International Journal of Computer Vision
Hierarchical classification using a frequency-based weighting and simple visual features
Pattern Recognition Letters
Overview of the ImageCLEFmed 2007 Medical Retrieval and Medical Annotation Tasks
Advances in Multilingual and Multimodal Information Retrieval
University and Hospitals of Geneva Participating at ImageCLEF 2007
Advances in Multilingual and Multimodal Information Retrieval
Overview of the ImageCLEFmed 2008 medical image retrieval task
CLEF'08 Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access
Medical image annotation in ImageCLEF 2008
CLEF'08 Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access
The MedGIFT group at ImageCLEF 2009
CLEF'09 Proceedings of the 10th international conference on Cross-language evaluation forum: multimedia experiments
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This article describes the participation of the MedGIFT research group at the 2008 ImageCLEFmed image retrieval benchmark. We concentrated on the two tasks concerning medical imaging. The visual information analysis is mainly based on the GNU Image Finding Tool (GIFT). Other information such as textual information and aspect ratio were integrated to improve our results. The main techniques are similar to past years, with tuning a few parameters to improve results. For the visual tasks it becomes clear that the baseline GIFT runs do not have the same performance as some more sophisticated and more modern techniques. GIFT can be seen as a baseline for the visual retrieval as it has been used for the past five years in ImageCLEF. Due to time constraints not all optimizations could be performed and no relevance feedback was used, one of the strong points of GIFT. Still, a clear difference in performance can be observed depending on the various optimizations applied, and the difference with the best groups is smaller than in past years.