Abstract
The aim of this paper is to explore different medical image modality and retrieval strategies. First, we analyze how current state-of-the art image representations (bags of visual words and Fisher Vectors) perform when we use them for medical modality classification. Then we integrated these representations in a content based image retrieval system and tested on a medical image retrieval task. Finally, in both cases, we explored how the performance can be improved if we combine visual with textual information. To show the performance of different systems we compared our approaches to the systems participated at the Medical Task of the latest ImageClef Challenge [16].
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