of different facies is simulated by indicator models using conditioning points selected adaptively during the iterative process of data assimilation. To evaluate the new method, a two-dimensional semi-synthetic example is designed to estimate the spatial distribution and permeability of two distinct facies from transient head data induced by pumping tests. The example demonstrates that our new method adequately captures the spatial pattern of facies distribution by imposing spatial continuity through conditioning points. The new method also reproduces the overall response in hydraulic head field with better accuracy compared to data assimilation with no constraints on spatial continuity on facies.

  1. Flipping for success: evaluating the effectiveness of a novel teaching approach in a graduate level setting.

    Science.gov (United States)

    Moraros, John; Islam, Adiba; Yu, Stan; Banow, Ryan; Schindelka, Barbara

    2015-02-28

    opportunities based on problem-solving activities and offer timely feedback/guidance to students. Yet in our study, this teaching style had its fair share of challenges, which were largely dependent on the use and management of technology. Despite these challenges, the Flipped Classroom proved to be a novel and effective teaching approach at the graduate level setting.

  2. 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)

  3. Sensitivity Analysis of features in tolerancing based on constraint function level sets

    International Nuclear Information System (INIS)

    Ziegler, Philipp; Wartzack, Sandro

    2015-01-01

    Usually, the geometry of the manufactured product inherently varies from the nominal geometry. This may negatively affect the product functions and properties (such as quality and reliability), as well as the assemblability of the single components. In order to avoid this, the geometric variation of these component surfaces and associated geometry elements (like hole axes) are restricted by tolerances. Since tighter tolerances lead to significant higher manufacturing costs, tolerances should be specified carefully. Therefore, the impact of deviating component surfaces on functions, properties and assemblability of the product has to be analyzed. As physical experiments are expensive, methods of statistical tolerance analysis tools are widely used in engineering design. Current tolerance simulation tools lack of an appropriate indicator for the impact of deviating component surfaces. In the adoption of Sensitivity Analysis methods, there are several challenges, which arise from the specific framework in tolerancing. This paper presents an approach to adopt Sensitivity Analysis methods on current tolerance simulations with an interface module, which bases on level sets of constraint functions for parameters of the simulation model. The paper is an extension and generalization of Ziegler and Wartzack [1]. Mathematical properties of the constraint functions (convexity, homogeneity), which are important for the computational costs of the Sensitivity Analysis, are shown. The practical use of the method is illustrated in a case study of a plain bearing. - Highlights: • Alternative definition of Deviation Domains. • Proof of mathematical properties of the Deviation Domains. • Definition of the interface between Deviation Domains and Sensitivity Analysis. • Sensitivity analysis of a gearbox to show the methods practical use

  4. Shape Reconstruction of Thin Electromagnetic Inclusions via Boundary Measurements: Level-Set Method Combined with the Topological Derivative

    Directory of Open Access Journals (Sweden)

    Won-Kwang Park

    2013-01-01

    Full Text Available An inverse problem for reconstructing arbitrary-shaped thin penetrable electromagnetic inclusions concealed in a homogeneous material is considered in this paper. For this purpose, the level-set evolution method is adopted. The topological derivative concept is incorporated in order to evaluate the evolution speed of the level-set functions. The results of the corresponding numerical simulations with and without noise are presented in this paper.

  5. Joint inversion of geophysical data using petrophysical clustering and facies deformation wth the level set technique

    Science.gov (United States)

    Revil, A.

    2015-12-01

    Geological expertise and petrophysical relationships can be brought together to provide prior information while inverting multiple geophysical datasets. The merging of such information can result in more realistic solution in the distribution of the model parameters, reducing ipse facto the non-uniqueness of the inverse problem. We consider two level of heterogeneities: facies, described by facies boundaries and heteroegenities inside each facies determined by a correlogram. In this presentation, we pose the geophysical inverse problem in terms of Gaussian random fields with mean functions controlled by petrophysical relationships and covariance functions controlled by a prior geological cross-section, including the definition of spatial boundaries for the geological facies. The petrophysical relationship problem is formulated as a regression problem upon each facies. The inversion of the geophysical data is performed in a Bayesian framework. We demonstrate the usefulness of this strategy using a first synthetic case for which we perform a joint inversion of gravity and galvanometric resistivity data with the stations located at the ground surface. The joint inversion is used to recover the density and resistivity distributions of the subsurface. In a second step, we consider the possibility that the facies boundaries are deformable and their shapes are inverted as well. We use the level set approach to perform such deformation preserving prior topological properties of the facies throughout the inversion. With the help of prior facies petrophysical relationships and topological characteristic of each facies, we make posterior inference about multiple geophysical tomograms based on their corresponding geophysical data misfits. The method is applied to a second synthetic case showing that we can recover the heterogeneities inside the facies, the mean values for the petrophysical properties, and, to some extent, the facies boundaries using the 2D joint inversion of

  6. 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...

  7. 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...

  8. FRAMEWORK FOR COMPARING SEGMENTATION ALGORITHMS

    Directory of Open Access Journals (Sweden)

    G. Sithole

    2015-05-01

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

  9. Underwater Object Segmentation Based on Optical Features

    Directory of Open Access Journals (Sweden)

    Zhe Chen

    2018-01-01

    Full Text Available Underwater optical environments are seriously affected by various optical inputs, such as artificial light, sky light, and ambient scattered light. The latter two can block underwater object segmentation tasks, since they inhibit the emergence of objects of interest and distort image information, while artificial light can contribute to segmentation. Artificial light often focuses on the object of interest, and, therefore, we can initially identify the region of target objects if the collimation of artificial light is recognized. Based on this concept, we propose an optical feature extraction, calculation, and decision method to identify the collimated region of artificial light as a candidate object region. Then, the second phase employs a level set method to segment the objects of interest within the candidate region. This two-phase structure largely removes background noise and highlights the outline of underwater objects. We test the performance of the method with diverse underwater datasets, demonstrating that it outperforms previous methods.

  10. MO-AB-BRA-01: A Global Level Set Based Formulation for Volumetric Modulated Arc Therapy

    Energy Technology Data Exchange (ETDEWEB)

    Nguyen, D; Lyu, Q; Ruan, D; O’Connor, D; Low, D; Sheng, K [Department of Radiation Oncology, University of California Los Angeles, Los Angeles, CA (United States)

    2016-06-15

    Purpose: The current clinical Volumetric Modulated Arc Therapy (VMAT) optimization is formulated as a non-convex problem and various greedy heuristics have been employed for an empirical solution, jeopardizing plan consistency and quality. We introduce a novel global direct aperture optimization method for VMAT to overcome these limitations. Methods: The global VMAT (gVMAT) planning was formulated as an optimization problem with an L2-norm fidelity term and an anisotropic total variation term. A level set function was used to describe the aperture shapes and adjacent aperture shapes were penalized to control MLC motion range. An alternating optimization strategy was implemented to solve the fluence intensity and aperture shapes simultaneously. Single arc gVMAT plans, utilizing 180 beams with 2° angular resolution, were generated for a glioblastoma multiforme (GBM), lung (LNG), and 2 head and neck cases—one with 3 PTVs (H&N3PTV) and one with 4 PTVs (H&N4PTV). The plans were compared against the clinical VMAT (cVMAT) plans utilizing two overlapping coplanar arcs. Results: The optimization of the gVMAT plans had converged within 600 iterations. gVMAT reduced the average max and mean OAR dose by 6.59% and 7.45% of the prescription dose. Reductions in max dose and mean dose were as high as 14.5 Gy in the LNG case and 15.3 Gy in the H&N3PTV case. PTV coverages (D95, D98, D99) were within 0.25% of the prescription dose. By globally considering all beams, the gVMAT optimizer allowed some beams to deliver higher intensities, yielding a dose distribution that resembles a static beam IMRT plan with beam orientation optimization. Conclusions: The novel VMAT approach allows for the search of an optimal plan in the global solution space and generates deliverable apertures directly. The single arc VMAT approach fully utilizes the digital linacs’ capability in dose rate and gantry rotation speed modulation. Varian Medical Systems, NIH grant R01CA188300, NIH grant R43CA183390.

  11. A finite element/level set model of polyurethane foam expansion and polymerization

    Energy Technology Data Exchange (ETDEWEB)

    Rao, Rekha R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Long, Kevin Nicholas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Roberts, Christine Cardinal [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Celina, Mathias C. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Brunini, Victor [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Soehnel, Melissa Marie [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Noble, David R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Tinsley, James [Honeywell Federal Manufacturing & Technologies, Kansas City, MO (United States); Mondy, Lisa [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-12-01

    Polyurethane foams are used widely for encapsulation and structural purposes because they are inexpensive, straightforward to process, amenable to a wide range of density variations (1 lb/ft3 - 50 lb/ft3), and able to fill complex molds quickly and effectively. Computational model of the filling and curing process are needed to reduce defects such as voids, out-of-specification density, density gradients, foam decomposition from high temperatures due to exotherms, and incomplete filling. This paper details the development of a computational fluid dynamics model of a moderate density PMDI structural foam, PMDI-10. PMDI is an isocyanate-based polyurethane foam, which is chemically blown with water. The polyol reacts with isocyanate to produces the polymer. PMDI- 10 is catalyzed giving it a short pot life: it foams and polymerizes to a solid within 5 minutes during normal processing. To achieve a higher density, the foam is over-packed to twice or more of its free rise density of 10 lb/ft3. The goal for modeling is to represent the expansion, filling of molds, and the polymerization of the foam. This will be used to reduce defects, optimize the mold design, troubleshoot the processed, and predict the final foam properties. A homogenized continuum model foaming and curing was developed based on reaction kinetics, documented in a recent paper; it uses a simplified mathematical formalism that decouples these two reactions. The chemo-rheology of PMDI is measured experimentally and fit to a generalized- Newtonian viscosity model that is dependent on the extent of cure, gas fraction, and temperature. The conservation equations, including the equations of motion, an energy balance, and three rate equations are solved via a stabilized finite element method. The equations are combined with a level set method to determine the location of the foam-gas interface as it evolves to fill the mold. Understanding the thermal history and loads on the foam due to exothermicity and oven

  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. Electrocardiogram ST-Segment Morphology Delineation Method Using Orthogonal Transformations.

    Directory of Open Access Journals (Sweden)

    Miha Amon

    Full Text Available Differentiation between ischaemic and non-ischaemic transient ST segment events of long term ambulatory electrocardiograms is a persisting weakness in present ischaemia detection systems. Traditional ST segment level measuring is not a sufficiently precise technique due to the single point of measurement and severe noise which is often present. We developed a robust noise resistant orthogonal-transformation based delineation method, which allows tracing the shape of transient ST segment morphology changes from the entire ST segment in terms of diagnostic and morphologic feature-vector time series, and also allows further analysis. For these purposes, we developed a new Legendre Polynomials based Transformation (LPT of ST segment. Its basis functions have similar shapes to typical transient changes of ST segment morphology categories during myocardial ischaemia (level, slope and scooping, thus providing direct insight into the types of time domain morphology changes through the LPT feature-vector space. We also generated new Karhunen and Lo ève Transformation (KLT ST segment basis functions using a robust covariance matrix constructed from the ST segment pattern vectors derived from the Long Term ST Database (LTST DB. As for the delineation of significant transient ischaemic and non-ischaemic ST segment episodes, we present a study on the representation of transient ST segment morphology categories, and an evaluation study on the classification power of the KLT- and LPT-based feature vectors to classify between ischaemic and non-ischaemic ST segment episodes of the LTST DB. Classification accuracy using the KLT and LPT feature vectors was 90% and 82%, respectively, when using the k-Nearest Neighbors (k = 3 classifier and 10-fold cross-validation. New sets of feature-vector time series for both transformations were derived for the records of the LTST DB which is freely available on the PhysioNet website and were contributed to the LTST DB. The

  14. Mixed segmentation

    DEFF Research Database (Denmark)

    Hansen, Allan Grutt; Bonde, Anders; Aagaard, Morten

    content analysis and audience segmentation in a single-source perspective. The aim is to explain and understand target groups in relation to, on the one hand, emotional response to commercials or other forms of audio-visual communication and, on the other hand, living preferences and personality traits...

  15. Direct measured systolic pressure gradients across the aorto-iliac segment in multiple-level-obstruction arteriosclerosis

    DEFF Research Database (Denmark)

    Noer, Ivan; Praestholm, J; Tønnesen, K H

    1981-01-01

    Patients with severe ischemia due to multi-level obstructions in the leg arteries both above and below the region were assessed preoperatively by intraarterial brachial and femoral artery pressure measurements. The systolic pressure drop along aorto-iliac obstructions was compared to the angiogra....... Due to large variations, however, the angiographic information was found to be useless in the individual patient. No difference in the pressure drop was found between cases in which rich and poor collateral networks were visualized....

  16. Carboxyhemoglobin levels of selected population segments in variously structured and polluted areas of North Rhine-Westphalia

    Energy Technology Data Exchange (ETDEWEB)

    Roscovanu, A.; Kraemer, U.B.; Baginski, B.; Dolgner, R.

    1985-03-01

    Measurements of carboxyhemoglobin (COHb)-content from about 13,000 inhabitants of various sites in western North Rhine-Westphalia are presented. Analyses were part of surveys on the effects of air pollution conducted between 1975 and 1980 in five designated, polluted areas. Determinations were executed in the Medical Institute for Environmental Hygiene, Duesseldorf, on behalf of the Ministry of Labor, Health and Social Administration. Analysis of blood samples for CO-content was performed by gas chromatography. Carboxyhemoglobin levels were calculated by reference to the individual hemoglobin levels. These surveys have been conducted during several years and included different seasons. Before 1977, fifty years old men were investigated. Until 1978, sixty years old men were studied. In 1979 and 1980, sixty years old women and ten years old children were additionally incorporated into the survey. Statistical analysis of data included variables which influence personal CO-burden such as smoking, and in the case of non-smokers indoor air exposure through passive smoking, use of gas facilities and heating in the flat, as well as occupational exposure. Besides, the influence of age, sex and location was considered. The average COHb-level of the populations under study was expressed as the median of the distribution. The distribution-free Mann-Whitney U-test served for assessment of differences between groups. As a further parameter, the percentage of the measurements greater than 2,5% COHb was chosen, because it was thought to be more relevant to risk populations, i.e. people suffering from Angina pectoris. As expected, tobacco smoking exerted the greatest influence on COHb-level. In non-smokers a trend, indicating a relationship between indoor air pollution and COHb-content could be observed.

  17. A two-level strategy to realize life-cycle production optimization in an operational setting

    NARCIS (Netherlands)

    Essen, van G.M.; Hof, Van den P.M.J.; Jansen, J.D.

    2012-01-01

    We present a two-level strategy to improve robustness against uncertainty and model errors in life-cycle flooding optimization. At the upper level, a physics-based large-scale reservoir model is used to determine optimal life-cycle injection and production profiles. At the lower level these profiles

  18. A two-level strategy to realize life-cycle production optimization in an operational setting

    NARCIS (Netherlands)

    Essen, van G.M.; Hof, Van den P.M.J.; Jansen, J.D.

    2013-01-01

    We present a two-level strategy to improve robustness against uncertainty and model errors in life-cycle flooding optimization. At the upper level, a physics-based large-scale reservoir model is used to determine optimal life-cycle injection and production profiles. At the lower level these profiles

  19. 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.

  20. Fluence map segmentation

    International Nuclear Information System (INIS)

    Rosenwald, J.-C.

    2008-01-01

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

  1. 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.

  2. A variational approach to multi-phase motion of gas, liquid and solid based on the level set method

    Science.gov (United States)

    Yokoi, Kensuke

    2009-07-01

    We propose a simple and robust numerical algorithm to deal with multi-phase motion of gas, liquid and solid based on the level set method [S. Osher, J.A. Sethian, Front propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulation, J. Comput. Phys. 79 (1988) 12; M. Sussman, P. Smereka, S. Osher, A level set approach for capturing solution to incompressible two-phase flow, J. Comput. Phys. 114 (1994) 146; J.A. Sethian, Level Set Methods and Fast Marching Methods, Cambridge University Press, 1999; S. Osher, R. Fedkiw, Level Set Methods and Dynamics Implicit Surface, Applied Mathematical Sciences, vol. 153, Springer, 2003]. In Eulerian framework, to simulate interaction between a moving solid object and an interfacial flow, we need to define at least two functions (level set functions) to distinguish three materials. In such simulations, in general two functions overlap and/or disagree due to numerical errors such as numerical diffusion. In this paper, we resolved the problem using the idea of the active contour model [M. Kass, A. Witkin, D. Terzopoulos, Snakes: active contour models, International Journal of Computer Vision 1 (1988) 321; V. Caselles, R. Kimmel, G. Sapiro, Geodesic active contours, International Journal of Computer Vision 22 (1997) 61; G. Sapiro, Geometric Partial Differential Equations and Image Analysis, Cambridge University Press, 2001; R. Kimmel, Numerical Geometry of Images: Theory, Algorithms, and Applications, Springer-Verlag, 2003] introduced in the field of image processing.

  3. Comparing Panelists' Understanding of Standard Setting across Multiple Levels of an Alternate Science Assessment

    Science.gov (United States)

    Hansen, Mary A.; Lyon, Steven R.; Heh, Peter; Zigmond, Naomi

    2013-01-01

    Large-scale assessment programs, including alternate assessments based on alternate achievement standards (AA-AAS), must provide evidence of technical quality and validity. This study provides information about the technical quality of one AA-AAS by evaluating the standard setting for the science component. The assessment was designed to have…

  4. Organizational factors related to low levels of sickness absence in a representative set of Swedish companies.

    Science.gov (United States)

    Stoetzer, Ulrich; Bergman, Peter; Aborg, Carl; Johansson, Gun; Ahlberg, Gunnel; Parmsund, Marianne; Svartengren, Magnus

    2014-01-01

    The aim of this qualitative study was to identify manageable organizational factors that could explain why some companies have low levels of sickness absence. There may be factors at company level that can be managed to influence levels of sickness absence, and promote health and a prosperous organization. 38 representative Swedish companies. The study included a total of 204 semi-structured interviews at 38 representative Swedish companies. Qualitative thematic analysis was applied to the interviews, primarily with managers, to indicate the organizational factors that characterize companies with low levels of sickness absence. The factors that were found to characterize companies with low levels of sickness absence concerned strategies and procedures for managing leadership, employee development, communication, employee participation and involvement, corporate values and visions, and employee health. The results may be useful in finding strategies and procedures to reduce levels of sickness absence and promote health. There is research at individual level on the reasons for sickness absence. This study tries to elevate the issue to an organizational level. The findings suggest that explicit strategies for managing certain organizational factors can reduce sickness absence and help companies to develop more health-promoting strategies.

  5. An Accurate Fire-Spread Algorithm in the Weather Research and Forecasting Model Using the Level-Set Method

    Science.gov (United States)

    Muñoz-Esparza, Domingo; Kosović, Branko; Jiménez, Pedro A.; Coen, Janice L.

    2018-04-01

    The level-set method is typically used to track and propagate the fire perimeter in wildland fire models. Herein, a high-order level-set method using fifth-order WENO scheme for the discretization of spatial derivatives and third-order explicit Runge-Kutta temporal integration is implemented within the Weather Research and Forecasting model wildland fire physics package, WRF-Fire. The algorithm includes solution of an additional partial differential equation for level-set reinitialization. The accuracy of the fire-front shape and rate of spread in uncoupled simulations is systematically analyzed. It is demonstrated that the common implementation used by level-set-based wildfire models yields to rate-of-spread errors in the range 10-35% for typical grid sizes (Δ = 12.5-100 m) and considerably underestimates fire area. Moreover, the amplitude of fire-front gradients in the presence of explicitly resolved turbulence features is systematically underestimated. In contrast, the new WRF-Fire algorithm results in rate-of-spread errors that are lower than 1% and that become nearly grid independent. Also, the underestimation of fire area at the sharp transition between the fire front and the lateral flanks is found to be reduced by a factor of ≈7. A hybrid-order level-set method with locally reduced artificial viscosity is proposed, which substantially alleviates the computational cost associated with high-order discretizations while preserving accuracy. Simulations of the Last Chance wildfire demonstrate additional benefits of high-order accurate level-set algorithms when dealing with complex fuel heterogeneities, enabling propagation across narrow fuel gaps and more accurate fire backing over the lee side of no fuel clusters.

  6. Elevated gamma glutamyl transferase levels are associated with the location of acute pulmonary embolism. Cross-sectional evaluation in hospital setting

    Directory of Open Access Journals (Sweden)

    Ozge Korkmaz

    Full Text Available ABSTRACT CONTEXT AND OBJECTIVE: The location of embolism is associated with clinical findings and disease severity in cases of acute pulmonary embolism. The level of gamma-glutamyl transferase increases under oxidative stress-related conditions. In this study, we investigated whether gamma-glutamyl transferase levels could predict the location of pulmonary embolism. DESIGN AND SETTING: Hospital-based cross-sectional study at Cumhuriyet University, Sivas, Turkey. METHODS : 120 patients who were diagnosed with acute pulmonary embolism through computed tomography-assisted pulmonary angiography were evaluated. They were divided into two main groups (proximally and distally located, and subsequently into subgroups according to thrombus localization as follows: first group (thrombus in main pulmonary artery; n = 9; second group (thrombus in main pulmonary artery branches; n = 71; third group (thrombus in pulmonary artery segmental branches; n = 34; and fourth group (thrombus in pulmonary artery subsegmental branches; n = 8. RESULTS : Gamma-glutamyl transferase levels on admission, heart rate, oxygen saturation, right ventricular dilatation/hypokinesia, pulmonary artery systolic pressure and cardiopulmonary resuscitation requirement showed prognostic significance in univariate analysis. The multivariate logistic regression model showed that gamma-glutamyl transferase level on admission (odds ratio, OR = 1.044; 95% confidence interval, CI: 1.011-1.079; P = 0.009 and pulmonary artery systolic pressure (OR = 1.063; 95% CI: 1.005-1.124; P = 0.033 remained independently associated with proximally localized thrombus in pulmonary artery. CONCLUSIONS : The findings revealed a significant association between increased existing embolism load in the pulmonary artery and increased serum gamma-glutamyl transferase levels.

