Abstract
This paper describes our participation to the Medical Image Retrieval task of Image CLEF 2008. Our aim was to evaluate different combination approaches for context-based and content-base image retrieval. Our test set is composed of 30 queries, which has been classified by organizers into three categories: visual, textual (semantic) and mixed.
Our most interesting conclusion is that combining results provided by both methods using a classical combination function on all query types, obtains higher retrieval accuracy than combining according to query type. Moreover, it is more successful than using only textual retrieval or using only visual retrieval.
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Torjmen, M., Pinel-Sauvagnat, K., Boughanem, M. (2009). Methods for Combining Content-Based and Textual-Based Approaches in Medical Image Retrieval. In: Peters, C., et al. Evaluating Systems for Multilingual and Multimodal Information Access. CLEF 2008. Lecture Notes in Computer Science, vol 5706. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04447-2_87
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DOI: https://doi.org/10.1007/978-3-642-04447-2_87
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04446-5
Online ISBN: 978-3-642-04447-2
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