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A Novel Fuzzy Segmentation Approach for Brain MRI

  • Gang Yu
  • Changguo Wang
  • Hongmei Zhang
  • Yuxiang Yang
  • Zhengzhong Bian
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4179)

Abstract

A novel multiresolution approach is presented to segment Brain MRI images using fuzzy clustering. This approach is based on the fact that the image segmentation results should be optimized simultaneously in different scales. A new fuzzy inter-scale constraint based on antistrophic diffusion linkage model is introduced, which builds an efficient linkage relationship between the high resolution images and low resolution ones. Meanwhile, this paper develops two new fuzzy distances and then embeds them into the fuzzy clustering algorithm. The distances describe the fuzzy similarity in adjacent scales effectively. Moreover, a new multiresolution framework combining the inter- and intra-scale constraints is presented. The proposed framework is robust to noise images and low contrast ones, such as medical images. Segmentation of a number of images is illustrated. The experiments show that the proposed approach can extract the objects accurately.

Keywords

Cluster Center Segmentation Result Fuzzy Cluster High Scale Linkage Relationship 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Gang Yu
    • 1
  • Changguo Wang
    • 2
  • Hongmei Zhang
    • 1
  • Yuxiang Yang
    • 1
  • Zhengzhong Bian
    • 1
  1. 1.School of Life Science and TechnologyXi’an Jiaotong UniversityXi’anChina
  2. 2.Nantong Vocational CollegeNantongChina

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