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We present a novel method for automated diagnosis of liver lesions in multi-phase CT images. Our approach is a variant of the Bag-of-Visual-Words (BoVW) method. It improves the BoVW model by selecting the most relevant words to be used for the input representation using a mutual information based criterion. Additionally, we generate relevance maps to visualize and localize the decision of the automatic classification algorithm. We validated our algorithm on 85 multi-phase CT images of 4doi:10.1109/isbi.2015.7163898 dblp:conf/isbi/DiamantGKAG15 fatcat:2nv4pt7d6bdapimbc4l3v4u6fa