Content–based image retrieval in the medical domain is an extremely hot topic in medical imaging as it promises to help better managing the large amount of medical images being produced. Applications are mainly expected in the field of medical teaching files and for research projects, where performance issues and speed are less critical than in the field of diagnostic aid. Final goal with most impact will be the use as a diagnostic aid in a real–world clinical setting. Other applications of image retrieval and image classification can be the automatic annotation of images with basic concepts or the control of DICOM header information. ImageCLEF is part of the Cross Language Evaluation Forum (CLEF). Since 2004, a medical image retrieval task has been added. Goal is to create databases of a realistic and useful size and also query topics that are based on real–world needs in the medical domain but still correspond to the limited capabilities of purely visual retrieval at the m...
Henning Müller, Paul Clough, William R. Hersh