Filters








95,739 Hits in 9.8 sec

Using Prior Shape and Points in Medical Image Segmentation [chapter]

Yunmei Chen, Weihong Guo, Feng Huang, David Wilson, Edward A. Geiser
2003 Lecture Notes in Computer Science  
One measures high image gradients, the other two measure the disparity in shape between the interface and prior, and the distance from the prior points to the interface, respectively.  ...  In this paper we propose a new variational framework for image segmentation that incorporates the information of expected shape and a few points on the boundary into geodesic active contours.  ...  Wilson and E.A.Geiser for providing ultrasound heart images. Yunmei Chen is partially supported by NIH grants P50-DC03888, and NIH NS42075.  ... 
doi:10.1007/978-3-540-45063-4_19 fatcat:5i7q47szyzb7virkuuor62bsva

Analysis of contour evolution methods for segmentation of medical images

S Divya, K.B Jayanthi
2015 2015 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS)  
Deformable models are promising and robustly researched computer-assisted medical image analysis technique. Here the segmentation is done by using the contour evolution method.  ...  Among the various prior models, shape is the most important to acquire the heart shape accurately. This approach is used to segment the heart from the computed tomographic image.  ...  In this paper, we use the shape of the object as the contour for the segmentation of 2D medical images [11] - [12] .  ... 
doi:10.1109/iciiecs.2015.7192938 fatcat:qxzzijdyi5akddprvhejpjnvly

Medical Image Segmentation Using Minimal Path Deformable Models With Implicit Shape Priors

P. Yan, A.A. Kassim
2006 IEEE Transactions on Information Technology in Biomedicine  
This paper presents a new method for segmentation of medical images by extracting organ contours, using minimal path deformable models incorporated with statistical shape priors.  ...  Index Terms-Deformable models, energy minimization, medical image segmentation, minimal path, shape prior modeling.  ...  Wang and Dr. B. Shuter of National University Hospital, Singapore, for providing data sets and manual segmentation results used in this work.  ... 
doi:10.1109/titb.2006.874199 pmid:17044401 fatcat:apaez2kbkncx3mivewod3rugei

Neighbor-Constrained Segmentation With Level Set Based 3-D Deformable Models

J. Yang, L.H. Staib, J.S. Duncan
2004 IEEE Transactions on Medical Imaging  
A novel method for the segmentation of multiple objects from three-dimensional (3-D) medical images using interobject constraints is presented.  ...  Index Terms-Deformable models, level set, neighbor-constrained segmentation, neighbor prior model, shape prior model, 3-D segmentation.  ...  Win and R. T. Schultz for help with the visualization and manual tracing of the MR data. They also thank H. Tagare for the many thoughtful discussions and comments.  ... 
doi:10.1109/tmi.2004.830802 pmid:15338728 pmcid:PMC2838450 fatcat:4a4cy765jvdajmcmfprp56sixy

A Generalized Level Set Formulation of the Mumford-Shah Functional with Shape Prior for Medical Image Segmentation [chapter]

Lishui Cheng, Xian Fan, Jie Yang, Yun Zhu
2005 Lecture Notes in Computer Science  
Image segmentation is an important research topic in medical image analysis area.  ...  The region force provides a global criterion and increases the speed of convergence, the gradient information allows for a better spatial localization while the shape prior makes the model especially useful  ...  The authors Lishui Cheng and Xian Fan would like to particularly thank for the many helpful and stimulating discussions with Dr. Chenyang Xu and Dr. Yuanjie Zheng on medical image segmentation.  ... 
doi:10.1007/11569541_8 fatcat:rkg3cweh6rfp5ddb5dsk34egky

3D image segmentation of deformable objects with joint shape-intensity prior models using level sets

J YANG
2004 Medical Image Analysis  
We define a maximum a posteriori (MAP) estimation model using the joint prior information of the object shape and the image gray levels to realize image segmentation.  ...  We propose a novel method for 3D image segmentation, where a Bayesian formulation, based on joint prior knowledge of the object shape and the image gray levels, along with information derived from the  ...  Finally, they thank the editors and reviewers for their general and detailed comments and suggestions, which very much helped to improve the presentation of the paper.  ... 
doi:10.1016/j.media.2004.06.008 pmid:15450223 pmcid:PMC2832842 fatcat:kyjaa5iquzaqjaxxxqbxd3dbr4

Shape prior based image segmentation using manifold learning

Arturo Mendoza Quispe, Caroline Petitjean
2015 2015 International Conference on Image Processing Theory, Tools and Applications (IPTA)  
In image segmentation, the shape knowledge of the object may be used to guide the segmentation process.  ...  Finally, some segmentation results are shown on a medical imaging application.  ...  ACKNOWLEDGEMENTS This project is co-financed by the European Union with the European regional development fund (ERDF) and by the Haute-Normandie Regional Council.  ... 
doi:10.1109/ipta.2015.7367113 dblp:conf/ipta/QuispeP15 fatcat:3qszktceefc6fa6nsjh753ujxu

3D Image Segmentation of Deformable Objects with Shape-Appearance Joint Prior Models [chapter]

