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Medical Image Retrieval based on Multi-class SVM and Correlated Categories Vector  

Park, Ki-Hee (계명대학교 컴퓨터공학과)
Ko, Byoung-Chul (계명대학교 컴퓨터공학과)
Nam, Jae-Yeal (계명대학교 컴퓨터공학과)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.34, no.8C, 2009 , pp. 772-781 More about this Journal
Abstract
This paper proposes a novel algorithm for the efficient classification and retrieval of medical images. After color and edge features are extracted from medical images, these two feature vectors are then applied to a multi-class Support Vector Machine, to give membership vectors. Thereafter, the two membership vectors are combined into an ensemble feature vector. Also, to reduce the search time, Correlated Categories Vector is proposed for similarity matching. The experimental results show that the proposed system improves the retrieval performance when compared to other methods.
Keywords
MISS; CCV; H-CSD; EHD; Multi-class SVM;
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