A Comparative Study of Similarity Measures for Content-Based Medical Image Retrieval
نویسندگان
چکیده
This note summarizes methodologies employed in our submissions for the medical retrieval subtask of 2012 ImageCLEF competition. Our work aims to provide a systematic comparison of various similarity measures in the Medical CBIR application context. Our system consists of the standard bag-of-words features with SIFT. Computed features are then compared by using various plug-in similarity measures, including diffusion distance and information-theoretic metric learning. This note provides the results of our experimental validation using the 2011 ImageCLEF dataset.
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