Medical Image Annotation in ImageCLEF 2008

The ImageCLEF 2008 medical image annotation task is designed to assess the quality of content-based image retrieval and image classification by means of global signatures. In total, 12,076 images were used. In contrast to previous years, the task was designed such that the hierarchy of reference IRMA code classifications is essential for good performance. 24 runs of 6 groups were submitted. Multi-class classification schemes for support vector machines outperformed the other methods. The obtained scores rage from 74.92 over 182.77 to 313.01 for best, baseline and worst results, respectively.