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1 From the Service of Medical Informatics, University and University Hospitals of Geneva, 24 Rue Michelidu-Crest, 1211 Geneva 14, Switzerland. Presented as an infoRAD exhibit at the 2003 RSNA Scientific Assembly. Received April 12, 2004; revision requested July 1; final revision received January 13, 2005; accepted January 20. All authors have no financial relationships to disclose. Address correspondence to H.M. (e-mail: henning.mueller{at}sim.hcuge.ch).
The field of medicine is often cited as an area for which content-based visual retrieval holds considerable promise. To date, very few visual image retrieval systems have been used in clinical practice; the first applications of image retrieval systems in medicine are currently being developed to complement conventional text-based searches. An image retrieval system was developed and integrated into a radiology teaching file system, and the performance of the retrieval system was evaluated, with use of query topics that represent the teaching database well, against a standard of reference generated by a radiologist. The results of this evaluation indicate that content-based image retrieval has the potential to become an important technology for the field of radiology, not only in research, but in teaching and diagnostics as well. However, acceptance of this technology in the clinical domain will require identification and implementation of clinical applications that use content-based access mechanisms, necessitating close cooperation between medical practitioners and medical computer scientists. Nevertheless, content-based image retrieval has the potential to become an important technology for radiology practice.
© RSNA, 2005
Abbreviations: ASSERT = Automatic Search and Selection Engine with Retrieval Tools, GIFT = GNU Image Finding Tool, IRMA = Image Retrieval in Medical Applications, MIRC = Medical Imaging Resource Center, PACS = picture archiving and communication system
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