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Using prior shape and intensity profile in medical image segmentation
2003
Proceedings Ninth IEEE International Conference on Computer Vision
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The second part determines the 'best' parameter used in the first part by maximizing the mutual information of the image geometry between the prior and an aligned novel image over all the alignments, that ...
These results indicate that the proposed model provides close agreement with expert traced borders, and the parameter determined in this model for one image can be used for images with similar properties ...
Chen is supported by NIH grants P50-DC03888 and NS42075. H.D.Tagare is supported by the grant R01-LM06911 from the National Library of Medicine. ...
doi:10.1109/iccv.2003.1238474
dblp:conf/iccv/ChenHTRWG03
fatcat:upc23ozo6vdlhiltghluejcasu
Comparison of statistical models performance in case of segmentation using a small amount of training datasets
2010
The Visual Computer
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Model-based image segmentation has been extensively used in medical imaging to learn both shape and appearance of anatomical structures from training datasets. ...
For shape, both PCA-based priors and shape memory strategies are tested. ...
Introduction Building meaningful priors for model-based image segmentation purposes is an important topic in medical imaging. ...
doi:10.1007/s00371-010-0536-9
fatcat:uohlbdvmnzgc7bqt4fk2mjuire
A Coupled Minimization Problem for Medical Image Segmentation with Priors
2006
International Journal of Computer Vision
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We present a coupled minimization problem for image segmentation using prior shape and intensity profile. ...
By this coupling the segmentation arrives at higher image gradient, forms a shape similar to the prior, and captures the prior intensity profile. ...
David Wilson, Department of Mathematics, University of Florida, and Dr. Edward A. Geiser, Division of Cardiology, Department of Medicine, University of Florida for providing the ...
doi:10.1007/s11263-006-8524-2
fatcat:3y47cqeykzdy7bzhbklernr6ie
Profile Scale-Spaces for Multiscale Image Match
[chapter]
2004
Lecture Notes in Computer Science
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We present a novel image-match model for use in Bayesian segmentation, a multiscale extension of image profile models akin to those in Active Shape Models. ...
A framework for model-building and segmentation has been built, and testing and validation are in progress with a dataset of 70 segmented images of the caudate nucleus. ...
Acknowledgments The caudate images and expert manual segmentations are funded by NIH RO1 MH61696 and NIMH MH 64580 (PI: Joe Piven). ...
doi:10.1007/978-3-540-30135-6_22
fatcat:w3gxiq5m4vawro7cmym33zejkq
Evolutionary Deformable Models for Medical Image Segmentation: A Genetic Algorithm Approach to Optimizing Learned, Intuitive, and Localized Medial-Based Shape Deformation
[chapter]
2010
Genetic and Evolutionary Computation
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We present a novel evolutionary computing based approach to medical image segmentation. ...
We demonstrate our work through its application to corpus callosum segmentation in mid-sagittal brain magnetic resonance images (MRI). ...
Martha Shenton of the Harvard Medical School for providing the MRI data, and Peter Plett for assisting with code development. ...
doi:10.1002/9780470973134.ch4
fatcat:ib6j2ogcdnbxfkoif4wvxs7r4y
Mixture Modeling of Global Shape Priors and Autoencoding Local Intensity Priors for Left Atrium Segmentation
[article]
2019
arXiv
pre-print
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Here, we propose a maximum-a-posteriori formulation that relies on a generative image model by incorporating both local intensity and global shape priors. ...
Difficult image segmentation problems, for instance left atrium MRI, can be addressed by incorporating shape priors to find solutions that are consistent with known objects. ...
Introduction Automatic image segmentation is an important enabling technology in most medical imaging applications that involve soft tissue imaging, e.g., neurology, cardiology, and oncology. ...
arXiv:1903.06260v1
fatcat:dgc7ahto5zebbcdthsxdd24xoe
Segmentation by surface-to-image registration
2006
Medical Imaging 2006: Image Processing
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external forces in which weights and forces are determined by gradients and local intensity profiles obtained from images. ...
