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31 March 2007 A preliminary study of content-based mammographic masses retrieval
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Abstract
The purpose of this study is to develop a Content-Based Image Retrieval (CBIR) system for mammographic computer-aided diagnosis. We have investigated the potential of using shape, texture, and intensity features to categorize masses that may lead to sorting similar image patterns in order to facilitate clinical viewing of mammographic masses. Experiments were conducted within a database that contains 243 masses (122 benign and 121 malignant). The retrieval performances using the individual feature was evaluated, and the best precision was determined to be 79.9% when using the curvature scale space descriptor (CSSD). By combining several selected shape features for retrieval, the precision was found to improve to 81.4%. By combining the shape, texture, and intensity features together, the precision was found to improve to 82.3%.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yimo Tao, Shih-Chung B. Lo, Matthew T. Freedman M.D., and Jianhua Xuan "A preliminary study of content-based mammographic masses retrieval", Proc. SPIE 6514, Medical Imaging 2007: Computer-Aided Diagnosis, 65141Z (31 March 2007); https://doi.org/10.1117/12.711528
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