Brain image segmentation based on multi-weighted probabilistic atlas / 南方医科大学学报
Journal of Southern Medical University
;
(12): 1143-1148, 2015.
Artigo
em Chinês
| WPRIM
| ID: wpr-333667
ABSTRACT
We propose a multi-weighted probabilistic atlas to obtain accurate, robust, and reliable segmentation. The local similarity measure is used as the weight to compute the probabilistic atlas, and the distance field is used as the weight to incorporate the locality information of the atlas; the self-similarity is used as the weight to incorporate the local information of target image to refine the probabilistic atlas. Experimental results with brain MRI images showed that the proposed algorithm outperforms the common brain image segmentation methods and achieved a median Dice coefficient of 87.1% on the left hippocampus and 87.6% on the right.
Texto completo:
DisponíveL
Índice:
WPRIM (Pacífico Ocidental)
Assunto principal:
Algoritmos
/
Encéfalo
/
Imageamento por Ressonância Magnética
/
Neuroimagem
Limite:
Humanos
Idioma:
Chinês
Revista:
Journal of Southern Medical University
Ano de publicação:
2015
Tipo de documento:
Artigo
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