Journal of Jilin University Science Edition

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Brain Tumor Image Segmentation Based on Rapid Global FCM Algorithm

ZHOU Wengang1, FU Fen2   

  1. 1. College of Computer Science and Technology, Zhoukou Normal University, Zhoukou 466001,Henan Province, China; 2. College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
  • Received:2014-12-11 Online:2015-05-26 Published:2015-05-21
  • Contact: ZHOU Wengang E-mail:zhouwengang@zknu.edu.cn

Abstract:

In view of classical FCM clustering algorithm being too sensitive to the initial cluster centers, a rapid global FCM clustering algorithm was proposed. The algorithm uses dynamic incrementally phased selection of initial cluster centers, avoiding the problem of poor stability of clustering results due to random settings. The experiments show that the clustering result of the improved FCM clustering algorithm is better than that of classical FCM in image segmentation of brain tumors, while the clustering accuracy of multiple data sets also shows that the clustering stability of the rapid global FCM algorithm is enhanced
greatly.

Key words: brain tumor, image segmentation, fuzzy C-mean (FCM), clustering

CLC Number: 

  • TP751.1