  7. 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.

  8. 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.

  9. On piecewise constant level-set (PCLS) methods for the identification of discontinuous parameters in ill-posed problems

    International Nuclear Information System (INIS)

    De Cezaro, A; Leitão, A; Tai, X-C

    2013-01-01

    We investigate level-set-type methods for solving ill-posed problems with discontinuous (piecewise constant) coefficients. The goal is to identify the level sets as well as the level values of an unknown parameter function on a model described by a nonlinear ill-posed operator equation. The PCLS approach is used here to parametrize the solution of a given operator equation in terms of a L 2 level-set function, i.e. the level-set function itself is assumed to be a piecewise constant function. Two distinct methods are proposed for computing stable solutions of the resulting ill-posed problem: the first is based on Tikhonov regularization, while the second is based on the augmented Lagrangian approach with total variation penalization. Classical regularization results (Engl H W et al 1996 Mathematics and its Applications (Dordrecht: Kluwer)) are derived for the Tikhonov method. On the other hand, for the augmented Lagrangian method, we succeed in proving the existence of (generalized) Lagrangian multipliers in the sense of (Rockafellar R T and Wets R J-B 1998 Grundlehren der Mathematischen Wissenschaften (Berlin: Springer)). Numerical experiments are performed for a 2D inverse potential problem (Hettlich F and Rundell W 1996 Inverse Problems 12 251–66), demonstrating the capabilities of both methods for solving this ill-posed problem in a stable way (complicated inclusions are recovered without any a priori geometrical information on the unknown parameter). (paper)

  10. Area-level risk factors for adverse birth outcomes: trends in urban and rural settings

    OpenAIRE

    Kent, Shia T; McClure, Leslie A; Zaitchik, Ben F; Gohlke, Julia M

    2013-01-01

    Background Significant and persistent racial and income disparities in birth outcomes exist in the US. The analyses in this manuscript examine whether adverse birth outcome time trends and associations between area-level variables and adverse birth outcomes differ by urban?rural status. Methods Alabama births records were merged with ZIP code-level census measures of race, poverty, and rurality. B-splines were used to determine long-term preterm birth (PTB) and low birth weight (LBW) trends b...

  11. Representing the Fuzzy improved risk graph for determination of optimized safety integrity level in industrial setting

    Directory of Open Access Journals (Sweden)

    Z. Qorbali

    2013-12-01

    .Conclusion: as a result of establishing the presented method, identical levels in conventional risk graph table are replaced with different sublevels that not only increases the accuracy in determining the SIL, but also elucidates the effective factor in improving the safety level and consequently saves time and cost significantly. The proposed technique has been employed to develop the SIL of Tehran Refinery ISOMAX Center. IRG and FIRG results have been compared to clarify the efficacy and importance of the proposed method

  12. 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.

  13. On the Level Set of a Function with Degenerate Minimum Point

    Directory of Open Access Journals (Sweden)

    Yasuhiko Kamiyama

    2015-01-01

    Full Text Available For n≥2, let M be an n-dimensional smooth closed manifold and f:M→R a smooth function. We set minf(M=m and assume that m is attained by unique point p∈M such that p is a nondegenerate critical point. Then the Morse lemma tells us that if a is slightly bigger than m, f-1(a is diffeomorphic to Sn-1. In this paper, we relax the condition on p from being nondegenerate to being an isolated critical point and obtain the same consequence. Some application to the topology of polygon spaces is also included.

  14. CUDA based Level Set Method for 3D Reconstruction of Fishes from Large Acoustic Data

    DEFF Research Database (Denmark)

    Sharma, Ojaswa; Anton, François

    2009-01-01

    Acoustic images present views of underwater dynamics, even in high depths. With multi-beam echo sounders (SONARs), it is possible to capture series of 2D high resolution acoustic images. 3D reconstruction of the water column and subsequent estimation of fish abundance and fish species identificat...... of suppressing threshold and show its convergence as the evolution proceeds. We also present a GPU based streaming computation of the method using NVIDIA's CUDA framework to handle large volume data-sets. Our implementation is optimised for memory usage to handle large volumes....

  15. Intra-cameral level of ganciclovir gel, 0.15% following topical application for cytomegalovirus anterior segment infection: A pilot study.

    Science.gov (United States)

    Waduthantri, Samanthila; Zhou, Lei; Chee, Soon-Phaik

    2018-01-01

    To investigate the intra-cameral level of ganciclovir following topical application of ganciclovir gel, 0.15% for cytomegalovirus (CMV) anterior segment infection. Non-randomized, prospective, interventional clinical study. Patients with active CMV anterior segment infection seen at Singapore National Eye Centre, confirmed by positive CMV real time PCR (RT-PCR) of the aqueous humor, that had not been treated with any form of ganciclovir in the preceding 1 month were recruited. They were treated with ganciclovir gel, 0.15% 1cc 5 times a day. Following 6 weeks of treatment, CMV load in the aqueous humor was measured using CMV RT-PCR and the ganciclovir drug levels in tears and aqueous humor were measured using high-performance liquid chromatography-mass spectrometry. The clinical features of the disease activity and the central corneal thickness (CCT) were recorded at the baseline and post-treatment. There were 29 eyes of 29 patients, of which 23 eyes had CMV anterior uveitis and 6 eyes had CMV endotheliitis. At the end of week 6, 26 eyes had undetectable CMV titre in the aqueous humor and no anterior chamber (AC) activity. Two patients had an increased CMV titre and increased AC inflammation. Both of these patients were non-compliant with the treatment. One patient had a reduced CMV titre in the aqueous humor with minimal AC inflammation. The mean ganciclovir concentration in the aqueous humor and the tears were 17.4 ± 30.6 ng/ml and 20,420.9 ± 33,120.8 ng/ml respectively. Mean CCT was 552.2 ± 42.3 microns. There was a weak correlation between the ganciclovir concentration in the aqueous humor and CCT (Spearmen's r = + 0.42, p = 0.025). There was no significant correlation between the ganiclovir concentration in the tears and CCT (Spearmen's r = + 0.39, p = 0.11). Ganciclovir levels in the aqueous humor was below the 50% inhibitory dose (ID50) for CMV replication, following topical application of the ganciclovir gel, 0.15%. SingHealth Centralized Institutional

  16. 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. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Area-level risk factors for adverse birth outcomes: trends in urban and rural settings.

    Science.gov (United States)

    Kent, Shia T; McClure, Leslie A; Zaitchik, Ben F; Gohlke, Julia M

    2013-06-10

    Significant and persistent racial and income disparities in birth outcomes exist in the US. The analyses in this manuscript examine whether adverse birth outcome time trends and associations between area-level variables and adverse birth outcomes differ by urban-rural status. Alabama births records were merged with ZIP code-level census measures of race, poverty, and rurality. B-splines were used to determine long-term preterm birth (PTB) and low birth weight (LBW) trends by rurality. Logistic regression models were used to examine differences in the relationships between ZIP code-level percent poverty or percent African-American with either PTB or LBW. Interactions with rurality were examined. Population dense areas had higher adverse birth outcome rates compared to other regions. For LBW, the disparity between population dense and other regions increased during the 1991-2005 time period, and the magnitude of the disparity was maintained through 2010. Overall PTB and LBW rates have decreased since 2006, except within isolated rural regions. The addition of individual-level socioeconomic or race risk factors greatly attenuated these geographical disparities, but isolated rural regions maintained increased odds of adverse birth outcomes. ZIP code-level percent poverty and percent African American both had significant relationships with adverse birth outcomes. Poverty associations remained significant in the most population-dense regions when models were adjusted for individual-level risk factors. Population dense urban areas have heightened rates of adverse birth outcomes. High-poverty African American areas have higher odds of adverse birth outcomes in urban versus rural regions. These results suggest there are urban-specific social or environmental factors increasing risk for adverse birth outcomes in underserved communities. On the other hand, trends in PTBs and LBWs suggest interventions that have decreased adverse birth outcomes elsewhere may not be reaching

  18. 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.

  19. 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…

  20. The Daily Events and Emotions of Master's-Level Family Therapy Trainees in Off-Campus Practicum Settings

    Science.gov (United States)

    Edwards, Todd M.; Patterson, Jo Ellen

    2012-01-01

    The Day Reconstruction Method (DRM) was used to assess the daily events and emotions of one program's master's-level family therapy trainees in off-campus practicum settings. This study examines the DRM reports of 35 family therapy trainees in the second year of their master's program in marriage and family therapy. Four themes emerged from the…

  1. Activity Sets in Multi-Organizational Ecologies : A Project-Level Perspective on Sustainable Energy Innovations

    NARCIS (Netherlands)

    Gerrit Willem Ziggers; Kristina Manser; Bas Hillebrand; Paul Driessen; Josée Bloemer

    2014-01-01

    Complex innovations involve multi-organizational ecologies consisting of a myriad of different actors. This study investigates how innovation activities can be interpreted in the context of multi-organizational ecologies. Taking a project-level perspective, this study proposes a typology of four

  2. 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…

  3. ADVANCED CLUSTER BASED IMAGE SEGMENTATION

    Directory of Open Access Journals (Sweden)

    D. Kesavaraja

    2011-11-01

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

  4. 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.

  5. Segmentation of complex document

    Directory of Open Access Journals (Sweden)

    Souad Oudjemia

    2014-06-01

    Full Text Available In this paper we present a method for segmentation of documents image with complex structure. This technique based on GLCM (Grey Level Co-occurrence Matrix used to segment this type of document in three regions namely, 'graphics', 'background' and 'text'. Very briefly, this method is to divide the document image, in block size chosen after a series of tests and then applying the co-occurrence matrix to each block in order to extract five textural parameters which are energy, entropy, the sum entropy, difference entropy and standard deviation. These parameters are then used to classify the image into three regions using the k-means algorithm; the last step of segmentation is obtained by grouping connected pixels. Two performance measurements are performed for both graphics and text zones; we have obtained a classification rate of 98.3% and a Misclassification rate of 1.79%.

  6. Lung Tumor Segmentation Using Electric Flow Lines for Graph Cuts

    DEFF Research Database (Denmark)

    Hollensen, Christian; Cannon, George; Cannon, Donald

    2012-01-01

    are normally only used for correction of movements. The method uses graphs based on electric flow lines. The method offers several advantages when trying to replicate manual segmentations. The method gave a dice coefficient of 0.85 and performed better than level set methods and deformable registration....

  7. Lung segmentation from HRCT using united geometric active contours

    Science.gov (United States)

    Liu, Junwei; Li, Chuanfu; Xiong, Jin; Feng, Huanqing

    2007-12-01

    Accurate lung segmentation from high resolution CT images is a challenging task due to various detail tracheal structures, missing boundary segments and complex lung anatomy. One popular method is based on gray-level threshold, however its results are usually rough. A united geometric active contours model based on level set is proposed for lung segmentation in this paper. Particularly, this method combines local boundary information and region statistical-based model synchronously: 1) Boundary term ensures the integrality of lung tissue.2) Region term makes the level set function evolve with global characteristic and independent on initial settings. A penalizing energy term is introduced into the model, which forces the level set function evolving without re-initialization. The method is found to be much more efficient in lung segmentation than other methods that are only based on boundary or region. Results are shown by 3D lung surface reconstruction, which indicates that the method will play an important role in the design of computer-aided diagnostic (CAD) system.

  8. Flipping for success: evaluating the effectiveness of a novel teaching approach in a graduate level setting

    OpenAIRE

    Moraros, John; Islam, Adiba; Yu, Stan; Banow, Ryan; Schindelka, Barbara

    2015-01-01

    Background Flipped Classroom is a model that?s quickly gaining recognition as a novel teaching approach among health science curricula. The purpose of this study was four-fold and aimed to compare Flipped Classroom effectiveness ratings with: 1) student socio-demographic characteristics, 2) student final grades, 3) student overall course satisfaction, and 4) course pre-Flipped Classroom effectiveness ratings. Methods The participants in the study consisted of 67 Masters-level graduate student...

  9. The Kinematics and Spondylosis of the Lumbar Spine Vary Depending on the Levels of Motion Segments in Individuals With Low Back Pain.

    Science.gov (United States)

    Basques, Bryce A; Espinoza Orías, Alejandro A; Shifflett, Grant D; Fice, Michael P; Andersson, Gunnar B; An, Howard S; Inoue, Nozomu

    2017-07-01

    A prospective cohort study. The aim of this study was to identify associations of spondylotic and kinematic changes with low back pain (LBP). The ability to characterize and differentiate the biomechanics of both the symptomatic and asymptomatic lumbar spine is crucial to alleviate the sparse literature on the association of lumbar spine biomechanics and LBP. Lumbar dynamic plain radiographs (flexion-extension), dynamic computed tomography (CT) scanning (axial rotation, disc height), and magnetic resonance imaging (MRI, disc and facet degeneration grades) were obtained for each subject. These parameters were compared between symptomatic and control groups using Student t test and multivariate logistic regression, which controlled for patient age and sex and identified spinal parameters that were independently associated with symptomatic LBP. Disc grade and mean segmental motion by level were tested by one-way analysis of variance (ANOVA). Ninety-nine volunteers (64 asymptomatic/35 LBP) were prospectively recruited. Mean age was 37.3 ± 10.1 years and 55% were male. LBP showed association with increased L5/S1 translation [odds ratio (OR) 1.63 per mm, P = 0.005], decreased flexion-extension motion at L1/L2 (OR 0.87 per degree, P = 0.036), L2/L3 (OR 0.88 per degree, P = 0.036), and L4/L5 (OR 0.87 per degree, P = 0.020), increased axial rotation at L4/L5 (OR 2.11 per degree, P = 0.032), decreased disc height at L3/L4 (OR 0.52 per mm, P = 0.008) and L4/L5 (OR 0.37 per mm, p  0.05). In symptomatic individuals, L4/L5 and L5/S1 levels were affected by spondylosis and kinematic changes. This study clarifies the relationships between kinematic alterations and LBP, mostly observed at the above-mentioned segments. N/A.

  10. A highly efficient 3D level-set grain growth algorithm tailored for ccNUMA architecture

    Science.gov (United States)

    Mießen, C.; Velinov, N.; Gottstein, G.; Barrales-Mora, L. A.

    2017-12-01

    A highly efficient simulation model for 2D and 3D grain growth was developed based on the level-set method. The model introduces modern computational concepts to achieve excellent performance on parallel computer architectures. Strong scalability was measured on cache-coherent non-uniform memory access (ccNUMA) architectures. To achieve this, the proposed approach considers the application of local level-set functions at the grain level. Ideal and non-ideal grain growth was simulated in 3D with the objective to study the evolution of statistical representative volume elements in polycrystals. In addition, microstructure evolution in an anisotropic magnetic material affected by an external magnetic field was simulated.

  11. Brookhaven segment interconnect

    International Nuclear Information System (INIS)

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

    1983-01-01

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

  12. Planning and delivering high doses to targets surrounding the spinal cord at the lower neck and upper mediastinal levels: static beam-segmentation technique executed with a multileaf collimator

    International Nuclear Information System (INIS)

    Neve, W. de; Wagter, C. de; Jaeger, K. de; Thienpont, M.; Colle, C.; Derycke, S.; Schelfhout, J.

    1996-01-01

    Background and purpose. It remains a technical challenge to limit the dose to the spinal cord below tolerance if, in head and neck or thyroid cancer, the planning target volume reaches to a level below the shoulders. In order to avoid these dose limitations, we developed a standard plan involving Beam Intensity Modulation (BIM) executed by a static technique of beam segmentation. In this standard plan, many machine parameters (gantry angles, couch position, relative beam and segment weights) as well as the beam segmentation rules were identical for all patients. Materials and methods. The standard plan involved: the use of static beams with a single isocenter; BIM by field segmentation executable with a standard Philips multileaf collimator; virtual simulation and dose computation on a general 3D-planning system (Sherouse's GRATIS[reg]); heuristic computation of segment intensities and optimization (improving the dose distribution and reducing the execution time) by human intelligence. The standard plan used 20 segments spread over 8 gantry angles plus 2 non-segmented wedged beams (2 gantry angles). Results. The dose that could be achieved at the lowest target voxel, without exceeding tolerance of the spinal cord (50 Gy at highest voxel) was 70-80 Gy. The in-target 3D dose-inhomogeneity was ∼25%. The shortest time of execution of a treatment (22 segments) on a patient (unpublished) was 25 min. Conclusions. A heuristic model has been developed and investigated to obtain a 3D concave dose distribution applicable to irradiate targets in the lower neck and upper mediastinal regions. The technique spares efficiently the spinal cord and allows the delivery of higher target doses than with conventional techniques. It can be planned as a standard plan using conventional 3D-planning technology. The routine clinical implementation is performed with commercially available equipment, however, at the expense of extended execution times

  13. 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.

  14. Job satisfaction in nurses working in tertiary level health care settings of Islamabad, Pakistan.

    Science.gov (United States)

    Bahalkani, Habib Akhtar; Kumar, Ramesh; Lakho, Abdul Rehman; Mahar, Benazir; Mazhar, Syeda Batool; Majeed, Abdul

    2011-01-01

    Job satisfaction greatly determines the productivity and efficiency of human resource for health. It literally means: 'the extent to which Health Professionals like or dislike their jobs'. Job satisfaction is said to be linked with employee's work environment, job responsibilities, and powers; and time pressure among various health professionals. As such it affects employee's organizational commitment and consequently the quality of health services. Objective of this study was to determine the level of job satisfaction and factors influencing it among nurses in a public sector hospital of Islamabad. A cross sectional study with self-administered structured questionnaire was conducted in the federal capital of Pakistan, Islamabad. Sample included 56 qualified nurses working in a tertiary care hospital. Overall 86% respondents were dissatisfied with about 26% highly dissatisfied with their job. The work environments, poor fringe benefits, dignity, responsibility given at workplace and time pressure were reason for dissatisfaction. Poor work environment, low salaries, lack of training opportunities, proper supervision, time pressure and financial rewards reported by the respondents. Our findings state a low level of overall satisfaction among workers in a public sector tertiary care health organization in Islamabad. Most of this dissatisfaction is caused by poor salaries, not given the due respect, poor work environment, unbalanced responsibilities with little overall control, time pressure, patient care and lack of opportunities for professional development.

  15. 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

    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. Compare the association between regional poverty with self-reported unmet need, a marker of health care access, by rural/urban setting. Multilevel, cross-sectional analysis of a state-representative sample of 39,953 adults stratified by rural/urban status, linked at the county level to data describing contextual characteristics. Weighted random intercept models examined the independent association of regional poverty with unmet needs, controlling for a range of contextual and individual-level characteristics. The unadjusted association between regional poverty levels and unmet needs was similar in both rural (OR = 1.06 [95% CI, 1.04-1.08]) and urban (OR = 1.03 [1.02-1.05]) settings. Adjusting for other contextual characteristics increased the size of the association in both rural (OR = 1.11 [1.04-1.19]) and urban (OR = 1.11 [1.05-1.18]) settings. Further adjustment for individual characteristics had little additional effect in rural (OR = 1.10 [1.00-1.20]) or urban (OR = 1.11 [1.01-1.22]) settings. To better meet the health care needs of all Americans, health care systems in areas with high regional poverty should acknowledge the relationship between poverty and unmet health care needs. Investments, or other interventions, that reduce regional poverty may be useful strategies for improving health through better access to health care. © 2010 National Rural Health Association.

  16. Comparing of goal setting strategy with group education method to increase physical activity level: A randomized trial.

    Science.gov (United States)

    Jiryaee, Nasrin; Siadat, Zahra Dana; Zamani, Ahmadreza; Taleban, Roya

    2015-10-01

    Designing an intervention to increase physical activity is important to be based on the health care settings resources and be acceptable by the subject group. This study was designed to assess and compare the effect of the goal setting strategy with a group education method on increasing the physical activity of mothers of children aged 1 to 5. Mothers who had at least one child of 1-5 years were randomized into two groups. The effect of 1) goal-setting strategy and 2) group education method on increasing physical activity was assessed and compared 1 month and 3 months after the intervention. Also, the weight, height, body mass index (BMI), waist and hip circumference, and well-being were compared between the two groups before and after the intervention. Physical activity level increased significantly after the intervention in the goal-setting group and it was significantly different between the two groups after intervention (P goal-setting group after the intervention. In the group education method, only the well-being score improved significantly (P goal-setting strategy to boost physical activity, improving the state of well-being and decreasing BMI, waist, and hip circumference.

  17. Comparing of goal setting strategy with group education method to increase physical activity level: A randomized trial

    Directory of Open Access Journals (Sweden)

    Nasrin Jiryaee

    2015-01-01

    Full Text Available Background: Designing an intervention to increase physical activity is important to be based on the health care settings resources and be acceptable by the subject group. This study was designed to assess and compare the effect of the goal setting strategy with a group education method on increasing the physical activity of mothers of children aged 1 to 5. Materials and Methods: Mothers who had at least one child of 1-5 years were randomized into two groups. The effect of 1 goal-setting strategy and 2 group education method on increasing physical activity was assessed and compared 1 month and 3 months after the intervention. Also, the weight, height, body mass index (BMI, waist and hip circumference, and well-being were compared between the two groups before and after the intervention. Results: Physical activity level increased significantly after the intervention in the goal-setting group and it was significantly different between the two groups after intervention (P < 0.05. BMI, waist circumference, hip circumference, and well-being score were significantly different in the goal-setting group after the intervention. In the group education method, only the well-being score improved significantly (P < 0.05. Conclusion: Our study presented the effects of using the goal-setting strategy to boost physical activity, improving the state of well-being and decreasing BMI, waist, and hip circumference.

