Abstract
MedGIFT is a medical imaging group of the Geneva University Hospitals and the University of Geneva, Switzerland. Since 2004, the group has participated ImageCLEF each year, focusing on the medical imaging tasks. For the medical image retrieval task, two existing retrieval engines were used: the GNU Image Finding Tool (GIFT) for visual retrieval and Apache Lucene for text. Various strategies were applied to improve the retrieval performance. In total, 16 runs were submitted, 10 for the image–based topics and 6 for the case–based topics. The baseline GIFT setup used for the past three years obtained the best results among all our submissions.
For medical image annotation two approaches were tested. One approach is using GIFT for retrieval and kNN (k–Nearest Neighbors) for classification. The second approach used the Scale–Invariant Feature Transform (SIFT) with a Support Vector Machine (SVM) classifier. Three runs were submitted, two with the GIFT–kNN approach and one using the common results of the two approaches. The GIFT–kNN approach gave stable results. The SIFT–SVM approach did not achieve the expected performance, most likely due to the SVM Kernel used that was not optimized.
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Zhou, X., Eggel, I., Müller, H. (2010). The MedGIFT Group at ImageCLEF 2009. In: Peters, C., et al. Multilingual Information Access Evaluation II. Multimedia Experiments. CLEF 2009. Lecture Notes in Computer Science, vol 6242. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15751-6_25
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DOI: https://doi.org/10.1007/978-3-642-15751-6_25
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