This paper presents a new image segmentation algorithm using surface-to-image registration. ...
methods in medical image segmentation). ...
doi:10.1117/12.649572
dblp:conf/miip/XieTGLDC06
fatcat:wejlct5g2bb4lo3vkr7ii5qj2y
3D Image Segmentation of Deformable Objects with Shape-Appearance Joint Prior Models
[chapter]
2003
Lecture Notes in Computer Science
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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 ...
By using PCA, we can build a model of the shape-intensity profile of the left putamen. ...
doi:10.1007/978-3-540-39899-8_71
fatcat:36issxxnorhopgtogpyhevr7qa
Model-Based Segmentation
[chapter]
2010
Biomedical Image Processing
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Several approaches of how gray level appearance can be modeled are presented, and search algorithms that use this knowledge to segment the modeled structures in new images are described. ...
Common choices for image forces are presented, and how to evolve the mesh to adapt to certain structures. Second, the method of point-based statistical shape models is described. ...
The meshes are driven by the matching of intensity profiles; Upper row: reference CT image scan (left) and head segmented with a simplex mesh (right). ...
doi:10.1007/978-3-642-15816-2_11
fatcat:tj4v5thgnjhafhlmoz47vskcwu
A Nonparametric Shape Prior Constrained Active Contour Model for Segmentation of Coronaries in CTA Images
2014
Computational and Mathematical Methods in Medicine
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The possible leakage, which cannot be identified by using intensity features alone, is reduced through the application of the proposed shape constraint, where the shape of circular sampled intensity profile ...
We present a nonparametric shape constrained algorithm for segmentation of coronary arteries in computed tomography images within the framework of active contours. ...
The leakage problem is often encountered in medical image segmentation when only intensity features are utilized, since boundaries between different objects cannot be always defined by intensities. ...
doi:10.1155/2014/302805
pmid:24803950
pmcid:PMC3988742
fatcat:waa3nul6x5bsdfcylgm3tc3jr4
Echocardiographic contour extraction with local and global priors through boosting and level sets
2009
2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
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Second, the local priors can use any features from the images including different filters and intensity profiles. ...
First, boosting encodes the knowledge about the image information and the temporal cardiac wall motion effectively by using spatiotemporal filters. ...
[1] suggested using intensity profiles of object contours by training an intensity model from a set of images. ...
doi:10.1109/cvprw.2009.5204349
dblp:conf/cvpr/OktayA09
fatcat:bftkyy2qrfetbjmxjx4eam7awu
Echocardiographic contour extraction with local and global priors through boosting and level sets
2009
2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
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Second, the local priors can use any features from the images including different filters and intensity profiles. ...
First, boosting encodes the knowledge about the image information and the temporal cardiac wall motion effectively by using spatiotemporal filters. ...
[1] suggested using intensity profiles of object contours by training an intensity model from a set of images. ...
doi:10.1109/cvpr.2009.5204349
fatcat:nxy6qbenp5duhprrqnnmtusvma
ShapeCut: Bayesian surface estimation using shape-driven graph
2017
Medical Image Analysis
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A variety of medical image segmentation problems present significant technical challenges, including heterogeneous pixel intensities, noisy/ill-defined boundaries and irregular shapes with high variability ...
In this paper, we propose a maximum-a-posteriori formulation that relies on a generative image model by incorporating both local and global shape priors. ...
and Alan Morris for assisting in fibrosis and scar analysis. ...
doi:10.1016/j.media.2017.04.005
pmid:28582702
pmcid:PMC5546629
fatcat:pccmvszcureehoia4jxeo5wz5i
Automatic Analysis of Pediatric Renal Ultrasound Using Shape, Anatomical and Image Acquisition Priors
[chapter]
2013
Lecture Notes in Computer Science
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In this paper we present a segmentation method for ultrasound (US) images of the pediatric kidney, a difficult and barely studied problem. ...
Our method segments the kidney on 2D sagittal US images and relies on minimal user intervention and a combination of improvements made to the Active Shape Model (ASM) framework. ...
This project was supported by a philanthropic gift from the Government of Abu Dhabi to Children's National Medical Center. ...
doi:10.1007/978-3-642-40760-4_33
fatcat:4phnsmpnmzhcxnhelqkz4xwuxy
3D image segmentation of deformable objects with joint shape-intensity prior models using level sets
2004
Medical Image Analysis
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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
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