Content-Based Similarity Assessment in Multi-segmented Medical Image Data Bases

Authors:
George Potamias
Affiliations:
-
Venue:
MLDM '01 Proceedings of the Second International Workshop on Machine Learning and Data Mining in Pattern Recognition
Year:
2001

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Abstract

Image database systems and image management in general are extremely important in achieving both technical and functional integration of the various clinical functional units. In the emerging 'film-less' clinical environment it is possible to extend the capabilities of diagnostic medical image techniques and introduce intelligent content-based image retrieval operations, towards 'evidence-based' clinical decision support. In this paper we presented an integrated methodology for content-based retrieval of multisegmented medical images. The system relies on the tight integration of clustering and pattern- (similarity) matching techniques and operations. Evaluation of the approach on a set of indicative medical images shows the reliability of our approach.