title: [Automatic segmentation of three dimension medical image series].
abstract: We propose an improved version of regional competition algorithm in this paper, and apply it to the automatic segmentation of medical image series, particularly in the segmentation and recognition of brain tumor. The traditional regional competition is enhanced by combining the attractive aspects of fuzzy segmentation, and thus it provides an efficient approach to segment the fuzzy and heterogeneous medical images. In order to perform regional competition on medical image series, we utilize the segmentation result of a slice to initiate the next segmented slice, while the first slice is initialized using regional growing algorithm. Moreover, we develop an algorithm to recognize the tumors automatically, taking into account its characters. Experimental results show that our algorithm performs well on the segmentation of magnetic resonance imaging (MRI) image series with high speed and precision.
authors.affiliation: Image Processing & Pattern Recognition Institute, Shanghai Jiaotong University, Shanghai 200240, China.
authors.forename: Siyi
authors.initials: S
authors.lastname: Ding
authors.forename: Jie
authors.initials: J
authors.lastname: Yang
authors.forename: Lixiu
authors.initials: L
authors.lastname: Yao
authors.forename: Qing
authors.initials: Q
authors.lastname: Xu
mesh_terms: D000465:Algorithms; D001932:Brain Neoplasms / Q000175:diagnosis; D017143:Fuzzy Logic; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging; D010363:Pattern Recognition, Automated