  18. A possible methodological approach to setting up control level of radiation factors

    International Nuclear Information System (INIS)

    Devyatajkin, E.V.; Abramov, Yu.V.

    1986-01-01

    The mathematical formalization of the concept of control levels (CL) which enables one to obtain CL numerical values of controllable parameters required for rapid control purposes is described. The initial data for the assessment of environmental radioactivity are the controllable parameter values that is practical characteristic of controllable radiation factor showing technically measurable or calculation value. The controllable parameters can be divided into two classes depending on the degree of radiation effect on a man: possessing additivity properties (dosimetric class) and non-possessing (radiation class, which comprises the results of control of medium alteration dynamics, equipment operation safety, completeness of protection measures performance). The CL calculation formulas with account for requirements of radiation safety standards (RSS-76) are presented

  19. 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

  20. High Levels of Post-Abortion Complication in a Setting Where Abortion Service Is Not Legalized.

    Directory of Open Access Journals (Sweden)

    Tadele Melese

    Full Text Available 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

  1. Setting up experimental incineration system for low-level radioactive samples and combustion experiments

    International Nuclear Information System (INIS)

    Yumoto, Yasuhiro; Hanafusa, Tadashi; Nagamatsu, Tomohiro; Okada, Shigeru

    1997-01-01

    An incineration system was constructed which were composed of a combustion furnace (AP-150R), a cyclone dust collector, radioisotope trapping and measurement apparatus and a radioisotope storage room built in the first basement of the Radioisotope Center. Low level radioactive samples (LLRS) used for the combustion experiment were composed of combustible material or semi-combustible material containing 500 kBq of 99m TcO 4 or 23.25 kBq of 131 INa. The distribution of radioisotopes both in the inside and outside of combustion furnace were estimated. We measured radioactivity of a smoke duct gas in terminal exit of the exhaust port. In case of combustion of LLRS containing 99m TcO 4 or 131 INa, concentration of radioisotopes at the exhaust port showed less than legal concentration limit of these radioisotopes. In cases of combustion of LLRS containing 99m TcO 4 or 131 INa, decontamination factors of the incineration system were 120 and 1.1, respectively. (author)

  2. 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 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. Combinational pixel-by-pixel and object-level classifying, segmenting, and agglomerating in performing quantitative image analysis that distinguishes between healthy non-cancerous and cancerous cell nuclei and delineates nuclear, cytoplasm, and stromal material objects from stained biological tissue materials

    Science.gov (United States)

    Boucheron, Laura E

    2013-07-16

    Quantitative object and spatial arrangement-level analysis of tissue are detailed using expert (pathologist) input to guide the classification process. A two-step method is disclosed for imaging tissue, by classifying one or more biological materials, e.g. nuclei, cytoplasm, and stroma, in the tissue into one or more identified classes on a pixel-by-pixel basis, and segmenting the identified classes to agglomerate one or more sets of identified pixels into segmented regions. Typically, the one or more biological materials comprises nuclear material, cytoplasm material, and stromal material. The method further allows a user to markup the image subsequent to the classification to re-classify said materials. The markup is performed via a graphic user interface to edit designated regions in the image.

  4. Segmentation of urinary bladder in CT Urography (CTU) using CLASS

    Science.gov (United States)

    Hadjiiski, Lubomir; Chan, Heang-Ping; Law, Yuen; Cohan, Richard H.; Caoili, Elaine M.; Cho, Hyun-Chong; Zhou, Chuan; Wei, Jun

    2012-03-01

    We are developing a computerized system for bladder segmentation on CTU, as a critical component for computer aided diagnosis of bladder cancer. A challenge for bladder segmentation is the presence of regions without contrast (NC) and filled with IV contrast (C). We are developing a Conjoint Level set Analysis and Segmentation System (CLASS) specifically for this application. CLASS performs a series of image processing tasks: preprocessing, initial segmentation, and 3D and 2D level set segmentation and post-processing, designed according to the characteristics of the bladder in CTU. The NC and the C regions of the bladder were segmented separately in CLASS. The final contour is obtained in the post-processing stage by the union of the NC and C contours. Seventy bladders (31 containing lesions, 24 containing wall thickening, and 15 normal) were segmented. The performance of CLASS was assessed by rating the quality of the contours on a 5-point scale (1= "very poor", 3= "fair", 5 = "excellent"). For the 53 partially contrast-filled bladders, the average quality ratings for the 53 NC and 53 C regions were 4.0+/-0.7 and 4.0+/-1.0, respectively. 46 NC and 41 C regions were given quality ratings of 4 or above. Only 2 NC and 5 C regions had ratings under 3. The average quality ratings for the remaining 12 completely no contrast (NC) and 5 completely contrast-filled (C) bladder contours were 3.3+/-1.0 and 3.4+/-0.5, respectively. After combining the NC and C contours for each of the 70 bladders, 46 had quality ratings of 4 or above. Only 4 had ratings under 3. The average quality rating was 3.8+/-0.7. The results demonstrate the potential of CLASS for automated segmentation of the bladder.

  5. Three-Dimensional Simulation of DRIE Process Based on the Narrow Band Level Set and Monte Carlo Method

    Directory of Open Access Journals (Sweden)

    Jia-Cheng Yu

    2018-02-01

    Full Text Available A three-dimensional topography simulation of deep reactive ion etching (DRIE is developed based on the narrow band level set method for surface evolution and Monte Carlo method for flux distribution. The advanced level set method is implemented to simulate the time-related movements of etched surface. In the meanwhile, accelerated by ray tracing algorithm, the Monte Carlo method incorporates all dominant physical and chemical mechanisms such as ion-enhanced etching, ballistic transport, ion scattering, and sidewall passivation. The modified models of charged particles and neutral particles are epitomized to determine the contributions of etching rate. The effects such as scalloping effect and lag effect are investigated in simulations and experiments. Besides, the quantitative analyses are conducted to measure the simulation error. Finally, this simulator will be served as an accurate prediction tool for some MEMS fabrications.

  6. 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

    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...... 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...

  7. Quasi-min-max Fuzzy MPC of UTSG Water Level Based on Off-Line Invariant Set

    Science.gov (United States)

    Liu, Xiangjie; Jiang, Di; Lee, Kwang Y.

    2015-10-01

    In a nuclear power plant, the water level of the U-tube steam generator (UTSG) must be maintained within a safe range. Traditional control methods encounter difficulties due to the complexity, strong nonlinearity and “swell and shrink” effects, especially at low power levels. A properly designed robust model predictive control can well solve this problem. In this paper, a quasi-min-max fuzzy model predictive controller is developed for controlling the constrained UTSG system. While the online computational burden could be quite large for the real-time control, a bank of ellipsoid invariant sets together with the corresponding feedback control laws are obtained by off-line solving linear matrix inequalities (LMIs). Based on the UTSG states, the online optimization is simplified as a constrained optimization problem with a bisection search for the corresponding ellipsoid invariant set. Simulation results are given to show the effectiveness of the proposed controller.

  8. Computing segmentations directly from x-ray projection data via parametric deformable curves

    DEFF Research Database (Denmark)

    Dahl, Vedrana Andersen; Dahl, Anders Bjorholm; Hansen, Per Christian

    2018-01-01

    We describe an efficient algorithm that computes a segmented reconstruction directly from x-ray projection data. Our algorithm uses a parametric curve to define the segmentation. Unlike similar approaches which are based on level-sets, our method avoids a pixel or voxel grid; hence the number...... of unknowns is reduced to the set of points that define the curve, and attenuation coefficients of the segments. Our current implementation uses a simple closed curve and is capable of separating one object from the background. However, our basic algorithm can be applied to an arbitrary topology and multiple...

  9. Numerical simulation of interface movement in gas-liquid two-phase flows with Level Set method

    International Nuclear Information System (INIS)

    Li Huixiong; Chinese Academy of Sciences, Beijing; Deng Sheng; Chen Tingkuan; Zhao Jianfu; Wang Fei

    2005-01-01

    Numerical simulation of gas-liquid two-phase flow and heat transfer has been an attractive work for a quite long time, but still remains as a knotty difficulty due to the inherent complexities of the gas-liquid two-phase flow resulted from the existence of moving interfaces with topology changes. This paper reports the effort and the latest advances that have been made by the authors, with special emphasis on the methods for computing solutions to the advection equation of the Level set function, which is utilized to capture the moving interfaces in gas-liquid two-phase flows. Three different schemes, i.e. the simple finite difference scheme, the Superbee-TVD scheme and the 5-order WENO scheme in combination with the Runge-Kutta method are respectively applied to solve the advection equation of the Level Set. A numerical procedure based on the well-verified SIMPLER method is employed to numerically calculate the momentum equations of the two-phase flow. The above-mentioned three schemes are employed to simulate the movement of four typical interfaces under 5 typical flowing conditions. Analysis of the numerical results shows that the 5-order WENO scheme and the Superbee-TVD scheme are much better than the simple finite difference scheme, and the 5-order WENO scheme is the best to compute solutions to the advection equation of the Level Set. The 5-order WENO scheme will be employed as the main scheme to get solutions to the advection equations of the Level Set when gas-liquid two-phase flows are numerically studied in the future. (authors)

  10. 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

  11. Comparison of different statistical methods for estimation of extreme sea levels with wave set-up contribution

    Science.gov (United States)

    Kergadallan, Xavier; Bernardara, Pietro; Benoit, Michel; Andreewsky, Marc; Weiss, Jérôme

    2013-04-01

    Estimating the probability of occurrence of extreme sea levels is a central issue for the protection of the coast. Return periods of sea level with wave set-up contribution are estimated here in one site : Cherbourg in France in the English Channel. The methodology follows two steps : the first one is computation of joint probability of simultaneous wave height and still sea level, the second one is interpretation of that joint probabilities to assess a sea level for a given return period. Two different approaches were evaluated to compute joint probability of simultaneous wave height and still sea level : the first one is multivariate extreme values distributions of logistic type in which all components of the variables become large simultaneously, the second one is conditional approach for multivariate extreme values in which only one component of the variables have to be large. Two different methods were applied to estimate sea level with wave set-up contribution for a given return period : Monte-Carlo simulation in which estimation is more accurate but needs higher calculation time and classical ocean engineering design contours of type inverse-FORM in which the method is simpler and allows more complex estimation of wave setup part (wave propagation to the coast for example). We compare results from the two different approaches with the two different methods. To be able to use both Monte-Carlo simulation and design contours methods, wave setup is estimated with an simple empirical formula. We show advantages of the conditional approach compared to the multivariate extreme values approach when extreme sea-level occurs when either surge or wave height is large. We discuss the validity of the ocean engineering design contours method which is an alternative when computation of sea levels is too complex to use Monte-Carlo simulation method.

  12. Document flow segmentation for business applications

    Science.gov (United States)

    Daher, Hani; Belaïd, Abdel

    2013-12-01

    The aim of this paper is to propose a document flow supervised segmentation approach applied to real world heterogeneous documents. Our algorithm treats the flow of documents as couples of consecutive pages and studies the relationship that exists between them. At first, sets of features are extracted from the pages where we propose an approach to model the couple of pages into a single feature vector representation. This representation will be provided to a binary classifier which classifies the relationship as either segmentation or continuity. In case of segmentation, we consider that we have a complete document and the analysis of the flow continues by starting a new document. In case of continuity, the couple of pages are assimilated to the same document and the analysis continues on the flow. If there is an uncertainty on whether the relationship between the couple of pages should be classified as a continuity or segmentation, a rejection is decided and the pages analyzed until this point are considered as a "fragment". The first classification already provides good results approaching 90% on certain documents, which is high at this level of the system.

  13. Single-step reinitialization and extending algorithms for level-set based multi-phase flow simulations

    Science.gov (United States)

    Fu, Lin; Hu, Xiangyu Y.; Adams, Nikolaus A.

    2017-12-01

    We propose efficient single-step formulations for reinitialization and extending algorithms, which are critical components of level-set based interface-tracking methods. The level-set field is reinitialized with a single-step (non iterative) "forward tracing" algorithm. A minimum set of cells is defined that describes the interface, and reinitialization employs only data from these cells. Fluid states are extrapolated or extended across the interface by a single-step "backward tracing" algorithm. Both algorithms, which are motivated by analogy to ray-tracing, avoid multiple block-boundary data exchanges that are inevitable for iterative reinitialization and extending approaches within a parallel-computing environment. The single-step algorithms are combined with a multi-resolution conservative sharp-interface method and validated by a wide range of benchmark test cases. We demonstrate that the proposed reinitialization method achieves second-order accuracy in conserving the volume of each phase. The interface location is invariant to reapplication of the single-step reinitialization. Generally, we observe smaller absolute errors than for standard iterative reinitialization on the same grid. The computational efficiency is higher than for the standard and typical high-order iterative reinitialization methods. We observe a 2- to 6-times efficiency improvement over the standard method for serial execution. The proposed single-step extending algorithm, which is commonly employed for assigning data to ghost cells with ghost-fluid or conservative interface interaction methods, shows about 10-times efficiency improvement over the standard method while maintaining same accuracy. Despite their simplicity, the proposed algorithms offer an efficient and robust alternative to iterative reinitialization and extending methods for level-set based multi-phase simulations.

  14. Metrics for image segmentation

    Science.gov (United States)

    Rees, Gareth; Greenway, Phil; Morray, Denise

    1998-07-01

    An important challenge in mapping image-processing techniques onto applications is the lack of quantitative performance measures. From a systems engineering perspective these are essential if system level requirements are to be decomposed into sub-system requirements which can be understood in terms of algorithm selection and performance optimization. Nowhere in computer vision is this more evident than in the area of image segmentation. This is a vigorous and innovative research activity, but even after nearly two decades of progress, it remains almost impossible to answer the question 'what would the performance of this segmentation algorithm be under these new conditions?' To begin to address this shortcoming, we have devised a well-principled metric for assessing the relative performance of two segmentation algorithms. This allows meaningful objective comparisons to be made between their outputs. It also estimates the absolute performance of an algorithm given ground truth. Our approach is an information theoretic one. In this paper, we describe the theory and motivation of our method, and present practical results obtained from a range of state of the art segmentation methods. We demonstrate that it is possible to measure the objective performance of these algorithms, and to use the information so gained to provide clues about how their performance might be improved.

  15. Adaptive geodesic transform for segmentation of vertebrae on CT images

    Science.gov (United States)

    Gaonkar, Bilwaj; Shu, Liao; Hermosillo, Gerardo; Zhan, Yiqiang

    2014-03-01

    Vertebral segmentation is a critical first step in any quantitative evaluation of vertebral pathology using CT images. This is especially challenging because bone marrow tissue has the same intensity profile as the muscle surrounding the bone. Thus simple methods such as thresholding or adaptive k-means fail to accurately segment vertebrae. While several other algorithms such as level sets may be used for segmentation any algorithm that is clinically deployable has to work in under a few seconds. To address these dual challenges we present here, a new algorithm based on the geodesic distance transform that is capable of segmenting the spinal vertebrae in under one second. To achieve this we extend the theory of the geodesic distance transforms proposed in1 to incorporate high level anatomical knowledge through adaptive weighting of image gradients. Such knowledge may be provided by the user directly or may be automatically generated by another algorithm. We incorporate information 'learnt' using a previously published machine learning algorithm2 to segment the L1 to L5 vertebrae. While we present a particular application here, the adaptive geodesic transform is a generic concept which can be applied to segmentation of other organs as well.

  16. 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 consecutive growing seasons. Fruit set on the other hand, decreased with the decrease in irrigation treatment. Floral abortion, reduced pollen viability as well as moisture stress in the style were contributing factors to the reduction in fruiting/yield observed at the 300IT. Moderate water stress prior to floral initiation could stimulate flower initiation, however, this should be followed by sufficient irrigation to ensure good pollination, fruit set and yield.

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

    Science.gov (United States)

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

    2013-01-01

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

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

    OpenAIRE

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

    2009-01-01

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

  19. Improving district level health planning and priority setting in Tanzania through implementing accountability for reasonableness framework: Perceptions of stakeholders.

    Science.gov (United States)

    Maluka, Stephen; Kamuzora, Peter; San Sebastián, Miguel; Byskov, Jens; Ndawi, Benedict; Hurtig, Anna-Karin

    2010-12-01

    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. Individual interviews were carried out with different categories of actors and stakeholders in the district. The interview guide consisted of a series of questions, asking respondents to describe their perceptions regarding each condition of the Accountability for Reasonableness framework in terms of priority setting. Interviews were analysed using thematic framework analysis. Documentary data were used to support, verify and highlight the key issues that emerged. Almost all stakeholders viewed Accountability for Reasonableness as an important and feasible approach for improving priority-setting and health service delivery in their context. However, a few aspects of Accountability for Reasonableness were seen as too difficult to implement given the socio-political conditions and traditions in Tanzania. Respondents mentioned: budget ceilings and guidelines, low level of public awareness, unreliable and untimely funding, as well as the limited capacity of the district to generate local resources as the major contextual factors that hampered the full implementation of the framework in their context. This study was one of the first assessments of the applicability of Accountability for Reasonableness in health care priority-setting in Tanzania. The analysis, overall, suggests that the Accountability for Reasonableness framework could be an important tool for improving priority-setting processes in the contexts of resource-poor settings

  20. Segmentation of urinary bladder in CT urography (CTU) using CLASS with enhanced contour conjoint procedure

    Science.gov (United States)

    Cha, Kenny; Hadjiiski, Lubomir; Chan, Heang-Ping; Cohan, Richard H.; Caoili, Elaine M.; Zhou, Chuan

    2014-03-01

    We are developing a computerized method for bladder segmentation in CT urography (CTU) for computeraided diagnosis of bladder cancer. A challenge for computerized bladder segmentation in CTU is that the bladder often contains regions filled with intravenous (IV) contrast and without contrast. Previously, we proposed a Conjoint Level set Analysis and Segmentation System (CLASS) consisting of four stages: preprocessing and initial segmentation, 3D and 2D level set segmentation, and post-processing. In case the bladder is partially filled with contrast, CLASS segments the non-contrast (NC) region and the contrast (C) filled region separately and conjoins the contours with a Contour Conjoint Procedure (CCP). The CCP is not trivial. Inaccuracies in the NC and C contours may cause CCP to exclude portions of the bladder. To alleviate this problem, we implemented model-guided refinement to propagate the C contour if the level set propagation in the region stops prematurely due to substantial non-uniformity of the contrast. An enhanced CCP with regularized energies further propagates the conjoint contours to the correct bladder boundary. Segmentation performance was evaluated using 70 cases. For all cases, 3D hand segmented contours were obtained as reference standard, and computerized segmentation accuracy was evaluated in terms of average volume intersection %, average % volume error, and average minimum distance. With enhanced CCP, those values were 84.4±10.6%, 8.3±16.1%, 3.4±1.8 mm, respectively. With CLASS, those values were 74.6±13.1%, 19.6±18.6%, 4.4±2.2 mm, respectively. The enhanced CCP improved bladder segmentation significantly (p<0.001) for all three performance measures.

  1. Automatic segmentation of vertebrae from radiographs

    DEFF Research Database (Denmark)

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

    2011-01-01

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

  2. A shape-optimized framework for kidney segmentation in ultrasound images using NLTV denoising and DRLSE

    Directory of Open Access Journals (Sweden)

    Yang Fan

    2012-10-01

    Full Text Available Abstract Background Computer-assisted surgical navigation aims to provide surgeons with anatomical target localization and critical structure observation, where medical image processing methods such as segmentation, registration and visualization play a critical role. Percutaneous renal intervention plays an important role in several minimally-invasive surgeries of kidney, such as Percutaneous Nephrolithotomy (PCNL and Radio-Frequency Ablation (RFA of kidney tumors, which refers to a surgical procedure where access to a target inside the kidney by a needle puncture of the skin. Thus, kidney segmentation is a key step in developing any ultrasound-based computer-aided diagnosis systems for percutaneous renal intervention. Methods In this paper, we proposed a novel framework for kidney segmentation of ultrasound (US images combined with nonlocal total variation (NLTV image denoising, distance regularized level set evolution (DRLSE and shape prior. Firstly, a denoised US image was obtained by NLTV image denoising. Secondly, DRLSE was applied in the kidney segmentation to get binary image. In this case, black and white region represented the kidney and the background respectively. The last stage is that the shape prior was applied to get a shape with the smooth boundary from the kidney shape space, which was used to optimize the segmentation result of the second step. The alignment model was used occasionally to enlarge the shape space in order to increase segmentation accuracy. Experimental results on both synthetic images and US data are given to demonstrate the effectiveness and accuracy of the proposed algorithm. Results We applied our segmentation framework on synthetic and real US images to demonstrate the better segmentation results of our method. From the qualitative results, the experiment results show that the segmentation results are much closer to the manual segmentations. The sensitivity (SN, specificity (SP and positive predictive value

  3. Graph-based surface reconstruction from stereo pairs using image segmentation

    Science.gov (United States)

    Bleyer, Michael; Gelautz, Margrit

    2005-01-01

    This paper describes a novel stereo matching algorithm for epipolar rectified images. The method applies colour segmentation on the reference image. The use of segmentation makes the algorithm capable of handling large untextured regions, estimating precise depth boundaries and propagating disparity information to occluded regions, which are challenging tasks for conventional stereo methods. We model disparity inside a segment by a planar equation. Initial disparity segments are clustered to form a set of disparity layers, which are planar surfaces that are likely to occur in the scene. Assignments of segments to disparity layers are then derived by minimization of a global cost function via a robust optimization technique that employs graph cuts. The cost function is defined on the pixel level, as well as on the segment level. While the pixel level measures the data similarity based on the current disparity map and detects occlusions symmetrically in both views, the segment level propagates the segmentation information and incorporates a smoothness term. New planar models are then generated based on the disparity layers' spatial extents. Results obtained for benchmark and self-recorded image pairs indicate that the proposed method is able to compete with the best-performing state-of-the-art algorithms.

