FCSE at ImageCLEF 2012: Evaluating Techniques for Medical Image Retrieval
Date Issued
2012
Author(s)
Loshkovska, Suzana
Abstract
. This paper presents the details of the participation of FCSE (Faculty
of Computer Science and Engineering) research team in ImageCLEF 2012
medical retrieval task. We investigated by evaluating different weighting
models for text retrieval. In the case of the visual retrieval, we focused on
extracting low-level features and examining their performance. For, the
multimodal retrieval we used late fusion to combine the best text and visual
results. We found that the choice of weighting model for text retrieval
dramatically influences the outcome of the multimodal retrieval. We tested the
multimodal retrieval on data from ImageCLEF 2011 medical task and based on
that we submitted new experiments for ImageCLEF 2012. The results show that
fusing different modalities in the retrieval can improve the overall retrieval
performance.
of Computer Science and Engineering) research team in ImageCLEF 2012
medical retrieval task. We investigated by evaluating different weighting
models for text retrieval. In the case of the visual retrieval, we focused on
extracting low-level features and examining their performance. For, the
multimodal retrieval we used late fusion to combine the best text and visual
results. We found that the choice of weighting model for text retrieval
dramatically influences the outcome of the multimodal retrieval. We tested the
multimodal retrieval on data from ImageCLEF 2011 medical task and based on
that we submitted new experiments for ImageCLEF 2012. The results show that
fusing different modalities in the retrieval can improve the overall retrieval
performance.
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