Brain image segmentation based on multi-weighted probabilistic atlas
ZHANG Lei
ZHANG Minghui
LU Zhentai
FENG Qianjin
CHEN Wufan
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.
Keywords：image segmentationprobabilistic atlassimilarity measuredistance fieldself-similarityhippocampus
Publication Date：2015-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 1143-1148 )