  4. Using Predictability for Lexical Segmentation.

    Science.gov (United States)

    Çöltekin, Çağrı

    2017-09-01

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

  5. Accurate prediction of complex free surface flow around a high speed craft using a single-phase level set method

    Science.gov (United States)

    Broglia, Riccardo; Durante, Danilo

    2017-11-01

    This paper focuses on the analysis of a challenging free surface flow problem involving a surface vessel moving at high speeds, or planing. The investigation is performed using a general purpose high Reynolds free surface solver developed at CNR-INSEAN. The methodology is based on a second order finite volume discretization of the unsteady Reynolds-averaged Navier-Stokes equations (Di Mascio et al. in A second order Godunov—type scheme for naval hydrodynamics, Kluwer Academic/Plenum Publishers, Dordrecht, pp 253-261, 2001; Proceedings of 16th international offshore and polar engineering conference, San Francisco, CA, USA, 2006; J Mar Sci Technol 14:19-29, 2009); air/water interface dynamics is accurately modeled by a non standard level set approach (Di Mascio et al. in Comput Fluids 36(5):868-886, 2007a), known as the single-phase level set method. In this algorithm the governing equations are solved only in the water phase, whereas the numerical domain in the air phase is used for a suitable extension of the fluid dynamic variables. The level set function is used to track the free surface evolution; dynamic boundary conditions are enforced directly on the interface. This approach allows to accurately predict the evolution of the free surface even in the presence of violent breaking waves phenomena, maintaining the interface sharp, without any need to smear out the fluid properties across the two phases. This paper is aimed at the prediction of the complex free-surface flow field generated by a deep-V planing boat at medium and high Froude numbers (from 0.6 up to 1.2). In the present work, the planing hull is treated as a two-degree-of-freedom rigid object. Flow field is characterized by the presence of thin water sheets, several energetic breaking waves and plungings. The computational results include convergence of the trim angle, sinkage and resistance under grid refinement; high-quality experimental data are used for the purposes of validation, allowing to

  6. Introduction to the level-set full field modeling of laths spheroidization phenomenon in α/β titanium alloys

    Directory of Open Access Journals (Sweden)

    Polychronopoulou D.

    2016-01-01

    Full Text Available Fragmentation of α lamellae and subsequent spheroidization of α laths in α/β titanium alloys occurring during and after deformation are well known phenomena. We will illustrate the development of a new finite element methodology to model them. This new methodology is based on a level set framework to model the deformation and the ad hoc simultaneous and/or subsequent interfaces kinetics. We will focus, at yet, on the modeling of the surface diffusion at the α/β phase interfaces and the motion by mean curvature at the α/α grain interfaces.

  7. Novel room-temperature-setting phosphate ceramics for stabilizing combustion products and low-level mixed wastes

    International Nuclear Information System (INIS)

    Wagh, A.S.; Singh, D.

    1994-01-01

    Argonne National Laboratory, with support from the Office of Technology in the US Department of Energy (DOE), has developed a new process employing novel, chemically bonded ceramic materials to stabilize secondary waste streams. Such waste streams result from the thermal processes used to stabilize low-level, mixed wastes. The process will help the electric power industry treat its combustion and low-level mixed wastes. The ceramic materials are strong, dense, leach-resistant, and inexpensive to fabricate. The room-temperature-setting process allows stabilization of volatile components containing lead, mercury, cadmium, chromium, and nickel. The process also provides effective stabilization of fossil fuel combustion products. It is most suitable for treating fly and bottom ashes

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

    Science.gov (United States)

    Tilton, James C.; Pasolli, Edoardo

    2014-01-01

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

  9. Simulation to aid in interpreting biological relevance and setting of population-level protection goals for risk assessment of pesticides.

    Science.gov (United States)

    Topping, Christopher John; Luttik, Robert

    2017-10-01

    Specific protection goals (SPGs) comprise an explicit expression of the environmental components that need protection and the maximum impacts that can be tolerated. SPGs are set by risk managers and are typically based on protecting populations or functions. However, the measurable endpoints available to risk managers, at least for vertebrates, are typically laboratory tests. We demonstrate, using the example of eggshell thinning in skylarks, how simulation can be used to place laboratory endpoints in context of population-level effects as an aid to setting the SPGs. We develop explanatory scenarios investigating the impact of different assumptions of eggshell thinning on skylark population size, density and distribution in 10 Danish landscapes, chosen to represent the range of typical Danish agricultural conditions. Landscape and timing of application of the pesticide were found to be the most critical factors to consider in the impact assessment. Consequently, a regulatory scenario of monoculture spring barley with an early spray treatment eliciting the eggshell thinning effect was applied using concentrations eliciting effects of zero to 100% in steps of 5%. Setting the SPGs requires balancing scientific, social and political realities. However, the provision of clear and detailed options such as those from comprehensive simulation results can inform the decision process by improving transparency and by putting the more abstract testing data into the context of real-world impacts. Copyright © 2017 Elsevier Inc. All rights reserved.

  10. Level-set reconstruction algorithm for ultrafast limited-angle X-ray computed tomography of two-phase flows.

    Science.gov (United States)

    Bieberle, M; Hampel, U

    2015-06-13

    Tomographic image reconstruction is based on recovering an object distribution from its projections, which have been acquired from all angular views around the object. If the angular range is limited to less than 180° of parallel projections, typical reconstruction artefacts arise when using standard algorithms. To compensate for this, specialized algorithms using a priori information about the object need to be applied. The application behind this work is ultrafast limited-angle X-ray computed tomography of two-phase flows. Here, only a binary distribution of the two phases needs to be reconstructed, which reduces the complexity of the inverse problem. To solve it, a new reconstruction algorithm (LSR) based on the level-set method is proposed. It includes one force function term accounting for matching the projection data and one incorporating a curvature-dependent smoothing of the phase boundary. The algorithm has been validated using simulated as well as measured projections of known structures, and its performance has been compared to the algebraic reconstruction technique and a binary derivative of it. The validation as well as the application of the level-set reconstruction on a dynamic two-phase flow demonstrated its applicability and its advantages over other reconstruction algorithms. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  11. Effect of a uniform magnetic field on dielectric two-phase bubbly flows using the level set method

    International Nuclear Information System (INIS)

    Ansari, M.R.; Hadidi, A.; Nimvari, M.E.

    2012-01-01

    In this study, the behavior of a single bubble in a dielectric viscous fluid under a uniform magnetic field has been simulated numerically using the Level Set method in two-phase bubbly flow. The two-phase bubbly flow was considered to be laminar and homogeneous. Deformation of the bubble was considered to be due to buoyancy and magnetic forces induced from the external applied magnetic field. A computer code was developed to solve the problem using the flow field, the interface of two phases, and the magnetic field. The Finite Volume method was applied using the SIMPLE algorithm to discretize the governing equations. Using this algorithm enables us to calculate the pressure parameter, which has been eliminated by previous researchers because of the complexity of the two-phase flow. The finite difference method was used to solve the magnetic field equation. The results outlined in the present study agree well with the existing experimental data and numerical results. These results show that the magnetic field affects and controls the shape, size, velocity, and location of the bubble. - Highlights: ►A bubble behavior was simulated numerically. ► A single bubble behavior was considered in a dielectric viscous fluid. ► A uniform magnetic field is used to study a bubble behavior. ► Deformation of the bubble was considered using the Level Set method. ► The magnetic field affects the shape, size, velocity, and location of the bubble.

  12. Identification of Arbitrary Zonation in Groundwater Parameters using the Level Set Method and a Parallel Genetic Algorithm

    Science.gov (United States)

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

    2017-12-01

    Simultaneous identification of both the zonation structure of aquifer heterogeneity and the hydrogeological parameters associated with these zones is challenging, especially for complex subsurface heterogeneity fields. In this study, a new approach, based on the combination of the level set method and a parallel genetic algorithm is proposed. Starting with an initial guess for the zonation field (including both zonation structure and the hydraulic properties of each zone), the level set method ensures that material interfaces are evolved through the inverse process such that the total residual between the simulated and observed state variables (hydraulic head) always decreases, which means that the inversion result depends on the initial guess field and the minimization process might fail if it encounters a local minimum. To find the global minimum, the genetic algorithm (GA) is utilized to explore the parameters that define initial guess fields, and the minimal total residual corresponding to each initial guess field is considered as the fitness function value in the GA. Due to the expensive evaluation of the fitness function, a parallel GA is adapted in combination with a simulated annealing algorithm. The new approach has been applied to several synthetic cases in both steady-state and transient flow fields, including a case with real flow conditions at the chromium contaminant site at the Los Alamos National Laboratory. The results show that this approach is capable of identifying the arbitrary zonation structures of aquifer heterogeneity and the hydrogeological parameters associated with these zones effectively.

  13. GSHR, a Web-Based Platform Provides Gene Set-Level Analyses of Hormone Responses in Arabidopsis

    Directory of Open Access Journals (Sweden)

    Xiaojuan Ran

    2018-01-01

    Full Text Available Phytohormones regulate diverse aspects of plant growth and environmental responses. Recent high-throughput technologies have promoted a more comprehensive profiling of genes regulated by different hormones. However, these omics data generally result in large gene lists that make it challenging to interpret the data and extract insights into biological significance. With the rapid accumulation of theses large-scale experiments, especially the transcriptomic data available in public databases, a means of using this information to explore the transcriptional networks is needed. Different platforms have different architectures and designs, and even similar studies using the same platform may obtain data with large variances because of the highly dynamic and flexible effects of plant hormones; this makes it difficult to make comparisons across different studies and platforms. Here, we present a web server providing gene set-level analyses of Arabidopsis thaliana hormone responses. GSHR collected 333 RNA-seq and 1,205 microarray datasets from the Gene Expression Omnibus, characterizing transcriptomic changes in Arabidopsis in response to phytohormones including abscisic acid, auxin, brassinosteroids, cytokinins, ethylene, gibberellins, jasmonic acid, salicylic acid, and strigolactones. These data were further processed and organized into 1,368 gene sets regulated by different hormones or hormone-related factors. By comparing input gene lists to these gene sets, GSHR helped to identify gene sets from the input gene list regulated by different phytohormones or related factors. Together, GSHR links prior information regarding transcriptomic changes induced by hormones and related factors to newly generated data and facilities cross-study and cross-platform comparisons; this helps facilitate the mining of biologically significant information from large-scale datasets. The GSHR is freely available at http://bioinfo.sibs.ac.cn/GSHR/.

  14. Abdomen and spinal cord segmentation with augmented active shape models.

    Science.gov (United States)

    Xu, Zhoubing; Conrad, Benjamin N; Baucom, Rebeccah B; Smith, Seth A; Poulose, Benjamin K; Landman, Bennett A

    2016-07-01

    Active shape models (ASMs) have been widely used for extracting human anatomies in medical images given their capability for shape regularization of topology preservation. However, sensitivity to model initialization and local correspondence search often undermines their performances, especially around highly variable contexts in computed-tomography (CT) and magnetic resonance (MR) images. In this study, we propose an augmented ASM (AASM) by integrating the multiatlas label fusion (MALF) and level set (LS) techniques into the traditional ASM framework. Using AASM, landmark updates are optimized globally via a region-based LS evolution applied on the probability map generated from MALF. This augmentation effectively extends the searching range of correspondent landmarks while reducing sensitivity to the image contexts and improves the segmentation robustness. We propose the AASM framework as a two-dimensional segmentation technique targeting structures with one axis of regularity. We apply AASM approach to abdomen CT and spinal cord (SC) MR segmentation challenges. On 20 CT scans, the AASM segmentation of the whole abdominal wall enables the subcutaneous/visceral fat measurement, with high correlation to the measurement derived from manual segmentation. On 28 3T MR scans, AASM yields better performances than other state-of-the-art approaches in segmenting white/gray matter in SC.

  15. Efficient graph-cut tattoo segmentation

    Science.gov (United States)

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

    2015-03-01

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

  16. Patient- and population-level health consequences of discontinuing antiretroviral therapy in settings with inadequate HIV treatment availability

    Directory of Open Access Journals (Sweden)

    Kimmel April D

    2012-09-01

    Full Text Available Abstract Background In resource-limited settings, HIV budgets are flattening or decreasing. A policy of discontinuing antiretroviral therapy (ART after HIV treatment failure was modeled to highlight trade-offs among competing policy goals of optimizing individual and population health outcomes. Methods In settings with two available ART regimens, we assessed two strategies: (1 continue ART after second-line failure (Status Quo and (2 discontinue ART after second-line failure (Alternative. A computer model simulated outcomes for a single cohort of newly detected, HIV-infected individuals. Projections were fed into a population-level model allowing multiple cohorts to compete for ART with constraints on treatment capacity. In the Alternative strategy, discontinuation of second-line ART occurred upon detection of antiretroviral failure, specified by WHO guidelines. Those discontinuing failed ART experienced an increased risk of AIDS-related mortality compared to those continuing ART. Results At the population level, the Alternative strategy increased the mean number initiating ART annually by 1,100 individuals (+18.7% to 6,980 compared to the Status Quo. More individuals initiating ART under the Alternative strategy increased total life-years by 15,000 (+2.8% to 555,000, compared to the Status Quo. Although more individuals received treatment under the Alternative strategy, life expectancy for those treated decreased by 0.7 years (−8.0% to 8.1 years compared to the Status Quo. In a cohort of treated patients only, 600 more individuals (+27.1% died by 5 years under the Alternative strategy compared to the Status Quo. Results were sensitive to the timing of detection of ART failure, number of ART regimens, and treatment capacity. Although we believe the results robust in the short-term, this analysis reflects settings where HIV case detection occurs late in the disease course and treatment capacity and the incidence of newly detected patients are

  17. Active Contour Driven by Local Region Statistics and Maximum A Posteriori Probability for Medical Image Segmentation

    Directory of Open Access Journals (Sweden)

    Xiaoliang Jiang

    2014-01-01

    Full Text Available This paper presents a novel active contour model in a variational level set formulation for simultaneous segmentation and bias field estimation of medical images. An energy function is formulated based on improved Kullback-Leibler distance (KLD with likelihood ratio. According to the additive model of images with intensity inhomogeneity, we characterize the statistics of image intensities belonging to each different object in local regions as Gaussian distributions with different means and variances. Then, we use the Gaussian distribution with bias field as a local region descriptor in level set formulation for segmentation and bias field correction of the images with inhomogeneous intensities. Therefore, image segmentation and bias field estimation are simultaneously achieved by minimizing the level set formulation. Experimental results demonstrate desirable performance of the proposed method for different medical images with weak boundaries and noise.

  18. Unsupervised Performance Evaluation of Image Segmentation

    Directory of Open Access Journals (Sweden)

    Chabrier Sebastien

    2006-01-01

    Full Text Available We present in this paper a study of unsupervised evaluation criteria that enable the quantification of the quality of an image segmentation result. These evaluation criteria compute some statistics for each region or class in a segmentation result. Such an evaluation criterion can be useful for different applications: the comparison of segmentation results, the automatic choice of the best fitted parameters of a segmentation method for a given image, or the definition of new segmentation methods by optimization. We first present the state of art of unsupervised evaluation, and then, we compare six unsupervised evaluation criteria. For this comparative study, we use a database composed of 8400 synthetic gray-level images segmented in four different ways. Vinet's measure (correct classification rate is used as an objective criterion to compare the behavior of the different criteria. Finally, we present the experimental results on the segmentation evaluation of a few gray-level natural images.

  19. MRI Brain Tumor Segmentation Methods- A Review

    OpenAIRE

    Gursangeet, Kaur; Jyoti, Rani

    2016-01-01

    Medical image processing and its segmentation is an active and interesting area for researchers. It has reached at the tremendous place in diagnosing tumors after the discovery of CT and MRI. MRI is an useful tool to detect the brain tumor and segmentation is performed to carry out the useful portion from an image. The purpose of this paper is to provide an overview of different image segmentation methods like watershed algorithm, morphological operations, neutrosophic sets, thresholding, K-...

  20. An approach for maximizing the smallest eigenfrequency of structure vibration based on piecewise constant level set method

    Science.gov (United States)

    Zhang, Zhengfang; Chen, Weifeng

    2018-05-01

    Maximization of the smallest eigenfrequency of the linearized elasticity system with area constraint is investigated. The elasticity system is extended into a large background domain, but the void is vacuum and not filled with ersatz material. The piecewise constant level set (PCLS) method is applied to present two regions, the original material region and the void region. A quadratic PCLS function is proposed to represent the characteristic function. Consequently, the functional derivative of the smallest eigenfrequency with respect to PCLS function takes nonzero value in the original material region and zero in the void region. A penalty gradient algorithm is proposed, which initializes the whole background domain with the original material and decreases the area of original material region till the area constraint is satisfied. 2D and 3D numerical examples are presented, illustrating the validity of the proposed algorithm.

  1. Computational Fluid Dynamics Analysis of Cold Plasma Plume Mixing with Blood Using Level Set Method Coupled with Heat Transfer

    Directory of Open Access Journals (Sweden)

    Mehrdad Shahmohammadi Beni

    2017-06-01

    Full Text Available Cold plasmas were proposed for treatment of leukemia. In the present work, conceptual designs of mixing chambers that increased the contact between the two fluids (plasma and blood through addition of obstacles within rectangular-block-shaped chambers were proposed and the dynamic mixing between the plasma and blood were studied using the level set method coupled with heat transfer. Enhancement of mixing between blood and plasma in the presence of obstacles was demonstrated. Continuous tracking of fluid mixing with determination of temperature distributions was enabled by the present model, which would be a useful tool for future development of cold plasma devices for treatment of blood-related diseases such as leukemia.

  2. Comparison of CLASS and ITK-SNAP in segmentation of urinary bladder in CT urography

    Science.gov (United States)

    Cha, Kenny; Hadjiiski, Lubomir; Chan, Heang-Ping; Caoili, Elaine M.; Cohan, Richard H.; Zhou, Chuan

    2014-03-01

    We are developing a computerized method for bladder segmentation in CT urography (CTU) for computeraided diagnosis of bladder cancer. We have developed a Conjoint Level set Analysis and Segmentation System (CLASS) consisting of four stages: preprocessing and initial segmentation, 3D and 2D level set segmentation, and post-processing. In case the bladder contains regions filled with intravenous (IV) contrast and without contrast, CLASS segments the noncontrast (NC) region and the contrast (C) filled region separately and conjoins the contours. In this study, we compared the performance of CLASS to ITK-SNAP 2.4, which is a publicly available software application for segmentation of structures in 3D medical images. ITK-SNAP performs segmentation by using the edge-based level set on preprocessed images. The level set were initialized by manually placing a sphere at the boundary between the C and NC parts of the bladders with C and NC regions, and in the middle of the bladders that had only C or NC region. Level set parameters and the number of iterations were chosen after experimentation with bladder cases. Segmentation performances were compared using 30 randomly selected bladders. 3D hand-segmented contours were obtained as reference standard, and computerized segmentation accuracy was evaluated in terms of the average volume intersection %, average % volume error, average absolute % volume error, average minimum distance, and average Jaccard index. For CLASS, the values for these performance metrics were 79.0±8.2%, 16.1±16.3%, 19.9±11.1%, 3.5±1.3 mm, 75.7±8.4%, respectively. For ITK-SNAP, the corresponding values were 78.8±8.2%, 8.3±33.1%, 24.2±23.7%, 5.2±2.6 mm, 71.0±15.4%, respectively. CLASS on average performed better and exhibited less variations than ITK-SNAP for bladder segmentation.

  3. A spectral k-means approach to bright-field cell image segmentation.

    Science.gov (United States)

    Bradbury, Laura; Wan, Justin W L

    2010-01-01

    Automatic segmentation of bright-field cell images is important to cell biologists, but difficult to complete due to the complex nature of the cells in bright-field images (poor contrast, broken halo, missing boundaries). Standard approaches such as level set segmentation and active contours work well for fluorescent images where cells appear as round shape, but become less effective when optical artifacts such as halo exist in bright-field images. In this paper, we present a robust segmentation method which combines the spectral and k-means clustering techniques to locate cells in bright-field images. This approach models an image as a matrix graph and segment different regions of the image by computing the appropriate eigenvectors of the matrix graph and using the k-means algorithm. We illustrate the effectiveness of the method by segmentation results of C2C12 (muscle) cells in bright-field images.

  4. Effect of culture levels, ultrafiltered retentate addition, total solid levels and heat treatments on quality improvement of buffalo milk plain set yoghurt.

    Science.gov (United States)

    Yadav, Vijesh; Gupta, Vijay Kumar; Meena, Ganga Sahay

    2018-05-01

    Studied the effect of culture (2, 2.5 and 3%), ultrafiltered (UF) retentate addition (0, 11, 18%), total milk solids (13, 13.50, 14%) and heat treatments (80 and 85 °C/30 min) on the change in pH and titratable acidity (TA), sensory scores and rheological parameters of yoghurt. With 3% culture levels, the required TA (0.90% LA) was achieved in minimum 6 h incubation. With an increase in UF retentate addition, there was observed a highly significant decrease in overall acceptability, body and texture and colour and appearance scores, but there was highly significant increase in rheological parameters of yoghurt samples. Yoghurt made from even 13.75% total solids containing nil UF retentate was observed to be sufficiently firm by the sensory panel. Most of the sensory attributes of yoghurt made with 13.50% total solids were significantly better than yoghurt prepared with either 13 or 14% total solids. Standardised milk heated to 85 °C/30 min resulted in significantly better overall acceptability in yoghurt. Overall acceptability of optimised yoghurt was significantly better than a branded market sample. UF retentate addition adversely affected yoghurt quality, whereas optimization of culture levels, totals milk solids and others process parameters noticeably improved the quality of plain set yoghurt with a shelf life of 15 days at 4 °C.

