A classification-driven similarity matching framework for retrieval of biomedical images


This paper presents a classification-driven biomedical image retrieval system to bride the semantic gap by transforming image features to their global categories at different granularity, such as image modality, body part, and orientation. To generate the feature vectors at different levels of abstraction, both the visual concept feature based on the "bag… (More)
DOI: 10.1145/1743384.1743413


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