%Aigaion2 BibTeX export from HES SO Valais Publications
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@INPROCEEDINGS{,
     author = {Markonis, Dimitrios and Schaer, Roger and M{\"{u}}ller, Henning},
   keywords = {Content-based image retrieval, Medical image retrieval, relevance feedback},
      title = {Multi-modal relevance feedback for medical image retrieval},
  booktitle = {SIGIR workshop on Medical Information Retrieval},
       year = {2014},
   location = {Gold Coast, Australia},
   abstract = {Medical image retrieval can assist physicians in finding in-
formation supporting their diagnosis. Systems that allow
searching for medical images need to provide tools for quick
and easy navigation and query refinement as the time for
information search is often short.

Relevance feedback is a powerful tool in information re-
trieval. This study evaluates relevance feedback techniques
with regard to the content they use. A novel relevance feed-
back technique that uses both text and visual information
of the results is proposed.

Results show the potential of relevance feedback tech-
niques in medical image retrieval and the superiority of the
proposed algorithm over commonly used approaches.

Future steps include integrating semantics into relevance
feedback techniques to benefit of the structure knowledge
of ontologies and experimenting on the fusion of text and
visual information.},
A SIGIR 2014 workshop - Gold Coast, Australia - July, 11th 2014
}