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.
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Jiang, S., Chen, W., Feng, Q., Yang, S. (2008). Weighted Fuzzy Feature Matching for Region-Based Medical Image Retrieval: Application to Cerebral Hemorrhage Computerized Tomography. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2008. Lecture Notes in Computer Science, vol 5112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69812-8_27
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DOI: https://doi.org/10.1007/978-3-540-69812-8_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69811-1
Online ISBN: 978-3-540-69812-8
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