  5. Automatic Segmenting Structures in MRI's Based on Texture Analysis and Fuzzy Logic

    Science.gov (United States)

    Kaur, Mandeep; Rattan, Munish; Singh, Pushpinder

    2017-12-01

    The purpose of this paper is to present the variational method for geometric contours which helps the level set function remain close to the sign distance function, therefor it remove the need of expensive re-initialization procedure and thus, level set method is applied on magnetic resonance images (MRI) to track the irregularities in them as medical imaging plays a substantial part in the treatment, therapy and diagnosis of various organs, tumors and various abnormalities. It favors the patient with more speedy and decisive disease controlling with lesser side effects. The geometrical shape, the tumor's size and tissue's abnormal growth can be calculated by the segmentation of that particular image. It is still a great challenge for the researchers to tackle with an automatic segmentation in the medical imaging. Based on the texture analysis, different images are processed by optimization of level set segmentation. Traditionally, optimization was manual for every image where each parameter is selected one after another. By applying fuzzy logic, the segmentation of image is correlated based on texture features, to make it automatic and more effective. There is no initialization of parameters and it works like an intelligent system. It segments the different MRI images without tuning the level set parameters and give optimized results for all MRI's.

  6. Learning from Weak and Noisy Labels for Semantic Segmentation

    KAUST Repository

    Lu, Zhiwu

    2016-04-08

    A weakly supervised semantic segmentation (WSSS) method aims to learn a segmentation model from weak (image-level) as opposed to strong (pixel-level) labels. By avoiding the tedious pixel-level annotation process, it can exploit the unlimited supply of user-tagged images from media-sharing sites such as Flickr for large scale applications. However, these ‘free’ tags/labels are often noisy and few existing works address the problem of learning with both weak and noisy labels. In this work, we cast the WSSS problem into a label noise reduction problem. Specifically, after segmenting each image into a set of superpixels, the weak and potentially noisy image-level labels are propagated to the superpixel level resulting in highly noisy labels; the key to semantic segmentation is thus to identify and correct the superpixel noisy labels. To this end, a novel L1-optimisation based sparse learning model is formulated to directly and explicitly detect noisy labels. To solve the L1-optimisation problem, we further develop an efficient learning algorithm by introducing an intermediate labelling variable. Extensive experiments on three benchmark datasets show that our method yields state-of-the-art results given noise-free labels, whilst significantly outperforming the existing methods when the weak labels are also noisy.

  7. Learning from Weak and Noisy Labels for Semantic Segmentation

    KAUST Repository

    Lu, Zhiwu; Fu, Zhenyong; Xiang, Tao; Han, Peng; Wang, Liwei; Gao, Xin

    2016-01-01

    A weakly supervised semantic segmentation (WSSS) method aims to learn a segmentation model from weak (image-level) as opposed to strong (pixel-level) labels. By avoiding the tedious pixel-level annotation process, it can exploit the unlimited supply of user-tagged images from media-sharing sites such as Flickr for large scale applications. However, these ‘free’ tags/labels are often noisy and few existing works address the problem of learning with both weak and noisy labels. In this work, we cast the WSSS problem into a label noise reduction problem. Specifically, after segmenting each image into a set of superpixels, the weak and potentially noisy image-level labels are propagated to the superpixel level resulting in highly noisy labels; the key to semantic segmentation is thus to identify and correct the superpixel noisy labels. To this end, a novel L1-optimisation based sparse learning model is formulated to directly and explicitly detect noisy labels. To solve the L1-optimisation problem, we further develop an efficient learning algorithm by introducing an intermediate labelling variable. Extensive experiments on three benchmark datasets show that our method yields state-of-the-art results given noise-free labels, whilst significantly outperforming the existing methods when the weak labels are also noisy.

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

    Directory of Open Access Journals (Sweden)

    Shuo-Tsung Chen

    2015-01-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

  10. Set-up and first operation of a plasma oven for treatment of low level radioactive wastes

    Directory of Open Access Journals (Sweden)

    Nachtrodt Frederik

    2014-01-01

    Full Text Available An experimental device for plasma treatment of low and intermediate level radioactive waste was built and tested in several design variations. The laboratory device is designed with the intention to study the general effects and difficulties in a plasma incineration set-up for the further future development of a larger scale pilot plant. The key part of the device consists of a novel microwave plasma torch driven by 200 W electric power, and operating at atmospheric pressure. It is a specific design characteristic of the torch that a high peak temperature can be reached with a low power input compared to other plasma torches. Experiments have been carried out to analyze the effect of the plasma on materials typical for operational low-level wastes. In some preliminary cold tests the behavior of stable volatile species e. g., caesium was investigated by TXRF measurements of material collected from the oven walls and the filtered off-gas. The results help in improving and scaling up the existing design and in understanding the effects for a pilot plant, especially for the off-gas collection and treatment.

  11. Creating Web Area Segments with Google Analytics

    Science.gov (United States)

    Segments allow you to quickly access data for a predefined set of Sessions or Users, such as government or education users, or sessions in a particular state. You can then apply this segment to any report within the Google Analytics (GA) interface.

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

    DEFF Research Database (Denmark)

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

    2010-01-01

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

  13. An analysis on the level changing of UET and SET in blood and urine in early stage of kidney disease caused by diabetes

    International Nuclear Information System (INIS)

    Liu Juzhen; Yang Wenying; Cai Tietie

    2001-01-01

    Objective: To study the relationship between UET and SET variation and early changes of diabetic nephropathy. Methods: UET and SET were measured in 24 patients with diabetes, 19 with early stage diabetic nephropathy, 21 with advanced diabetic nephropathy and 30 normal as contrast. Results: Apparent uprise of UET and SET was observed in all patients when compared to normal contrasts (P 2 -macroglobulin was revealed (P<0.05). Conclusion: UET and SET levels uprose as long as diabetic nephropathy deteriorated. As a result, UET and SET may act as sensitive indices in diagnosing early stage diabetic nephropathy

  14. Image Segmentation Using Minimum Spanning Tree

    Science.gov (United States)

    Dewi, M. P.; Armiati, A.; Alvini, S.

    2018-04-01

    This research aim to segmented the digital image. The process of segmentation is to separate the object from the background. So the main object can be processed for the other purposes. Along with the development of technology in digital image processing application, the segmentation process becomes increasingly necessary. The segmented image which is the result of the segmentation process should accurate due to the next process need the interpretation of the information on the image. This article discussed the application of minimum spanning tree on graph in segmentation process of digital image. This method is able to separate an object from the background and the image will change to be the binary images. In this case, the object that being the focus is set in white, while the background is black or otherwise.

  15. Leveling the field: The role of training, safety programs, and knowledge management systems in fostering inclusive field settings

    Science.gov (United States)

    Starkweather, S.; Crain, R.; Derry, K. R.

    2017-12-01

    Knowledge is empowering in all settings, but plays an elevated role in empowering under-represented groups in field research. Field research, particularly polar field research, has deep roots in masculinized and colonial traditions, which can lead to high barriers for women and minorities (e.g. Carey et al., 2016). While recruitment of underrepresented groups into polar field research has improved through the efforts of organizations like the Association of Polar Early Career Scientists (APECS), the experiences and successes of these participants is often contingent on the availability of specialized training opportunities or the quality of explicitly documented information about how to survive Arctic conditions or how to establish successful measurement protocols in harsh environments. In Arctic field research, knowledge is often not explicitly documented or conveyed, but learned through "experience" or informally through ad hoc advice. The advancement of field training programs and knowledge management systems suggest two means for unleashing more explicit forms of knowledge about field work. Examples will be presented along with a case for how they level the playing field and improve the experience of field work for all participants.

  16. A comparative study of reinitialization approaches of the level set method for simulating free-surface flows

    Energy Technology Data Exchange (ETDEWEB)

    Sufyan, Muhammad; Ngo, Long Cu; Choi, Hyoung Gwon [Seoul National University, Seoul (Korea, Republic of)

    2016-04-15

    Unstructured grids were used to compare the performance of a direct reinitialization scheme with those of two reinitialization approaches based on the solution of a hyperbolic Partial differential equation (PDE). The problems of moving interface were solved in the context of a finite element method. A least-square weighted residual method was used to discretize the advection equation of the level set method. The benchmark problems of rotating Zalesak's disk, time-reversed single vortex, and two-dimensional sloshing were examined. Numerical results showed that the direct reinitialization scheme performed better than the PDE-based reinitialization approaches in terms of mass conservation, dissipation and dispersion error, and computational time. In the case of sloshing, numerical results were found to be in good agreement with existing experimental data. The direct reinitialization approach consumed considerably less CPU time than the PDE-based simulations for 20 time periods of sloshing. This approach was stable, accurate, and efficient for all the problems considered in this study.

  17. Developmental screening tools: feasibility of use at primary healthcare level in low- and middle-income settings.

    Science.gov (United States)

    Fischer, Vinicius Jobim; Morris, Jodi; Martines, José

    2014-06-01

    An estimated 150 million children have a disability. Early identification of developmental disabilities is a high priority for the World Health Organization to allow action to reduce impairments through Gap Action Program on mental health. The study identified the feasibility of using the developmental screening and monitoring tools for children aged 0-3 year(s) by non-specialist primary healthcare providers in low-resource settings. A systematic review of the literature was conducted to identify the tools, assess their psychometric properties, and feasibility of use in low- and middle-income countries (LMICs). Key indicators to examine feasibility in LMICs were derived from a consultation with 23 international experts. We identified 426 studies from which 14 tools used in LMICs were extracted for further examination. Three tools reported adequate psychometric properties and met most of the feasibility criteria. Three tools appear promising for use in identifying and monitoring young children with disabilities at primary healthcare level in LMICs. Further research and development are needed to optimize these tools.

  18. Neural Scene Segmentation by Oscillatory Correlation

    National Research Council Canada - National Science Library

    Wang, DeLiang

    2000-01-01

    The segmentation of a visual scene into a set of coherent patterns (objects) is a fundamental aspect of perception, which underlies a variety of important tasks such as figure/ground segregation, and scene analysis...

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

    Science.gov (United States)

    Tilton, James C.

    2003-01-01

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

  20. Automatic segmentation of psoriasis lesions

    Science.gov (United States)

    Ning, Yang; Shi, Chenbo; Wang, Li; Shu, Chang

    2014-10-01

    The automatic segmentation of psoriatic lesions is widely researched these years. It is an important step in Computer-aid methods of calculating PASI for estimation of lesions. Currently those algorithms can only handle single erythema or only deal with scaling segmentation. In practice, scaling and erythema are often mixed together. In order to get the segmentation of lesions area - this paper proposes an algorithm based on Random forests with color and texture features. The algorithm has three steps. The first step, the polarized light is applied based on the skin's Tyndall-effect in the imaging to eliminate the reflection and Lab color space are used for fitting the human perception. The second step, sliding window and its sub windows are used to get textural feature and color feature. In this step, a feature of image roughness has been defined, so that scaling can be easily separated from normal skin. In the end, Random forests will be used to ensure the generalization ability of the algorithm. This algorithm can give reliable segmentation results even the image has different lighting conditions, skin types. In the data set offered by Union Hospital, more than 90% images can be segmented accurately.

  1. Automatized spleen segmentation in non-contrast-enhanced MR volume data using subject-specific shape priors

    Science.gov (United States)

    Gloger, Oliver; Tönnies, Klaus; Bülow, Robin; Völzke, Henry

    2017-07-01

    To develop the first fully automated 3D spleen segmentation framework derived from T1-weighted magnetic resonance (MR) imaging data and to verify its performance for spleen delineation and volumetry. This approach considers the issue of low contrast between spleen and adjacent tissue in non-contrast-enhanced MR images. Native T1-weighted MR volume data was performed on a 1.5 T MR system in an epidemiological study. We analyzed random subsamples of MR examinations without pathologies to develop and verify the spleen segmentation framework. The framework is modularized to include different kinds of prior knowledge into the segmentation pipeline. Classification by support vector machines differentiates between five different shape types in computed foreground probability maps and recognizes characteristic spleen regions in axial slices of MR volume data. A spleen-shape space generated by training produces subject-specific prior shape knowledge that is then incorporated into a final 3D level set segmentation method. Individually adapted shape-driven forces as well as image-driven forces resulting from refined foreground probability maps steer the level set successfully to the segment the spleen. The framework achieves promising segmentation results with mean Dice coefficients of nearly 0.91 and low volumetric mean errors of 6.3%. The presented spleen segmentation approach can delineate spleen tissue in native MR volume data. Several kinds of prior shape knowledge including subject-specific 3D prior shape knowledge can be used to guide segmentation processes achieving promising results.

  2. Segmented trapped vortex cavity

    Science.gov (United States)

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

    2010-01-01

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

  3. Pavement management segment consolidation

    Science.gov (United States)

    1998-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Praveen Agarwal

    2017-06-01

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

  5. CONSUMER SEGMENTATION OF REFILLED DRINKING WATER IN PADANG

    Directory of Open Access Journals (Sweden)

    Awisal Fasyni

    2015-05-01

    Full Text Available The purposes of this study were to analyze consumer segmentation of refilled drinking water based on their behavior and to recommend strategies for increased sales of Salju depot. The study was conducted using a survey of family and non-family consumers in Nanggalo, North Padang, West and East Padang. The respondent selection technique is using a convenience sampling, which is based on the availability of elements and easiness of obtaining these samples. The analysis used for segmentation is cluster analysis and CHAID. The results showed that there were five segments in family consumer and four segments in non-family consumer. Each family segment was different in terms of usage and consumption level, while non-family segments differ in terms of consumption duration and consumption level. Salju depot could aim market segments that provide benefits, specifically segments with high consumption levels both in family and nonfamily consumers, maintain the price and quality of the product and show the best performance in serving customers, set the open hours and optimize the messaging services.Keywords: refilled drinking water, segmentation, Padang, CHAIDABSTRAKPenelitian ini bertujuan menganalisis segmentasi konsumen air minum isi ulang berdasarkan perilakunya dan merekomendasikan strategi peningkatan penjualan bagi depot Salju. Penelitian dilakukan dengan metode survei terhadap konsumen keluarga dan konsumen nonkeluarga di Kecamatan Nanggalo, Kecamatan Padang Utara, Kecamatan Padang Barat dan Kecamatan Padang Timur Kota Padang. Teknik pemilihan responden menggunakan convenience sampling, yaitu berdasarkan ketersediaan elemen dan kemudahan mendapatkan sampel tersebut. Analisis yang digunakan untuk segmentasi adalah analisis cluster dan CHAID Hasil penelitian menunjukkan terdapat lima segmen konsumen keluarga dan empat segmen konsumen nonkeluarga. Masing-masing segmen keluarga berbeda dalam hal penggunaan dan tingkat konsumsi, sedangkan segmen

  6. Speaker segmentation and clustering

    OpenAIRE

    Kotti, M; Moschou, V; Kotropoulos, C

    2008-01-01

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

  7. Spinal segmental dysgenesis

    Directory of Open Access Journals (Sweden)

    N Mahomed

    2009-06-01

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

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

    Science.gov (United States)

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

    2018-03-01

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

  9. Automatic Melody Segmentation

    NARCIS (Netherlands)

    Rodríguez López, Marcelo

    2016-01-01

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

  10. Segmentation of the geographic atrophy in spectral-domain optical coherence tomography and fundus autofluorescence images.

    Science.gov (United States)

    Hu, Zhihong; Medioni, Gerard G; Hernandez, Matthias; Hariri, Amirhossein; Wu, Xiaodong; Sadda, Srinivas R

    2013-12-30

    Geographic atrophy (GA) is the atrophic late-stage manifestation of age-related macular degeneration (AMD), which may result in severe vision loss and blindness. The purpose of this study was to develop a reliable, effective approach for GA segmentation in both spectral-domain optical coherence tomography (SD-OCT) and fundus autofluorescence (FAF) images using a level set-based approach and to compare the segmentation performance in the two modalities. To identify GA regions in SD-OCT images, three retinal surfaces were first segmented in volumetric SD-OCT images using a double-surface graph search scheme. A two-dimensional (2-D) partial OCT projection image was created from the segmented choroid layer. A level set approach was applied to segment the GA in the partial OCT projection image. In addition, the algorithm was applied to FAF images for the GA segmentation. Twenty randomly chosen macular SD-OCT (Zeiss Cirrus) volumes and 20 corresponding FAF (Heidelberg Spectralis) images were obtained from 20 subjects with GA. The algorithm-defined GA region was compared with consensus manual delineation performed by certified graders. The mean Dice similarity coefficients (DSC) between the algorithm- and manually defined GA regions were 0.87 ± 0.09 in partial OCT projection images and 0.89 ± 0.07 in registered FAF images. The area correlations between them were 0.93 (P segment GA regions in both SD-OCT and FAF images. This approach demonstrated good agreement between the algorithm- and manually defined GA regions within each single modality. The GA segmentation in FAF images performed better than in partial OCT projection images. Across the two modalities, the GA segmentation presented reasonable agreement.

  11. Statistical characterization and segmentation of drusen in fundus images.

    Science.gov (United States)

    Santos-Villalobos, H; Karnowski, T P; Aykac, D; Giancardo, L; Li, Y; Nichols, T; Tobin, K W; Chaum, E

    2011-01-01

    Age related Macular Degeneration (AMD) is a disease of the retina associated with aging. AMD progression in patients is characterized by drusen, pigmentation changes, and geographic atrophy, which can be seen using fundus imagery. The level of AMD is characterized by standard scaling methods, which can be somewhat subjective in practice. In this work we propose a statistical image processing approach to segment drusen with the ultimate goal of characterizing the AMD progression in a data set of longitudinal images. The method characterizes retinal structures with a statistical model of the colors in the retina image. When comparing the segmentation results of the method between longitudinal images with known AMD progression and those without, the method detects progression in our longitudinal data set with an area under the receiver operating characteristics curve of 0.99.

  12. Statistical Characterization and Segmentation of Drusen in Fundus Images

    Energy Technology Data Exchange (ETDEWEB)

    Santos-Villalobos, Hector J [ORNL; Karnowski, Thomas Paul [ORNL; Aykac, Deniz [ORNL; Giancardo, Luca [ORNL; Li, Yaquin [University of Tennessee, Knoxville (UTK); Nichols, Trent L [ORNL; Tobin Jr, Kenneth William [ORNL; Chaum, Edward [University of Tennessee, Knoxville (UTK)

    2011-01-01

    Age related Macular Degeneration (AMD) is a disease of the retina associated with aging. AMD progression in patients is characterized by drusen, pigmentation changes, and geographic atrophy, which can be seen using fundus imagery. The level of AMD is characterized by standard scaling methods, which can be somewhat subjective in practice. In this work we propose a statistical image processing approach to segment drusen with the ultimate goal of characterizing the AMD progression in a data set of longitudinal images. The method characterizes retinal structures with a statistical model of the colors in the retina image. When comparing the segmentation results of the method between longitudinal images with known AMD progression and those without, the method detects progression in our longitudinal data set with an area under the receiver operating characteristics curve of 0.99.

  13. The Process of Creation of Value Shareholder compared in each Level Segmented on the Bovespa Corporate Governance: A Study with the Companies comprising the Index Stock Portfolio Brazil (Ibrx 100

    Directory of Open Access Journals (Sweden)

    Wagner Moura Lamounier

    2012-06-01

    Full Text Available The objective of this article was of to measure and to analyze the creation of value for the shareholder through comparisons among each level of corporate governance segmented in BOVESPA, accomplishing an empiric study with interest of proving the existence of different averages regarding the one of creation of value in the different segments. The research was guided through a descriptive analysis which makes possible to establish relationships among the analyzed variables and to lift hypotheses or possibilities to explain those relationships. The found results didn't demonstrate statistical evidences that the level of corporate governance, in that certain company is inserted at the market, brings differentiation in the process of creation of value for the shareholders. The found conclusions thwarted the null hypothesis of this study, which mentioned that in agreement with the level of classification of the companies there would be a differentiation in the creation of value for the shareholder. It is pointed out that that conclusion not to be generalized by the fact that the sample used to obtain her, in spite of being representative, it was obtained in a limited temporary space, existing the possibility that increasing the space of time here the conclusions presented they can suffer alterations. For future researches it is suggested that this study is accomplished with a larger sample of companies, and with given quarterly with the intention of explaining the studied variables better.

  14. Clusterwise regression and market segmentation : developments and applications

    NARCIS (Netherlands)

    Wedel, M.

    1990-01-01

    The present work consists of two major parts. In the first part the literature on market segmentation is reviewed, in the second part a set of new methods for market segmentation are developed and applied.

    Part 1 starts with a discussion of the segmentation concept, and proceeds

  15. Dictionary Based Segmentation in Volumes

    DEFF Research Database (Denmark)

    Emerson, Monica Jane; Jespersen, Kristine Munk; Jørgensen, Peter Stanley

    2015-01-01

    We present a method for supervised volumetric segmentation based on a dictionary of small cubes composed of pairs of intensity and label cubes. Intensity cubes are small image volumes where each voxel contains an image intensity. Label cubes are volumes with voxelwise probabilities for a given...... label. The segmentation process is done by matching a cube from the volume, of the same size as the dictionary intensity cubes, to the most similar intensity dictionary cube, and from the associated label cube we get voxel-wise label probabilities. Probabilities from overlapping cubes are averaged...... and hereby we obtain a robust label probability encoding. The dictionary is computed from labeled volumetric image data based on weighted clustering. We experimentally demonstrate our method using two data sets from material science – a phantom data set of a solid oxide fuel cell simulation for detecting...

