Bridging the Gap: Enabling CBIR in Medical Applications

Content-based image retrieval (CBIR) for medical images has received a significant research interest over the past decade as a promising approach to address the data management challenges posed by the rapidly increasing volume of medical image data in use. Articles published in the literature detail...

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Bibliographische Detailangaben
Hauptverfasser: Antani, S., Long, R.L., Thoma, G.R.
Format: Tagungsbericht
Sprache:eng
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Beschreibung
Zusammenfassung:Content-based image retrieval (CBIR) for medical images has received a significant research interest over the past decade as a promising approach to address the data management challenges posed by the rapidly increasing volume of medical image data in use. Articles published in the literature detail the benefits and present impressive results to substantiate potential impact of the technology. However, the benefits have yet to make it to mainstream clinical, biomedical research, or educational use. No major commercial software tools are available for use in medical imaging products, although several are available for commercial stock photo collections. CBIR has had some success in isolated instances in applications on limited data sets addressing specialized medical problems and at biomedical research laboratories and hospitals that are tightly coupled with software developers. This article explores some possible causes of this "gap" in the lack of translation of research into widespread biomedical use and provides some directions to alleviate the problem.
ISSN:1063-7125
DOI:10.1109/CBMS.2008.133