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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Detalles Bibliográficos
Autores principales: Zheng, Chong-Xun, Lin, Pan, Yang, Yong, Gu, Jian-Wen
Formato: Articulo
Lenguaje:Inglés
Publicado: 2005
Materias:
Ciencias Informáticas
Segmentation
level set method
Imagen por Resonancia Magnética
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:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-9502
record_format dspace
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
bdutipo_str Repositorios
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