Full automatic framework for segmentation of MR brain image
Magnetic Resonance Imaging is one of the most important medical imaging techniques for the investigating diseases of the human brain. A novel method for automatic segmentation Magnetic resonance brain image framework is proposed in this paper. This method consists of three-step segmentation procedur...
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2005
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Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/9502 http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Apr05-2.pdf |
Aporte de: | Aportado por :
SEDICI (UNLP) de
Universidad Nacional de La Plata .
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I19-R120-10915-95022019-06-19T04:02:55Z http://sedici.unlp.edu.ar/handle/10915/9502 http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Apr05-2.pdf issn:1666-6038 Full automatic framework for segmentation of MR brain image Zheng, Chong-Xun Lin, Pan Yang, Yong Gu, Jian-Wen 2005-04 2008-05-20T03:00:00Z en Ciencias Informáticas Segmentation level set method Imagen por Resonancia Magnética Magnetic Resonance Imaging is one of the most important medical imaging techniques for the investigating diseases of the human brain. A novel method for automatic segmentation Magnetic resonance brain image framework is proposed in this paper. This method consists of three-step segmentation procedures step. The method first uses level set method for the non-brain structures removal. Second, the bias correction method is based on computing estimates or tissue intensity distributions variation. Finally, we consider a statistical model method based on bayesian estimation, with prior Markov random filed models, for Magnetic resonance brain image classification. The algorithm consists of an energy function, based on the Potts model, which models the segmentation of an image. The algonthm was evaluated using simulated Magnetic resonance images and real Magnetic resonance brain images. Facultad de Informática Articulo Articulo http://creativecommons.org/licenses/by-nc/3.0/ Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) application/pdf 6-11 |
institution |
Universidad Nacional de La Plata |
institution_str |
I-19 |
repository_str |
R-120 |
collection |
SEDICI (UNLP) |
language |
Inglés |
topic |
Ciencias Informáticas Segmentation level set method Imagen por Resonancia Magnética |
spellingShingle |
Ciencias Informáticas Segmentation level set method Imagen por Resonancia Magnética Zheng, Chong-Xun Lin, Pan Yang, Yong Gu, Jian-Wen Full automatic framework for segmentation of MR brain image |
topic_facet |
Ciencias Informáticas Segmentation level set method Imagen por Resonancia Magnética |
description |
Magnetic Resonance Imaging is one of the most important medical imaging techniques for the investigating diseases of the human brain. A novel method for automatic segmentation Magnetic resonance brain image framework is proposed in this paper. This method consists of three-step segmentation procedures step. The method first uses level set method for the non-brain structures removal. Second, the bias correction method is based on computing estimates or tissue intensity distributions variation. Finally, we consider a statistical model method based on bayesian estimation, with prior Markov random filed models, for Magnetic resonance brain image classification. The algorithm consists of an energy function, based on the Potts model, which models the segmentation of an image. The algonthm was evaluated using simulated Magnetic resonance images and real Magnetic resonance brain images. |
format |
Articulo Articulo |
author |
Zheng, Chong-Xun Lin, Pan Yang, Yong Gu, Jian-Wen |
author_facet |
Zheng, Chong-Xun Lin, Pan Yang, Yong Gu, Jian-Wen |
author_sort |
Zheng, Chong-Xun |
title |
Full automatic framework for segmentation of MR brain image |
title_short |
Full automatic framework for segmentation of MR brain image |
title_full |
Full automatic framework for segmentation of MR brain image |
title_fullStr |
Full automatic framework for segmentation of MR brain image |
title_full_unstemmed |
Full automatic framework for segmentation of MR brain image |
title_sort |
full automatic framework for segmentation of mr brain image |
publishDate |
2005 |
url |
http://sedici.unlp.edu.ar/handle/10915/9502 http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Apr05-2.pdf |
work_keys_str_mv |
AT zhengchongxun fullautomaticframeworkforsegmentationofmrbrainimage AT linpan fullautomaticframeworkforsegmentationofmrbrainimage AT yangyong fullautomaticframeworkforsegmentationofmrbrainimage AT gujianwen fullautomaticframeworkforsegmentationofmrbrainimage |
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1734114867341688832 |