  16. Vessel Enhancement and Segmentation of 4D CT Lung Image Using Stick Tensor Voting

    Science.gov (United States)

    Cong, Tan; Hao, Yang; Jingli, Shi; Xuan, Yang

    2016-12-01

    Vessel enhancement and segmentation plays a significant role in medical image analysis. This paper proposes a novel vessel enhancement and segmentation method for 4D CT lung image using stick tensor voting algorithm, which focuses on addressing the vessel distortion issue of vessel enhancement diffusion (VED) method. Furthermore, the enhanced results are easily segmented using level-set segmentation. In our method, firstly, vessels are filtered using Frangi's filter to reduce intrapulmonary noises and extract rough blood vessels. Secondly, stick tensor voting algorithm is employed to estimate the correct direction along the vessel. Then the estimated direction along the vessel is used as the anisotropic diffusion direction of vessel in VED algorithm, which makes the intensity diffusion of points locating at the vessel wall be consistent with the directions of vessels and enhance the tubular features of vessels. Finally, vessels can be extracted from the enhanced image by applying level-set segmentation method. A number of experiments results show that our method outperforms traditional VED method in vessel enhancement and results in satisfied segmented vessels.

  17. Hybrid Clustering And Boundary Value Refinement for Tumor Segmentation using Brain MRI

    Science.gov (United States)

    Gupta, Anjali; Pahuja, Gunjan

    2017-08-01

    The method of brain tumor segmentation is the separation of tumor area from Brain Magnetic Resonance (MR) images. There are number of methods already exist for segmentation of brain tumor efficiently. However it’s tedious task to identify the brain tumor from MR images. The segmentation process is extraction of different tumor tissues such as active, tumor, necrosis, and edema from the normal brain tissues such as gray matter (GM), white matter (WM), as well as cerebrospinal fluid (CSF). As per the survey study, most of time the brain tumors are detected easily from brain MR image using region based approach but required level of accuracy, abnormalities classification is not predictable. The segmentation of brain tumor consists of many stages. Manually segmenting the tumor from brain MR images is very time consuming hence there exist many challenges in manual segmentation. In this research paper, our main goal is to present the hybrid clustering which consists of Fuzzy C-Means Clustering (for accurate tumor detection) and level set method(for handling complex shapes) for the detection of exact shape of tumor in minimal computational time. using this approach we observe that for a certain set of images 0.9412 sec of time is taken to detect tumor which is very less in comparison to recent existing algorithm i.e. Hybrid clustering (Fuzzy C-Means and K Means clustering).

  18. Active contour segmentation in dynamic medical imaging: application to nuclear cardiology

    International Nuclear Information System (INIS)

    Debreuve, Eric

    2000-01-01

    In emission imaging, nuclear medicine provides functional information about the organ of interest. In transmission imaging, it provides anatomical information whose goal may be the correction of physical phenomena that corrupt emission images. With both emission and transmission images, it is useful to know how to extract, either automatically or semi-automatically, the organs of interest and the body outline in the case of a large field of view. This is the aim of segmentation. We developed two active contour segmentation methods. They were implemented using level sets. The key point is the evolution velocity definition. First, we were interested in static transmission imaging of the thorax. The evolution velocity was heuristically defined and depended only on the acquired projections. The segmented transmission map was computed w/o reconstruction and could be advantageously used for attenuation correction. Then, we studied the segmentation of cardiac gated sequences. The developed space-time segmentation method results from the minimization of a variational criterion which takes into account the whole sequence. The computed segmentation could be used for calculating physiological parameters. As an illustration, we computed the ejection fraction. Finally, we exploited some level set properties to develop a non-rigid, non-parametric, and geometric registration method. We applied it for kinetic compensation of cardiac gated sequences. The registered images were then added together providing an image with noise characteristics similar to a cardiac static image but w/o motion-induced blurring. (author)

  19. Interactive segmentation techniques algorithms and performance evaluation

    CERN Document Server

    He, Jia; Kuo, C-C Jay

    2013-01-01

    This book focuses on interactive segmentation techniques, which have been extensively studied in recent decades. Interactive segmentation emphasizes clear extraction of objects of interest, whose locations are roughly indicated by human interactions based on high level perception. This book will first introduce classic graph-cut segmentation algorithms and then discuss state-of-the-art techniques, including graph matching methods, region merging and label propagation, clustering methods, and segmentation methods based on edge detection. A comparative analysis of these methods will be provided

  20. Hierarchical image segmentation for learning object priors

    Energy Technology Data Exchange (ETDEWEB)

    Prasad, Lakshman [Los Alamos National Laboratory; Yang, Xingwei [TEMPLE UNIV.; Latecki, Longin J [TEMPLE UNIV.; Li, Nan [TEMPLE UNIV.

    2010-11-10

    The proposed segmentation approach naturally combines experience based and image based information. The experience based information is obtained by training a classifier for each object class. For a given test image, the result of each classifier is represented as a probability map. The final segmentation is obtained with a hierarchial image segmentation algorithm that considers both the probability maps and the image features such as color and edge strength. We also utilize image region hierarchy to obtain not only local but also semi-global features as input to the classifiers. Moreover, to get robust probability maps, we take into account the region context information by averaging the probability maps over different levels of the hierarchical segmentation algorithm. The obtained segmentation results are superior to the state-of-the-art supervised image segmentation algorithms.

  1. Supervised variational model with statistical inference and its application in medical image segmentation.

    Science.gov (United States)

    Li, Changyang; Wang, Xiuying; Eberl, Stefan; Fulham, Michael; Yin, Yong; Dagan Feng, David

    2015-01-01

    Automated and general medical image segmentation can be challenging because the foreground and the background may have complicated and overlapping density distributions in medical imaging. Conventional region-based level set algorithms often assume piecewise constant or piecewise smooth for segments, which are implausible for general medical image segmentation. Furthermore, low contrast and noise make identification of the boundaries between foreground and background difficult for edge-based level set algorithms. Thus, to address these problems, we suggest a supervised variational level set segmentation model to harness the statistical region energy functional with a weighted probability approximation. Our approach models the region density distributions by using the mixture-of-mixtures Gaussian model to better approximate real intensity distributions and distinguish statistical intensity differences between foreground and background. The region-based statistical model in our algorithm can intuitively provide better performance on noisy images. We constructed a weighted probability map on graphs to incorporate spatial indications from user input with a contextual constraint based on the minimization of contextual graphs energy functional. We measured the performance of our approach on ten noisy synthetic images and 58 medical datasets with heterogeneous intensities and ill-defined boundaries and compared our technique to the Chan-Vese region-based level set model, the geodesic active contour model with distance regularization, and the random walker model. Our method consistently achieved the highest Dice similarity coefficient when compared to the other methods.

  2. A FAST SEGMENTATION ALGORITHM FOR C-V MODEL BASED ON EXPONENTIAL IMAGE SEQUENCE GENERATION

    Directory of Open Access Journals (Sweden)

    J. Hu

    2017-09-01

    Full Text Available For the island coastline segmentation, a fast segmentation algorithm for C-V model method based on exponential image sequence generation is proposed in this paper. The exponential multi-scale C-V model with level set inheritance and boundary inheritance is developed. The main research contributions are as follows: 1 the problems of the "holes" and "gaps" are solved when extraction coastline through the small scale shrinkage, low-pass filtering and area sorting of region. 2 the initial value of SDF (Signal Distance Function and the level set are given by Otsu segmentation based on the difference of reflection SAR on land and sea, which are finely close to the coastline. 3 the computational complexity of continuous transition are successfully reduced between the different scales by the SDF and of level set inheritance. Experiment results show that the method accelerates the acquisition of initial level set formation, shortens the time of the extraction of coastline, at the same time, removes the non-coastline body part and improves the identification precision of the main body coastline, which automates the process of coastline segmentation.

  3. a Fast Segmentation Algorithm for C-V Model Based on Exponential Image Sequence Generation

    Science.gov (United States)

    Hu, J.; Lu, L.; Xu, J.; Zhang, J.

    2017-09-01

    For the island coastline segmentation, a fast segmentation algorithm for C-V model method based on exponential image sequence generation is proposed in this paper. The exponential multi-scale C-V model with level set inheritance and boundary inheritance is developed. The main research contributions are as follows: 1) the problems of the "holes" and "gaps" are solved when extraction coastline through the small scale shrinkage, low-pass filtering and area sorting of region. 2) the initial value of SDF (Signal Distance Function) and the level set are given by Otsu segmentation based on the difference of reflection SAR on land and sea, which are finely close to the coastline. 3) the computational complexity of continuous transition are successfully reduced between the different scales by the SDF and of level set inheritance. Experiment results show that the method accelerates the acquisition of initial level set formation, shortens the time of the extraction of coastline, at the same time, removes the non-coastline body part and improves the identification precision of the main body coastline, which automates the process of coastline segmentation.

  4. The effect of goal setting on fruit and vegetable consumption and physical activity level in a Web-based intervention.

    Science.gov (United States)

    O'Donnell, Stephanie; Greene, Geoffrey W; Blissmer, Bryan

    2014-01-01

    To explore the relationship between goal setting and fruit and vegetable (FV) consumption and physical activity (PA) in an intervention for college students. Secondary data analysis of intervention group participants from a 10-week online intervention with complete weekly data (n = 724). Outcomes (cups of FV per day and minutes of PA per week) and goals for both behaviors were reported online each week. Weekly differences between goals and behaviors were calculated, as well as the proportion meeting individual goals and meeting recommendations for behaviors. There were significant (P goal setting on both behaviors and of goal group (tertile of meeting weekly goals) on behavior, as well as meeting recommendations for both behaviors. There was an increase in FV consumption (P Goal setting as part of a Web-based intervention for college students was effective, but results differed for FV and PA. Goal setting for maintaining behavior may need to differ from goal setting for changing behavior. Copyright © 2014 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

  5. Methodology for setting the reference levels in the measurements of the dose rate absorbed in air due to the environmental gamma radiation

    International Nuclear Information System (INIS)

    Dominguez Ley, Orlando; Capote Ferrera, Eduardo; Caveda Ramos, Celia; Alonso Abad, Dolores

    2008-01-01

    Full text: The methodology for setting the reference levels of the measurements of the gamma dose rate absorbed in the air is described. The registration level was obtained using statistical methods. To set the alarm levels, it was necessary to begin with certain affectation level, which activates the investigation operation mode when being reached. It is was necessary to transform this affectation level into values of the indicators selected to set the appearance of an alarm in the network, allowing its direct comparison and at the same time a bigger operability of this one. The affectation level was assumed as an effective dose of 1 mSv/y, which is the international dose limit for public. The conversion factor obtained in a practical way as a consequence of the Chernobyl accident was assumed, converting the value of annual effective dose into values of effective dose rate in air. These factors are the most important in our work, since the main task of the National Network of Environmental Radiological Surveillance of the Republic of Cuba is detecting accidents with a situations regional affectation, and this accident is precisely an example of pollution at this scale. The alarm level setting was based on the results obtained in the first year of the Chernobyl accident. For this purpose, some transformations were achieved. In the final results, a correction factor was introduced depending on the year season the measurement was made. It was taken into account the influence of different meteorological events on the measurement of this indicator. (author)

  6. A Hybrid Technique for Medical Image Segmentation

    Directory of Open Access Journals (Sweden)

    Alamgir Nyma

    2012-01-01

    Full Text Available Medical image segmentation is an essential and challenging aspect in computer-aided diagnosis and also in pattern recognition research. This paper proposes a hybrid method for magnetic resonance (MR image segmentation. We first remove impulsive noise inherent in MR images by utilizing a vector median filter. Subsequently, Otsu thresholding is used as an initial coarse segmentation method that finds the homogeneous regions of the input image. Finally, an enhanced suppressed fuzzy c-means is used to partition brain MR images into multiple segments, which employs an optimal suppression factor for the perfect clustering in the given data set. To evaluate the robustness of the proposed approach in noisy environment, we add different types of noise and different amount of noise to T1-weighted brain MR images. Experimental results show that the proposed algorithm outperforms other FCM based algorithms in terms of segmentation accuracy for both noise-free and noise-inserted MR images.

  7. Deep 3D Convolutional Encoder Networks With Shortcuts for Multiscale Feature Integration Applied to Multiple Sclerosis Lesion Segmentation.

    Science.gov (United States)

    Brosch, Tom; Tang, Lisa Y W; Youngjin Yoo; Li, David K B; Traboulsee, Anthony; Tam, Roger

    2016-05-01

    We propose a novel segmentation approach based on deep 3D convolutional encoder networks with shortcut connections and apply it to the segmentation of multiple sclerosis (MS) lesions in magnetic resonance images. Our model is a neural network that consists of two interconnected pathways, a convolutional pathway, which learns increasingly more abstract and higher-level image features, and a deconvolutional pathway, which predicts the final segmentation at the voxel level. The joint training of the feature extraction and prediction pathways allows for the automatic learning of features at different scales that are optimized for accuracy for any given combination of image types and segmentation task. In addition, shortcut connections between the two pathways allow high- and low-level features to be integrated, which enables the segmentation of lesions across a wide range of sizes. We have evaluated our method on two publicly available data sets (MICCAI 2008 and ISBI 2015 challenges) with the results showing that our method performs comparably to the top-ranked state-of-the-art methods, even when only relatively small data sets are available for training. In addition, we have compared our method with five freely available and widely used MS lesion segmentation methods (EMS, LST-LPA, LST-LGA, Lesion-TOADS, and SLS) on a large data set from an MS clinical trial. The results show that our method consistently outperforms these other methods across a wide range of lesion sizes.

  8. Robust segmentation of medical images using competitive hop field neural network as a clustering tool

    International Nuclear Information System (INIS)

    Golparvar Roozbahani, R.; Ghassemian, M. H.; Sharafat, A. R.

    2001-01-01

    This paper presents the application of competitive Hop field neural network for medical images segmentation. Our proposed approach consists of Two steps: 1) translating segmentation of the given medical image into an optimization problem, and 2) solving this problem by a version of Hop field network known as competitive Hop field neural network. Segmentation is considered as a clustering problem and its validity criterion is based on both intra set distance and inter set distance. The algorithm proposed in this paper is based on gray level features only. This leads to near optimal solutions if both intra set distance and inter set distance are considered at the same time. If only one of these distances is considered, the result of segmentation process by competitive Hop field neural network will be far from optimal solution and incorrect even for very simple cases. Furthermore, sometimes the algorithm receives at unacceptable states. Both these problems may be solved by contributing both in tera distance and inter distances in the segmentation (optimization) process. The performance of the proposed algorithm is tested on both phantom and real medical images. The promising results and the robustness of algorithm to system noises show near optimal solutions

  9. Segmentation of radiographic images under topological constraints: application to the femur.

    Science.gov (United States)

    Gamage, Pavan; Xie, Sheng Quan; Delmas, Patrice; Xu, Wei Liang

    2010-09-01

    A framework for radiographic image segmentation under topological control based on two-dimensional (2D) image analysis was developed. The system is intended for use in common radiological tasks including fracture treatment analysis, osteoarthritis diagnostics and osteotomy management planning. The segmentation framework utilizes a generic three-dimensional (3D) model of the bone of interest to define the anatomical topology. Non-rigid registration is performed between the projected contours of the generic 3D model and extracted edges of the X-ray image to achieve the segmentation. For fractured bones, the segmentation requires an additional step where a region-based active contours curve evolution is performed with a level set Mumford-Shah method to obtain the fracture surface edge. The application of the segmentation framework to analysis of human femur radiographs was evaluated. The proposed system has two major innovations. First, definition of the topological constraints does not require a statistical learning process, so the method is generally applicable to a variety of bony anatomy segmentation problems. Second, the methodology is able to handle both intact and fractured bone segmentation. Testing on clinical X-ray images yielded an average root mean squared distance (between the automatically segmented femur contour and the manual segmented ground truth) of 1.10 mm with a standard deviation of 0.13 mm. The proposed point correspondence estimation algorithm was benchmarked against three state-of-the-art point matching algorithms, demonstrating successful non-rigid registration for the cases of interest. A topologically constrained automatic bone contour segmentation framework was developed and tested, providing robustness to noise, outliers, deformations and occlusions.

  10. Segmentation of radiographic images under topological constraints: application to the femur

    International Nuclear Information System (INIS)

    Gamage, Pavan; Xie, Sheng Quan; Delmas, Patrice; Xu, Wei Liang

    2010-01-01

    A framework for radiographic image segmentation under topological control based on two-dimensional (2D) image analysis was developed. The system is intended for use in common radiological tasks including fracture treatment analysis, osteoarthritis diagnostics and osteotomy management planning. The segmentation framework utilizes a generic three-dimensional (3D) model of the bone of interest to define the anatomical topology. Non-rigid registration is performed between the projected contours of the generic 3D model and extracted edges of the X-ray image to achieve the segmentation. For fractured bones, the segmentation requires an additional step where a region-based active contours curve evolution is performed with a level set Mumford-Shah method to obtain the fracture surface edge. The application of the segmentation framework to analysis of human femur radiographs was evaluated. The proposed system has two major innovations. First, definition of the topological constraints does not require a statistical learning process, so the method is generally applicable to a variety of bony anatomy segmentation problems. Second, the methodology is able to handle both intact and fractured bone segmentation. Testing on clinical X-ray images yielded an average root mean squared distance (between the automatically segmented femur contour and the manual segmented ground truth) of 1.10 mm with a standard deviation of 0.13 mm. The proposed point correspondence estimation algorithm was benchmarked against three state-of-the-art point matching algorithms, demonstrating successful non-rigid registration for the cases of interest. A topologically constrained automatic bone contour segmentation framework was developed and tested, providing robustness to noise, outliers, deformations and occlusions. (orig.)

  11. Quantification and visualization of carotid segmentation accuracy and precision using a 2D standardized carotid map

    International Nuclear Information System (INIS)

    Chiu, Bernard; Ukwatta, Eranga; Shavakh, Shadi; Fenster, Aaron

    2013-01-01

    This paper describes a framework for vascular image segmentation evaluation. Since the size of vessel wall and plaque burden is defined by the lumen and wall boundaries in vascular segmentation, these two boundaries should be considered as a pair in statistical evaluation of a segmentation algorithm. This work proposed statistical metrics to evaluate the difference of local vessel wall thickness (VWT) produced by manual and algorithm-based semi-automatic segmentation methods (ΔT) with the local segmentation standard deviation of the wall and lumen boundaries considered. ΔT was further approximately decomposed into the local wall and lumen boundary differences (ΔW and ΔL respectively) in order to provide information regarding which of the wall and lumen segmentation errors contribute more to the VWT difference. In this study, the lumen and wall boundaries in 3D carotid ultrasound images acquired for 21 subjects were each segmented five times manually and by a level-set segmentation algorithm. The (absolute) difference measures (i.e., ΔT, ΔW, ΔL and their absolute values) and the pooled local standard deviation of manually and algorithmically segmented wall and lumen boundaries were computed for each subject and represented in a 2D standardized map. The local accuracy and variability of the segmentation algorithm at each point can be quantified by the average of these metrics for the whole group of subjects and visualized on the 2D standardized map. Based on the results shown on the 2D standardized map, a variety of strategies, such as adding anchor points and adjusting weights of different forces in the algorithm, can be introduced to improve the accuracy and variability of the algorithm. (paper)

  12. Segmentation of radiographic images under topological constraints: application to the femur

    Energy Technology Data Exchange (ETDEWEB)

    Gamage, Pavan; Xie, Sheng Quan [University of Auckland, Department of Mechanical Engineering (Mechatronics), Auckland (New Zealand); Delmas, Patrice [University of Auckland, Department of Computer Science, Auckland (New Zealand); Xu, Wei Liang [Massey University, School of Engineering and Advanced Technology, Auckland (New Zealand)

    2010-09-15

    A framework for radiographic image segmentation under topological control based on two-dimensional (2D) image analysis was developed. The system is intended for use in common radiological tasks including fracture treatment analysis, osteoarthritis diagnostics and osteotomy management planning. The segmentation framework utilizes a generic three-dimensional (3D) model of the bone of interest to define the anatomical topology. Non-rigid registration is performed between the projected contours of the generic 3D model and extracted edges of the X-ray image to achieve the segmentation. For fractured bones, the segmentation requires an additional step where a region-based active contours curve evolution is performed with a level set Mumford-Shah method to obtain the fracture surface edge. The application of the segmentation framework to analysis of human femur radiographs was evaluated. The proposed system has two major innovations. First, definition of the topological constraints does not require a statistical learning process, so the method is generally applicable to a variety of bony anatomy segmentation problems. Second, the methodology is able to handle both intact and fractured bone segmentation. Testing on clinical X-ray images yielded an average root mean squared distance (between the automatically segmented femur contour and the manual segmented ground truth) of 1.10 mm with a standard deviation of 0.13 mm. The proposed point correspondence estimation algorithm was benchmarked against three state-of-the-art point matching algorithms, demonstrating successful non-rigid registration for the cases of interest. A topologically constrained automatic bone contour segmentation framework was developed and tested, providing robustness to noise, outliers, deformations and occlusions. (orig.)

  13. Improving image segmentation by learning region affinities

    Energy Technology Data Exchange (ETDEWEB)

    Prasad, Lakshman [Los Alamos National Laboratory; Yang, Xingwei [TEMPLE UNIV.; Latecki, Longin J [TEMPLE UNIV.

    2010-11-03

    We utilize the context information of other regions in hierarchical image segmentation to learn new regions affinities. It is well known that a single choice of quantization of an image space is highly unlikely to be a common optimal quantization level for all categories. Each level of quantization has its own benefits. Therefore, we utilize the hierarchical information among different quantizations as well as spatial proximity of their regions. The proposed affinity learning takes into account higher order relations among image regions, both local and long range relations, making it robust to instabilities and errors of the original, pairwise region affinities. Once the learnt affinities are obtained, we use a standard image segmentation algorithm to get the final segmentation. Moreover, the learnt affinities can be naturally unutilized in interactive segmentation. Experimental results on Berkeley Segmentation Dataset and MSRC Object Recognition Dataset are comparable and in some aspects better than the state-of-art methods.

  14. A web-based study of the relationship of duration of insulin pump infusion set use and fasting blood glucose level in adults with type 1 diabetes.