Jing Yang, James S. Duncan
2003 Lecture Notes in Computer Science  
We define a Maximum A Posteriori(MAP) estimation model using the joint prior information of the shape and image gray levels to realize image segmentation.  ...  We propose a novel method for 3D image segmentation, where a Bayesian formulation, based on joint prior knowledge of the shape and the image gray levels, along with information derived from the input image  ...  Introduction The accurate segmentation and quantitative analysis of structures in an image is a fundamental issue in a variety of applications including medical image processing, computer vision and pattern  ... 
doi:10.1007/978-3-540-39899-8_71 fatcat:36issxxnorhopgtogpyhevr7qa

Segmentation of medical images using a genetic algorithm

Payel Ghosh, Melanie Mitchell
2006 Proceedings of the 8th annual conference on Genetic and evolutionary computation - GECCO '06  
Shape and textural priors derived from manually segmented images are used to constrain the evolution of the segmenting curve over successive generations.  ...  Segmentation of medical images is challenging due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries.  ...  Arthur Hung for providing training data for this analysis and to Dr. Xubo Song and Kun Yang for their help in providing data and for valuable discussions on this project.  ... 
doi:10.1145/1143997.1144183 dblp:conf/gecco/GhoshM06 fatcat:frgl6g3oerbsvjn2r7oxe756sa

Robust Medical Images Segmentation Using Learned Shape and Appearance Models [chapter]

Ayman El-Baz, Georgy Gimel'farb
2009 Lecture Notes in Computer Science  
We propose a novel parametric deformable model controlled by shape and visual appearance priors learned from a training subset of co-aligned medical images of goal objects.  ...  Due to the analytical shape and appearance priors and a simple Expectation-Maximization procedure for getting the object and background LCDG, our segmentation is considerably faster than with most of the  ...  Introduction Parametric and geometric deformable models are widely used for image segmentation.  ... 
doi:10.1007/978-3-642-04268-3_35 fatcat:37iv6mwkeng4xeujyrge5dr74e

An Explicit Shape-Constrained MRF-Based Contour Evolution Method for 2-D Medical Image Segmentation

Deepak R. Chittajallu, Nikos Paragios, Ioannis A. Kakadiaris
2014 IEEE journal of biomedical and health informatics  
While segmenting organs in medical images, which is the topic of this paper, a significant amount of prior knowledge about the shape, appearance, and location of the organs is available that can be used  ...  Index Terms-Medical image segmentation, Markov random field model, contour evolution, shape priors.  ...  A variety of approaches have been proposed, both for image segmentation in general [1] and for medical image segmentation in particular [2] .  ... 
doi:10.1109/jbhi.2013.2257820 pmid:24403409 fatcat:7onhr4t4dzdqjhhsldb2yg3tpm

Statistical region-based active contours for segmentation: An overview

F. Lecellier, S. Jehan-Besson, J. Fadili
2014 IRBM  
In this paper we propose a brief survey on geometric variational approaches and more precisely on statistical region-based active contours for medical image segmentation.  ...  Examples on real medical images are given to illustrate some of the given criteria.  ...  Clouard from GREYC Laboratory for their useful image processing libraries Gmic and Pandore. [1] S. Zhu, A.  ... 
doi:10.1016/j.irbm.2013.12.002 fatcat:7zarlkcxzbaupocf6bvrnemej4

Shape regularized active contour based on dynamic programming for anatomical structure segmentation

Tianli Yu, Jiebo Luo, Amit Singhal, Narendra Ahuja, J. Michael Fitzpatrick, Joseph M. Reinhardt
2005 Medical Imaging 2005: Image Processing  
We present a method to incorporate nonlinear shape prior constraints into segmenting different anatomical structures in medical images.  ...  Both applications have shown that our method is effective and versatile in segmenting various anatomical structures under prior shape constraints; and it is robust to noise and local minima caused by clutter  ...  Senn, Hui Luo, Michael Heath, Teresa Levy, and Xiaohui Wang for help and discussions.  ... 
doi:10.1117/12.594662 dblp:conf/miip/YuLSA05 fatcat:3uvsro2dj5eunknxlqjfqy4rby

Segmentation of kidney from ultrasound images based on texture and shape priors

Jun Xie, Yifeng Jiang, Hung-tat Tsui
2005 IEEE Transactions on Medical Imaging  
This paper presents a novel texture and shape priors based method for kidney segmentation in ultrasound (US) images.  ...  Index Terms-Image segmentation, kidney segmentation, texture and shape prior, ultrasound image processing.  ...  Left Kidney Segmentation To segment kidney in US images, we have tried to derive the shape prior model from US images directly.  ... 
doi:10.1109/tmi.2004.837792 pmid:15638185 fatcat:ymylzulkszcwngk2ruvzhpmiae

Shape-Driven 3D Segmentation Using Spherical Wavelets [chapter]

Delphine Nain, Steven Haker, Aaron Bobick, Allen Tannenbaum
2006 Lecture Notes in Computer Science  
This paper presents a novel active surface segmentation algorithm using a multiscale shape representation and prior.  ...  We define a parametric model of a surface using spherical wavelet functions and learn a prior probability distribution over the wavelet coefficients to model shape variations at different scales and spatial  ...  This work is part of the National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149.  ... 
doi:10.1007/11866565_9 fatcat:6rxbbq7isbdsjchyqaco3z5x5q
« Previous Showing results 1 — 15 out of 95,739 results