Weighted Fuzzy Feature Matching for Region-Based Medical Image Retrieval: Application to Cerebral Hemorrhage Computerized Tomography

  • Authors:
  • Shaofeng Jiang;Wufan Chen;Qianjin Feng;Suhua Yang

  • Affiliations:
  • Key Lab for Medical Image Processing of Southern Medical University, Guang zhou, China and Nanchang Hangkong University, Nanchang, China;Key Lab for Medical Image Processing of Southern Medical University, Guang zhou, China;Key Lab for Medical Image Processing of Southern Medical University, Guang zhou, China;Nanchang Hangkong University, Nanchang, China

  • Venue:
  • ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
  • Year:
  • 2008

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Abstract

In this paper, we focus on retrieval for cerebral hemorrhage Computerized Tomography images based on Weighted Fuzzy Feature Matching (WFFM). We first apply an improved Expectation Maximization (EM) algorithm to segment the images into regions, and then extract the texture features of each region with Gabor filters. To improve the robustness of retrieval system against segmentation-related uncertainties, WFFM maps the intensity features of each region into fuzzy features with the exponential membership functions. Based on fuzzy features, regions between images are matched and the texture features serve as weighting factors when calculating the similarities between the images. Experiments show that the retrieval method performs better than some similar methods in the application to retrieve cerebral hemorrhage CT images.