    Science.gov (United States)

    Sampson Perrin, Alysa J; Guzzetta, Russell C; Miller, Kellee M; Foster, Nicole C; Lee, Anna; Lee, Joyce M; Block, Jennifer M; Beck, Roy W

    2015-05-01

    To evaluate the impact of infusion set use duration on glycemic control, we conducted an Internet-based study using the T1D Exchange's online patient community, Glu ( myGlu.org ). For 14 days, 243 electronically consented adults with type 1 diabetes (T1D) entered online that day's fasting blood glucose (FBG) level, the prior day's total daily insulin (TDI) dose, and whether the infusion set was changed. Mean duration of infusion set use was 3.0 days. Mean FBG level was higher with each successive day of infusion set use, increasing from 126 mg/dL on Day 1 to 133 mg/dL on Day 3 to 147 mg/dL on Day 5 (P<0.001). TDI dose did not vary with increased duration of infusion set use. Internet-based data collection was used to rapidly conduct the study at low cost. The results indicate that FBG levels increase with each additional day of insulin pump infusion set use.

  15. Continuous soil maps - a fuzzy set approach to bridge the gap between aggregation levels of process and distribution models

    NARCIS (Netherlands)

    Gruijter, de J.J.; Walvoort, D.J.J.; Gaans, van P.F.M.

    1997-01-01

    Soil maps as multi-purpose models of spatial soil distribution have a much higher level of aggregation (map units) than the models of soil processes and land-use effects that need input from soil maps. This mismatch between aggregation levels is particularly detrimental in the context of precision

  16. The Level of Vision Necessary for Competitive Performance in Rifle Shooting: Setting the Standards for Paralympic Shooting with Vision Impairment

    NARCIS (Netherlands)

    Allen, P.M.; Latham, K.; Mann, D.L.; Ravensbergen, H.J.C.; Myint, J.

    2016-01-01

    The aim of this study was to investigate the level of vision impairment (VI) that would reduce performance in shooting; to guide development of entry criteria to visually impaired (VI) shooting. Nineteen international-level shooters without VI took part in the study. Participants shot an air rifle,

  17. Mixed raster content segmentation, compression, transmission

    CERN Document Server

    Pavlidis, George

    2017-01-01

    This book presents the main concepts in handling digital images of mixed content, traditionally referenced as mixed raster content (MRC), in two main parts. The first includes introductory chapters covering the scientific and technical background aspects, whereas the second presents a set of research and development approaches to tackle key issues in MRC segmentation, compression and transmission. The book starts with a review of color theory and the mechanism of color vision in humans. In turn, the second chapter reviews data coding and compression methods so as to set the background and demonstrate the complexity involved in dealing with MRC. Chapter three addresses the segmentation of images through an extensive literature review, which highlights the various approaches used to tackle MRC segmentation. The second part of the book focuses on the segmentation of color images for optimized compression, including multi-layered decomposition and representation of MRC and the processes that can be employed to op...

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

    Science.gov (United States)

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

    2017-03-01

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

  19. Scale-space for empty catheter segmentation in PCI fluoroscopic images.

    Science.gov (United States)

    Bacchuwar, Ketan; Cousty, Jean; Vaillant, Régis; Najman, Laurent

    2017-07-01

    In this article, we present a method for empty guiding catheter segmentation in fluoroscopic X-ray images. The guiding catheter, being a commonly visible landmark, its segmentation is an important and a difficult brick for Percutaneous Coronary Intervention (PCI) procedure modeling. In number of clinical situations, the catheter is empty and appears as a low contrasted structure with two parallel and partially disconnected edges. To segment it, we work on the level-set scale-space of image, the min tree, to extract curve blobs. We then propose a novel structural scale-space, a hierarchy built on these curve blobs. The deep connected component, i.e. the cluster of curve blobs on this hierarchy, that maximizes the likelihood to be an empty catheter is retained as final segmentation. We evaluate the performance of the algorithm on a database of 1250 fluoroscopic images from 6 patients. As a result, we obtain very good qualitative and quantitative segmentation performance, with mean precision and recall of 80.48 and 63.04% respectively. We develop a novel structural scale-space to segment a structured object, the empty catheter, in challenging situations where the information content is very sparse in the images. Fully-automatic empty catheter segmentation in X-ray fluoroscopic images is an important and preliminary step in PCI procedure modeling, as it aids in tagging the arrival and removal location of other interventional tools.

  20. Anterior corpectomy via the mini-open, extreme lateral, transpsoas approach combined with short-segment posterior fixation for single-level traumatic lumbar burst fractures: analysis of health-related quality of life outcomes and patient satisfaction.

    Science.gov (United States)

    Theologis, Alexander A; Tabaraee, Ehsan; Toogood, Paul; Kennedy, Abbey; Birk, Harjus; McClellan, R Trigg; Pekmezci, Murat

    2016-01-01

    .4%) and mental health outcomes (SF-12 mental component score 50.2% ± 11.6%) after surgery. Anterior corpectomy and cage placement via a mini-open, extreme lateral, transpsoas approach supplemented by short-segment posterior instrumentation is a safe, effective alternative to conventional approaches in the treatment of single-level unstable burst fractures and is associated with excellent functional outcomes and patient satisfaction.

  1. Economic comparison of food, non food crops, set-aside at a regional level with a linear programming model

    International Nuclear Information System (INIS)

    Sourie, J.C.; Hautcolas, J.C.; Blanchet, J.

    1992-01-01

    This paper is concerned with a regional linear programming model. Its purpose is a simulation of the European Economic Community supply of non-food crops at the farm gate according to different sets of European Common Agriculture Policy (CAP) measures. The methodology is first described with a special emphasis on the aggregation problem. The model allows the simultaneous calculation of the impact of non food crops on the farmer's income and on the agricultural budget. The model is then applied to an intensive agricultural region (400 000 ha of arable land). In this region, sugar beet and rape seem the less costly resources, both for the farmers and the CAP taxpayers. An improvement of the economic situation of the two previous agents can be obtained only if a tax exemption on ethanol and rape oil and a subsidy per hactare are allowed. This subsidy can be lower than the set aside premium. (author)

  2. Developmental Screening Tools: Feasibility of Use at Primary Healthcare Level in Low- and Middle-income Settings

    OpenAIRE

    Fischer, Vinicius Jobim; Morris, Jodi; Martines, José

    2014-01-01

    ABSTRACT An estimated 150 million children have a disability. Early identification of developmental disabilities is a high priority for the World Health Organization to allow action to reduce impairments through Gap Action Program on mental health. The study identified the feasibility of using the developmental screening and monitoring tools for children aged 0-3 year(s) by non-specialist primary healthcare providers in low-resource settings. A systematic review of the literature was conducte...

  3. The RISC-V Instruction Set Manual. Volume 1: User-Level ISA, Version 2.0

    Science.gov (United States)

    2014-05-06

    RV128I Base Integer Instruction Set 81 18 Calling Convention 83 18.1 C Datatypes and Alignment...FCVT.D.S, are encoded in the OP-FP major opcode space and both the source and destination are floating-point registers. The rs2 field encodes the datatype ...of the source, and the fmt field encodes the datatype of the destination. FCVT.S.D rounds according to the RM field; FCVT.D.S will never round. 31 27

  4. Segmentation-Based And Segmentation-Free Methods for Spotting Handwritten Arabic Words

    OpenAIRE

    Ball , Gregory R.; Srihari , Sargur N.; Srinivasan , Harish

    2006-01-01

    http://www.suvisoft.com; Given a set of handwritten documents, a common goal is to search for a relevant subset. Attempting to find a query word or image in such a set of documents is called word spotting. Spotting handwritten words in documents written in the Latin alphabet, and more recently in Arabic, has received considerable attention. One issue is generating candidate word regions on a page. Attempting to definitely segment the document into such regions (automatic segmentation) can mee...

  5. A Fully Automated Penumbra Segmentation Tool

    DEFF Research Database (Denmark)

    Nagenthiraja, Kartheeban; Ribe, Lars Riisgaard; Hougaard, Kristina Dupont

    2012-01-01

    Introduction: Perfusion- and diffusion weighted MRI (PWI/DWI) is widely used to select patients who are likely to benefit from recanalization therapy. The visual identification of PWI-DWI-mismatch tissue depends strongly on the observer, prompting a need for software, which estimates potentially...... salavageable tissue, quickly and accurately. We present a fully Automated Penumbra Segmentation (APS) algorithm using PWI and DWI images. We compare automatically generated PWI-DWI mismatch mask to mask outlined manually by experts, in 168 patients. Method: The algorithm initially identifies PWI lesions......) at 600∙10-6 mm2/sec. Due to the nature of thresholding, the ADC mask overestimates the DWI lesion volume and consequently we initialized level-set algorithm on DWI image with ADC mask as prior knowledge. Combining the PWI and inverted DWI mask then yield the PWI-DWI mismatch mask. Four expert raters...

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

    Science.gov (United States)

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

    2017-09-01

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

  7. Combining segmentation and attention: a new foveal attention model

    Directory of Open Access Journals (Sweden)

    Rebeca eMarfil

    2014-08-01

    Full Text Available Artificial vision systems cannot process all the information that they receive from the world in real time because it is highly expensive and inefficient in terms of computational cost. Inspired by biological perception systems, articial attention models pursuit to select only the relevant part of the scene. Besides, it is well established that the units of attention on human vision are not merely spatial but closely related to perceptual objects (proto-objects. This implies a strong bidirectional relationship between segmentation and attention processes. Therefore, while the segmentation process is the responsible to extract the proto-objects from the scene, attention can guide segmentation, arising the concept of foveal attention. When the focus of attention is deployed from one visual unit to another, the rest of the scene is perceived but at a lower resolution that the focused object. The result is a multi-resolution visual perception in which the fovea, a dimple on the central retina, provides the highest resolution vision. In this paper, a bottom-up foveal attention model is presented. In this model the input image is a foveal image represented using a Cartesian Foveal Geometry (CFG, which encodes the field of view of the sensor as a fovea (placed in the focus of attention surrounded by a set of concentric rings with decreasing resolution. Then multirresolution perceptual segmentation is performed by building a foveal polygon using the Bounded Irregular Pyramid (BIP. Bottom-up attention is enclosed in the same structure, allowing to set the fovea over the most salient image proto-object. Saliency is computed as a linear combination of multiple low level features such us colour and intensity contrast, symmetry, orientation and roundness. Obtained results from natural images show that the performance of the combination of hierarchical foveal segmentation and saliency estimation is good in terms of accuracy and speed.

  8. SU-E-J-168: Automated Pancreas Segmentation Based On Dynamic MRI

    International Nuclear Information System (INIS)

    Gou, S; Rapacchi, S; Hu, P; Sheng, K

    2014-01-01

    Purpose: MRI guided radiotherapy is particularly attractive for abdominal targets with low CT contrast. To fully utilize this modality for pancreas tracking, automated segmentation tools are needed. A hybrid gradient, region growth and shape constraint (hGReS) method to segment 2D upper abdominal dynamic MRI is developed for this purpose. Methods: 2D coronal dynamic MR images of 2 healthy volunteers were acquired with a frame rate of 5 f/second. The regions of interest (ROIs) included the liver, pancreas and stomach. The first frame was used as the source where the centers of the ROIs were annotated. These center locations were propagated to the next dynamic MRI frame. 4-neighborhood region transfer growth was performed from these initial seeds for rough segmentation. To improve the results, gradient, edge and shape constraints were applied to the ROIs before final refinement using morphological operations. Results from hGReS and 3 other automated segmentation methods using edge detection, region growth and level set were compared to manual contouring. Results: For the first patient, hGReS resulted in the organ segmentation accuracy as measure by the Dices index (0.77) for the pancreas. The accuracy was slightly superior to the level set method (0.72), and both are significantly more accurate than the edge detection (0.53) and region growth methods (0.42). For the second healthy volunteer, hGReS reliably segmented the pancreatic region, achieving a Dices index of 0.82, 0.92 and 0.93 for the pancreas, stomach and liver, respectively, comparing to manual segmentation. Motion trajectories derived from the hGReS, level set and manual segmentation methods showed high correlation to respiratory motion calculated using a lung blood vessel as the reference while the other two methods showed substantial motion tracking errors. hGReS was 10 times faster than level set. Conclusion: We have shown the feasibility of automated segmentation of the pancreas anatomy based on

  9. Phase congruency map driven brain tumour segmentation

    Science.gov (United States)

    Szilágyi, Tünde; Brady, Michael; Berényi, Ervin

    2015-03-01

    Computer Aided Diagnostic (CAD) systems are already of proven value in healthcare, especially for surgical planning, nevertheless much remains to be done. Gliomas are the most common brain tumours (70%) in adults, with a survival time of just 2-3 months if detected at WHO grades III or higher. Such tumours are extremely variable, necessitating multi-modal Magnetic Resonance Images (MRI). The use of Gadolinium-based contrast agents is only relevant at later stages of the disease where it highlights the enhancing rim of the tumour. Currently, there is no single accepted method that can be used as a reference. There are three main challenges with such images: to decide whether there is tumour present and is so localize it; to construct a mask that separates healthy and diseased tissue; and to differentiate between the tumour core and the surrounding oedema. This paper presents two contributions. First, we develop tumour seed selection based on multiscale multi-modal texture feature vectors. Second, we develop a method based on a local phase congruency based feature map to drive level-set segmentation. The segmentations achieved with our method are more accurate than previously presented methods, particularly for challenging low grade tumours.

  10. Unsupervised Segmentation Methods of TV Contents

    Directory of Open Access Journals (Sweden)

    Elie El-Khoury

    2010-01-01

    Full Text Available We present a generic algorithm to address various temporal segmentation topics of audiovisual contents such as speaker diarization, shot, or program segmentation. Based on a GLR approach, involving the ΔBIC criterion, this algorithm requires the value of only a few parameters to produce segmentation results at a desired scale and on most typical low-level features used in the field of content-based indexing. Results obtained on various corpora are of the same quality level than the ones obtained by other dedicated and state-of-the-art methods.

  11. Elevated plasma level of pentraxin-3 predicts in-hospital and 30-day clinical outcomes in patients with non-ST-segment elevation myocardial infarction who have undergone percutaneous coronary intervention.

    Science.gov (United States)

    Guo, Rong; Li, Yuanmin; Wen, Jing; Li, Weiming; Xu, Yawei

    2014-01-01

    This investigation explored the short-term prognostic value of pentraxin-3 (PTX3) levels in patients with non-ST-segment elevation myocardial infarction (NSTEMI) treated by percutaneous coronary intervention (PCI). We measured plasma levels of PTX3 and other biomarkers in 525 PCI-treated NSTEMI patients (mean age, 57.7 years; 328 males). The associations of PTX3 levels with cardiac events and cardiac deaths occurring within 30 days of discharge were evaluated with multivariable Cox proportional hazard models. Renal function, diabetes prevalence, systolic blood pressure, heart rate and ejection fraction differed significantly in the high PTX3 (≥3.0 ng/ml, n = 107) and low PTX3 (<3.0 ng/ml, n = 418) groups (all p < 0.05). Plasma PTX3 levels were correlated with high-sensitivity C-reactive protein, troponin T and N-terminal pro-B-type natriuretic peptide in NSTEMI patients (all p < 0.05). Kaplan-Meier analysis showed in-hospital and 30-day cardiac events and deaths were higher in the high PTX3 group (both p < 0.01). Elevated PTX3 was an independent predictor of 30-day cardiac events (95% CI 1.09-1.68; p = 0.006) and mortality (95% CI 1.18-2.15; p = 0.002). An elevated plasma level of PTX3 predicts 30-day cardiac events and mortality in PCI-treated NSTEMI patients. © 2014 S. Karger AG, Basel.

  12. Segmentation, advertising and prices

    NARCIS (Netherlands)

    Galeotti, Andrea; Moraga González, José

    This paper explores the implications of market segmentation on firm competitiveness. In contrast to earlier work, here market segmentation is minimal in the sense that it is based on consumer attributes that are completely unrelated to tastes. We show that when the market is comprised by two

  13. Hierarchical layered and semantic-based image segmentation using ergodicity map

    Science.gov (United States)

    Yadegar, Jacob; Liu, Xiaoqing

    2010-04-01

    Image segmentation plays a foundational role in image understanding and computer vision. Although great strides have been made and progress achieved on automatic/semi-automatic image segmentation algorithms, designing a generic, robust, and efficient image segmentation algorithm is still challenging. Human vision is still far superior compared to computer vision, especially in interpreting semantic meanings/objects in images. We present a hierarchical/layered semantic image segmentation algorithm that can automatically and efficiently segment images into hierarchical layered/multi-scaled semantic regions/objects with contextual topological relationships. The proposed algorithm bridges the gap between high-level semantics and low-level visual features/cues (such as color, intensity, edge, etc.) through utilizing a layered/hierarchical ergodicity map, where ergodicity is computed based on a space filling fractal concept and used as a region dissimilarity measurement. The algorithm applies a highly scalable, efficient, and adaptive Peano- Cesaro triangulation/tiling technique to decompose the given image into a set of similar/homogenous regions based on low-level visual cues in a top-down manner. The layered/hierarchical ergodicity map is built through a bottom-up region dissimilarity analysis. The recursive fractal sweep associated with the Peano-Cesaro triangulation provides efficient local multi-resolution refinement to any level of detail. The generated binary decomposition tree also provides efficient neighbor retrieval mechanisms for contextual topological object/region relationship generation. Experiments have been conducted within the maritime image environment where the segmented layered semantic objects include the basic level objects (i.e. sky/land/water) and deeper level objects in the sky/land/water surfaces. Experimental results demonstrate the proposed algorithm has the capability to robustly and efficiently segment images into layered semantic objects

  14. Learning Semantic Segmentation with Diverse Supervision

    OpenAIRE

    Ye, Linwei; Liu, Zhi; Wang, Yang

    2018-01-01

    Models based on deep convolutional neural networks (CNN) have significantly improved the performance of semantic segmentation. However, learning these models requires a large amount of training images with pixel-level labels, which are very costly and time-consuming to collect. In this paper, we propose a method for learning CNN-based semantic segmentation models from images with several types of annotations that are available for various computer vision tasks, including image-level labels fo...

  15. Robust medical image segmentation for hyperthermia treatment planning

    International Nuclear Information System (INIS)

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

    2005-01-01

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

  16. "Notice the Similarities between the Two Sets …": Imperative Usage in a Corpus of Upper-Level Student Papers

    Science.gov (United States)

    Neiderhiser, Justine A.; Kelley, Patrick; Kennedy, Kohlee M.; Swales, John M.; Vergaro, Carla

    2016-01-01

    The sparse literature on the use of imperatives in research papers suggests that they are relatively common in a small number of disciplines, but rare, if used at all, in others. The present study addresses the use of imperatives in a corpus of upper-level A-graded student papers from 16 disciplines. A total of 822 papers collected within the past…

  17. Tails from previous exposures: a general problem in setting reference levels for the assessment of internal contamination

    International Nuclear Information System (INIS)

    Breuer, F.; Frittelli, L.

    1988-01-01

    Reference levels for retention and excretion are evaluated for routine and special monitoring following the intake of a fraction of ICRP annual limits (ALIs) or of a unit activity. Methodologies are also suggested for taking into account the contribution by previous intakes to excretion or retention

  18. Deep convolutional networks for pancreas segmentation in CT imaging

    Science.gov (United States)

    Roth, Holger R.; Farag, Amal; Lu, Le; Turkbey, Evrim B.; Summers, Ronald M.

    2015-03-01

    Automatic organ segmentation is an important prerequisite for many computer-aided diagnosis systems. The high anatomical variability of organs in the abdomen, such as the pancreas, prevents many segmentation methods from achieving high accuracies when compared to state-of-the-art segmentation of organs like the liver, heart or kidneys. Recently, the availability of large annotated training sets and the accessibility of affordable parallel computing resources via GPUs have made it feasible for "deep learning" methods such as convolutional networks (ConvNets) to succeed in image classification tasks. These methods have the advantage that used classification features are trained directly from the imaging data. We present a fully-automated bottom-up method for pancreas segmentation in computed tomography (CT) images of the abdomen. The method is based on hierarchical coarse-to-fine classification of local image regions (superpixels). Superpixels are extracted from the abdominal region using Simple Linear Iterative Clustering (SLIC). An initial probability response map is generated, using patch-level confidences and a two-level cascade of random forest classifiers, from which superpixel regions with probabilities larger 0.5 are retained. These retained superpixels serve as a highly sensitive initial input of the pancreas and its surroundings to a ConvNet that samples a bounding box around each superpixel at different scales (and random non-rigid deformations at training time) in order to assign a more distinct probability of each superpixel region being pancreas or not. We evaluate our method on CT images of 82 patients (60 for training, 2 for validation, and 20 for testing). Using ConvNets we achieve maximum Dice scores of an average 68% +/- 10% (range, 43-80%) in testing. This shows promise for accurate pancreas segmentation, using a deep learning approach and compares favorably to state-of-the-art methods.

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

    International Nuclear Information System (INIS)

    Iqbal, A.; Amin, M.S.

    2002-01-01

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

  20. The Level of Vision Necessary for Competitive Performance in Rifle Shooting: Setting the Standards for Paralympic Shooting with Vision Impairment.

