期刊名称:International Journal of Computer Network and Information Security
印刷版ISSN:2074-9090
电子版ISSN:2231-4946
出版年度:2014
卷号:6
期号:4
页码:55-62
DOI:10.5815/ijcnis.2014.04.07
出版社:MECS Publisher
摘要:Medical Magnetic Resonance Images (MRI) is characterized by a composition of small differences in signal intensities between different tissues types. Thus ambiguities and uncertainties are introduced in image formation. In this paper, review of the current approaches in the tissue segmentation of MR Brain Images has been presented. The segmentation algorithms has been divided into four categories which is able to deal with different intensity non-uniformity as adaptive spatial Fuzzy C - means, Markov Random Field, Fuzzy connectedness method and atlas based re-fuzzy connectedness. The performance of these segmentation methods have been compared in terms of validation metric as dice similarity coefficient, overlap ratio and Jaccard coefficient. The comparison of all validation metric at different levels of intensity non-uniformity shows that adaptive Fuzzy C - means clustering segmentation method give better result in segmentation of brain tissue.
关键词:Medical Image Segmentation;Adaptive Spatial Fuzzy C – means;Markov Random Field;Fuzzy Connectedness;Brain MRI