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Proceedings Paper

Attribute visualization and relevance feedback in the content-based image retrieval of medical images
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Paper Abstract

A novel CBIR system is described that incorporates both high level (semantic) and low level visual content. It is suitable for medical image information systems, to assist clinical diagnosis or for clinician training purposes. The system is XML-compliant and utilises MPEG-7 content descriptions and encoded metadata. The image retrieval process is driven by relevance feedback, enabling the indirect transferal of expert knowledge. A novel attribute visualisation facility enables the user to understand how the search criteria are modified and the effectiveness of the guidance provided. The relevance feedback visualisation can be used also to re-sort retrieved results according to the user's requirements and permit the interactive investigation of pertinent features. The effectiveness of the system is demonstrated by two examples from the field of dermatology. Evaluations show that combining the attribute visualisation with conventional retrieval techniques both increases user confidence levels and provides additional system functionality.

Paper Details

Date Published: 18 December 2003
PDF: 11 pages
Proc. SPIE 5307, Storage and Retrieval Methods and Applications for Multimedia 2004, (18 December 2003); doi: 10.1117/12.525779
Show Author Affiliations
Chee Un Ng, Univ. of Warwick (United Kingdom)
Graham R. Martin, Univ. of Warwick (United Kingdom)


Published in SPIE Proceedings Vol. 5307:
Storage and Retrieval Methods and Applications for Multimedia 2004
Minerva M. Yeung; Rainer W. Lienhart; Chung-Sheng Li, Editor(s)

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