    Science.gov (United States)

    Allen, Peter M; Latham, Keziah; Mann, David L; Ravensbergen, Rianne H J C; Myint, Joy

    2016-01-01

    The aim of this study was to investigate the level of vision impairment (VI) that would reduce performance in shooting; to guide development of entry criteria to visually impaired (VI) shooting. Nineteen international-level shooters without VI took part in the study. Participants shot an air rifle, while standing, toward a regulation target placed at the end of a 10 m shooting range. Cambridge simulation glasses were used to simulate six different levels of VI. Visual acuity (VA) and contrast sensitivity (CS) were assessed along with shooting performance in each of seven conditions of simulated impairment and compared to that with habitual vision. Shooting performance was evaluated by calculating each individual's average score in every level of simulated VI and normalizing this score by expressing it as a percentage of the baseline performance achieved with habitual vision. Receiver Operating Characteristic curves were constructed to evaluate the ability of different VA and CS cut-off criteria to appropriately classify these athletes as achieving 'expected' or 'below expected' shooting results based on their performance with different levels of VA and CS. Shooting performance remained relatively unaffected by mild decreases in VA and CS, but quickly deteriorated with more moderate losses. The ability of visual function measurements to classify shooting performance was good, with 78% of performances appropriately classified using a cut-off of 0.53 logMAR and 74% appropriately classified using a cut-off of 0.83 logCS. The current inclusion criteria for VI shooting (1.0 logMAR) is conservative, maximizing the chance of including only those with an impairment that does impact performance, but potentially excluding some who do have a genuine impairment in the sport. A lower level of impairment would include more athletes who do have a genuine impairment but would potentially include those who do not actually have an impairment that impacts performance in the sport. An

  1. The Level of Vision Necessary for Competitive Performance in Rifle Shooting: Setting the Standards for Paralympic Shooting With Vision Impairment

    Directory of Open Access Journals (Sweden)

    Peter M Allen

    2016-11-01

    Full Text Available The aim of this study was to investigate the level of vision impairment that would reduce performance in shooting; to guide development of entry criteria to visually impaired (VI shooting. Nineteen international-level shooters without vision impairment took part in the study. Participants shot an air rifle, while standing, towards a regulation target placed at the end of a 10m shooting range. Cambridge simulation glasses were used to simulate six different levels of vision impairment. Visual acuity (VA and contrast sensitivity (CS were assessed along with shooting performance in each of seven conditions of simulated impairment and compared to that with habitual vision. Shooting performance was evaluated by calculating each individual’s average score in every level of simulated vision impairment and normalising this score by expressing it as a percentage of the baseline performance achieved with habitual vision. Receiver Operating Characteristic (ROC curves were constructed to evaluate the ability of different VA and CS cut-off criteria to appropriately classify these athletes as achieving ‘expected’ or ‘below expected’ shooting results based on their performance with different levels of VA and CS. Shooting performance remained relatively unaffected by mild decreases in VA and CS, but quickly deteriorated with more moderate losses. The ability of visual function measurements to classify shooting performance was good, with 78% of performances appropriately classified using a cut-off of 0.53 logMAR and 74% appropriately classified using a cut-off of 0.83 logCS. The current inclusion criteria for VI shooting (1.0 logMAR is conservative, maximising the chance of including only those with an impairment that does impact performance, but potentially excluding some who do have a genuine impairment in the sport. A lower level of impairment would include more athletes who do have a genuine impairment but would potentially include those who do not

  2. Serum cystatin C levels in preterm newborns in our setting: Correlation with serum creatinine and preterm pathologies.

    Science.gov (United States)

    Bardallo Cruzado, Leonor; Pérez González, Elena; Martínez Martos, Zoraima; Bermudo Guitarte, Carmen; Granero Asencio, Mercedes; Luna Lagares, Salud; Marín Patón, Mariano; Polo Padilla, Juan

    2015-01-01

    Cystatin C (CysC) is a renal function marker that is not as influenced as creatinine (Cr) by endogenous or exogenous agents, so it is therefore proposed as a marker in preterm infants. To determine serum CysC values in preterm infants during the first week of life, compared to Cr. To analyze alterations caused by prematurity diseases. The design involved a longitudinal, observational study of prospective cohorts. Groups were based on gestational age (GA): Group A (24-27 weeks), Group B (28-33 weeks), Group C (34-36 weeks). Blood samples were collected at birth, within 48-72hours and after 7 days of life. SPSS v.20 software was used. The statistical methods applied included chi-squared test and ANOVA. A total of 109 preterm infants were included in the study. CysC levels were: 1.54mg/L (±0.28) at birth; 1.38mg/L (±0.36) within 48-72hours of life; 1.50mg/L (±0.31) after 7 days (p<0.05). Cr levels were: 0.64mg/dL (±0.17) at birth; 0.64mg/dL (±0.28) within 48-72hours; 0.56mg/dL (±0.19) after 7 days (P<.05). CysC values were lower in hypotensive patients and those with a respiratory disease (P<.05), and no alterations associated with other diseases were observed. There were no differences in Cr levels associated with any disease. Creatinine levels were higher in patients ≤1.500g (P<.05). Serum CysC decreased within 48-72hours of life, and this decline showed significance (P<.05). The levels increased after 7 days in all 3 GA groups, and there was no difference in CysC levels among the groups. More studies in preterm infants with hypotension and respiratory disease are required. CysC is a better glomerular filtration (GF) marker in ≤1.500g preterm infants. Copyright © 2015 The Authors. Published by Elsevier España, S.L.U. All rights reserved.

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

    Science.gov (United States)

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

    2014-12-30

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

  4. Marketing Communications as Important Segment of the Marketing Concept

    Directory of Open Access Journals (Sweden)

    Mirković Milena

    2016-06-01

    Full Text Available New frameworks operating at the international level have led to the need for a broader and more complex involvement of companies in international economic flows. In such circumstances, focus on the international and global markets becomes inevitable. Each segment companies must adapt and evolve in accordance with such conditions. Marketing as an important activity of the company in selling products or services is also changing and expanding its activities in line with international market. This leads to the creation of an international marketing concept and system as a specific approach to the processing of international economic relations. An important segment of implementation of the marketing concept is the marketing communication, which in terms of the limited number of international barriers. It is certainly possible to overcome with a well-defined marketing strategy. Clearly defined marketing strategy and well-prepared marketing mix remove barriers, to meet the set goals and lead to positive results for the company.

  5. Optimization-Based Image Segmentation by Genetic Algorithms

    Directory of Open Access Journals (Sweden)

    Rosenberger C

    2008-01-01

    Full Text Available Abstract Many works in the literature focus on the definition of evaluation metrics and criteria that enable to quantify the performance of an image processing algorithm. These evaluation criteria can be used to define new image processing algorithms by optimizing them. In this paper, we propose a general scheme to segment images by a genetic algorithm. The developed method uses an evaluation criterion which quantifies the quality of an image segmentation result. The proposed segmentation method can integrate a local ground truth when it is available in order to set the desired level of precision of the final result. A genetic algorithm is then used in order to determine the best combination of information extracted by the selected criterion. Then, we show that this approach can either be applied for gray-levels or multicomponents images in a supervised context or in an unsupervised one. Last, we show the efficiency of the proposed method through some experimental results on several gray-levels and multicomponents images.

  6. Optimization-Based Image Segmentation by Genetic Algorithms

    Directory of Open Access Journals (Sweden)

    H. Laurent

    2008-05-01

    Full Text Available Many works in the literature focus on the definition of evaluation metrics and criteria that enable to quantify the performance of an image processing algorithm. These evaluation criteria can be used to define new image processing algorithms by optimizing them. In this paper, we propose a general scheme to segment images by a genetic algorithm. The developed method uses an evaluation criterion which quantifies the quality of an image segmentation result. The proposed segmentation method can integrate a local ground truth when it is available in order to set the desired level of precision of the final result. A genetic algorithm is then used in order to determine the best combination of information extracted by the selected criterion. Then, we show that this approach can either be applied for gray-levels or multicomponents images in a supervised context or in an unsupervised one. Last, we show the efficiency of the proposed method through some experimental results on several gray-levels and multicomponents images.

  7. NSCT BASED LOCAL ENHANCEMENT FOR ACTIVE CONTOUR BASED IMAGE SEGMENTATION APPLICATION

    Directory of Open Access Journals (Sweden)

    Hiren Mewada

    2010-08-01

    Full Text Available Because of cross-disciplinary nature, Active Contour modeling techniques have been utilized extensively for the image segmentation. In traditional active contour based segmentation techniques based on level set methods, the energy functions are defined based on the intensity gradient. This makes them highly sensitive to the situation where the underlying image content is characterized by image nonhomogeneities due to illumination and contrast condition. This is the most difficult problem to make them as fully automatic image segmentation techniques. This paper introduces one of the approaches based on image enhancement to this problem. The enhanced image is obtained using NonSubsampled Contourlet Transform, which improves the edges strengths in the direction where the illumination is not proper and then active contour model based on level set technique is utilized to segment the object. Experiment results demonstrate that proposed method can be utilized along with existing active contour model based segmentation method under situation characterized by intensity non-homogeneity to make them fully automatic.

  8. Development of a working set of waste package performance criteria for deepsea disposal of low-level radioactive waste. Final report

    International Nuclear Information System (INIS)

    Columbo, P.; Fuhrmann, M.; Neilson, R.M. Jr; Sailor, V.L.

    1982-11-01

    The United States ocean dumping regulations developed pursuant to PL92-532, the Marine Protection, Research, and Sanctuaries Act of 1972, as amended, provide for a general policy of isolation and containment of low-level radioactive waste after disposal into the ocean. In order to determine whether any particular waste packaging system is adequate to meet this general requirement, it is necessary to establish a set of performance criteria against which to evaluate a particular packaging system. These performance criteria must present requirements for the behavior of the waste in combination with its immobilization agent and outer container in a deepsea environment. This report presents a working set of waste package performance criteria, and includes a glossary of terms, characteristics of low-level radioactive waste, radioisotopes of importance in low-level radioactive waste, and a summary of domestic and international regulations which control the ocean disposal of these wastes

  9. Pancreas and cyst segmentation

    Science.gov (United States)

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

    2016-03-01

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

  10. The politics of agenda setting at the global level: key informant interviews regarding the International Labour Organization Decent Work Agenda.

    Science.gov (United States)

    Di Ruggiero, Erica; Cohen, Joanna E; Cole, Donald C

    2014-07-01

    Global labour markets continue to undergo significant transformations resulting from socio-political instability combined with rises in structural inequality, employment insecurity, and poor working conditions. Confronted by these challenges, global institutions are providing policy guidance to protect and promote the health and well-being of workers. This article provides an account of how the International Labour Organization's Decent Work Agenda contributes to the work policy agendas of the World Health Organization and the World Bank. This qualitative study involved semi-structured interviews with representatives from three global institutions--the International Labour Organization (ILO), the World Health Organization and the World Bank. Of the 25 key informants invited to participate, 16 took part in the study. Analysis for key themes was followed by interpretation using selected agenda setting theories. Interviews indicated that through the Decent Work Agenda, the International Labour Organization is shaping the global policy narrative about work among UN agencies, and that the pursuit of decent work and the Agenda were perceived as important goals with the potential to promote just policies. The Agenda was closely linked to the World Health Organization's conception of health as a human right. However, decent work was consistently identified by World Bank informants as ILO terminology in contrast to terms such as job creation and job access. The limited evidence base and its conceptual nature were offered as partial explanations for why the Agenda has yet to fully influence other global institutions. Catalytic events such as the economic crisis were identified as creating the enabling conditions to influence global work policy agendas. Our evidence aids our understanding of how an issue like decent work enters and stays on the policy agendas of global institutions, using the Decent Work Agenda as an illustrative example. Catalytic events and policy

  11. The politics of agenda setting at the global level: key informant interviews regarding the International Labour Organization Decent Work Agenda

    Science.gov (United States)

    2014-01-01

    Background Global labour markets continue to undergo significant transformations resulting from socio-political instability combined with rises in structural inequality, employment insecurity, and poor working conditions. Confronted by these challenges, global institutions are providing policy guidance to protect and promote the health and well-being of workers. This article provides an account of how the International Labour Organization’s Decent Work Agenda contributes to the work policy agendas of the World Health Organization and the World Bank. Methods This qualitative study involved semi-structured interviews with representatives from three global institutions – the International Labour Organization (ILO), the World Health Organization and the World Bank. Of the 25 key informants invited to participate, 16 took part in the study. Analysis for key themes was followed by interpretation using selected agenda setting theories. Results Interviews indicated that through the Decent Work Agenda, the International Labour Organization is shaping the global policy narrative about work among UN agencies, and that the pursuit of decent work and the Agenda were perceived as important goals with the potential to promote just policies. The Agenda was closely linked to the World Health Organization’s conception of health as a human right. However, decent work was consistently identified by World Bank informants as ILO terminology in contrast to terms such as job creation and job access. The limited evidence base and its conceptual nature were offered as partial explanations for why the Agenda has yet to fully influence other global institutions. Catalytic events such as the economic crisis were identified as creating the enabling conditions to influence global work policy agendas. Conclusions Our evidence aids our understanding of how an issue like decent work enters and stays on the policy agendas of global institutions, using the Decent Work Agenda as an illustrative

  12. Leveling up: enabling diverse users to locate and effectively use unfamiliar data sets through NCAR's Research Data Archive

    Science.gov (United States)

    Peng, G. S.

    2016-12-01

    Research necessarily expands upon the volume and variety of data used in prior work. Increasingly, investigators look outside their primary areas of expertise for data to incorporate into their research. Locating and using the data that they need, which may be described in terminology from other fields of science or be encoded in unfamiliar data formats, present often insurmountable barriers for potential users. As a data provider of a diverse collection of over 600 atmospheric and oceanic data sets (DS) (http://rda.ucar.edu), we seek to reduce or remove those barriers. Serving a broadening and increasing user base with fixed and finite resources requires automation. Our software harvests metadata descriptors about the data from the data files themselves. Data curators/subject matter experts augment the machine-generated metadata as needed. Metadata powers our data search tools. Users may search for data in a myriad of ways ranging from free text queries to GCMD keywords to faceted searches capable of narrowing down selections by specific criteria. Users are offered customized lists of DSs fitting their criteria with links to DS main information pages that provide detailed information about each DS. Where appropriate, they link to the NCAR Climate Data Guide for expert guidance about strengths and weaknesses of that particular DS. Once users find the data sets they need, we provide modular lessons for common data tasks. The lessons may be data tool install guides, data recipes, blog posts, or short YouTube videos. Rather than overloading users with reams of information, we provide targeted lessons when the user is most receptive, e.g. when they want to use data in an unfamiliar format. We add new material when we discover common points of confusion. Each educational resource is tagged with DS ID numbers so that they are automatically linked with the relevant DSs. How can data providers leverage the work of other data providers? Can a common tagging scheme for data

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

    OpenAIRE

    ŠVECOVÁ, Iveta

    2013-01-01

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

  14. Systems-Level Annotation of a Metabolomics Data Set Reduces 25 000 Features to Fewer than 1000 Unique Metabolites.

    Science.gov (United States)

    Mahieu, Nathaniel G; Patti, Gary J

    2017-10-03

    When using liquid chromatography/mass spectrometry (LC/MS) to perform untargeted metabolomics, it is now routine to detect tens of thousands of features from biological samples. Poor understanding of the data, however, has complicated interpretation and masked the number of unique metabolites actually being measured in an experiment. Here we place an upper bound on the number of unique metabolites detected in Escherichia coli samples analyzed with one untargeted metabolomics method. We first group multiple features arising from the same analyte, which we call "degenerate features", using a context-driven annotation approach. Surprisingly, this analysis revealed thousands of previously unreported degeneracies that reduced the number of unique analytes to ∼2961. We then applied an orthogonal approach to remove nonbiological features from the data using the 13 C-based credentialing technology. This further reduced the number of unique analytes to less than 1000. Our 90% reduction in data is 5-fold greater than previously published studies. On the basis of the results, we propose an alternative approach to untargeted metabolomics that relies on thoroughly annotated reference data sets. To this end, we introduce the creDBle database ( http://creDBle.wustl.edu ), which contains accurate mass, retention time, and MS/MS fragmentation data as well as annotations of all credentialed features.

  15. Bayesian automated cortical segmentation for neonatal MRI

    Science.gov (United States)

    Chou, Zane; Paquette, Natacha; Ganesh, Bhavana; Wang, Yalin; Ceschin, Rafael; Nelson, Marvin D.; Macyszyn, Luke; Gaonkar, Bilwaj; Panigrahy, Ashok; Lepore, Natasha

    2017-11-01

    Several attempts have been made in the past few years to develop and implement an automated segmentation of neonatal brain structural MRI. However, accurate automated MRI segmentation remains challenging in this population because of the low signal-to-noise ratio, large partial volume effects and inter-individual anatomical variability of the neonatal brain. In this paper, we propose a learning method for segmenting the whole brain cortical grey matter on neonatal T2-weighted images. We trained our algorithm using a neonatal dataset composed of 3 fullterm and 4 preterm infants scanned at term equivalent age. Our segmentation pipeline combines the FAST algorithm from the FSL library software and a Bayesian segmentation approach to create a threshold matrix that minimizes the error of mislabeling brain tissue types. Our method shows promising results with our pilot training set. In both preterm and full-term neonates, automated Bayesian segmentation generates a smoother and more consistent parcellation compared to FAST, while successfully removing the subcortical structure and cleaning the edges of the cortical grey matter. This method show promising refinement of the FAST segmentation by considerably reducing manual input and editing required from the user, and further improving reliability and processing time of neonatal MR images. Further improvement will include a larger dataset of training images acquired from different manufacturers.

  16. The Impact of Video Length on Learning in a Middle-Level Flipped Science Setting: Implications for Diversity Inclusion

    Science.gov (United States)

    Slemmons, Krista; Anyanwu, Kele; Hames, Josh; Grabski, Dave; Mlsna, Jeffery; Simkins, Eric; Cook, Perry

    2018-05-01

    Popularity of videos for classroom instruction has increased over the years due to affordability and user-friendliness of today's digital video cameras. This prevalence has led to an increase in flipped, K-12 classrooms countrywide. However, quantitative data establishing the appropriate video length to foster authentic learning is limited, particularly in middle-level classrooms. We focus on this aspect of video technology in two flipped science classrooms at the middle school level to determine the optimal video length to enable learning, increase retention and support student motivation. Our results indicate that while assessments directly following short videos were slightly higher, these findings were not significantly different from scores following longer videos. While short-term retention of material did not seem to be influenced by video length, longer-term retention for males and students with learning disabilities was higher following short videos compared to long as assessed on summative assessments. Students self-report that they were more engaged, had enhanced focus, and had a perceived higher retention of content following shorter videos. This study has important implications for student learning, application of content, and the development of critical thinking skills. This is particularly paramount in an era where content knowledge is just a search engine away.

  17. Electronic Gaming Machine (EGM) Environments: Market Segments and Risk.

    Science.gov (United States)

    Rockloff, Matthew; Moskovsky, Neda; Thorne, Hannah; Browne, Matthew; Bryden, Gabrielle

    2017-12-01

    This study used a marketing-research paradigm to explore gamblers' attraction to EGMs based on different elements of the environment. A select set of environmental features was sourced from a prior study (Thorne et al. in J Gambl Issues 2016b), and a discrete choice experiment was conducted through an online survey. Using the same dataset first described by Rockloff et al. (EGM Environments that contribute to excess consumption and harm, 2015), a sample of 245 EGM gamblers were sourced from clubs in Victoria, Australia, and 7516 gamblers from an Australian national online survey-panel. Participants' choices amongst sets of hypothetical gambling environments allowed for an estimation of the implied individual-level utilities for each feature (e.g., general sounds, location, etc.). K-means clustering on these utilities identified four unique market segments for EGM gambling, representing four different types of consumers. The segments were named according to their dominant features: Social, Value, High Roller and Internet. We found that the environments orientated towards the Social and Value segments were most conducive to attracting players with relatively few gambling problems, while the High Roller and Internet-focused environments had greater appeal for players with problems and vulnerabilities. This study has generated new insights into the kinds of gambling environments that are most consistent with safe play.

  18. A browser-based 3D Visualization Tool designed for comparing CERES/CALIOP/CloudSAT level-2 data sets.

    Science.gov (United States)

    Chu, C.; Sun-Mack, S.; Chen, Y.; Heckert, E.; Doelling, D. R.

    2017-12-01

    In Langley NASA, Clouds and the Earth's Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS) are merged with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and CloudSat Cloud Profiling Radar (CPR). The CERES merged product (C3M) matches up to three CALIPSO footprints with each MODIS pixel along its ground track. It then assigns the nearest CloudSat footprint to each of those MODIS pixels. The cloud properties from MODIS, retrieved using the CERES algorithms, are included in C3M with the matched CALIPSO and CloudSat products along with radiances from 18 MODIS channels. The dataset is used to validate the CERES retrieved MODIS cloud properties and the computed TOA and surface flux difference using MODIS or CALIOP/CloudSAT retrieved clouds. This information is then used to tune the computed fluxes to match the CERES observed TOA flux. A visualization tool will be invaluable to determine the cause of these large cloud and flux differences in order to improve the methodology. This effort is part of larger effort to allow users to order the CERES C3M product sub-setted by time and parameter as well as the previously mentioned visualization capabilities. This presentation will show a new graphical 3D-interface, 3D-CERESVis, that allows users to view both passive remote sensing satellites (MODIS and CERES) and active satellites (CALIPSO and CloudSat), such that the detailed vertical structures of cloud properties from CALIPSO and CloudSat are displayed side by side with horizontally retrieved cloud properties from MODIS and CERES. Similarly, the CERES computed profile fluxes whether using MODIS or CALIPSO and CloudSat clouds can also be compared. 3D-CERESVis is a browser-based visualization tool that makes uses of techniques such as multiple synchronized cursors, COLLADA format data and Cesium.

  19. Economic evaluation and the Jordan Rational Drug List: an exploratory study of national-level priority setting.

    Science.gov (United States)

    Lafi, Rania; Robinson, Suzanne; Williams, Iestyn

    2012-01-01

    To explore the extent of and barriers to the use of economic evaluation in compiling the Jordan Rational Drug List in the health care system of Jordan. The research reported in this article involved a case study of the Jordan Rational Drug List. Data collection methods included semi-structured interviews with decision makers and analysis of secondary documentary sources. The case study was supplemented by addit