Medical Image Databases
A Content-based Retrieval Approach
- Affiliations of the authors: Departments of Diagnostic Radiology, Medicine (Cardiology) and Electrical Engineering, Yale University, New Haven, CT
- Correspondence and reprints: C. Carl Jaffe, MD, FACC, Center for Advanced Instructional Media, Yale University, 47 College Street, Suite 224, New Haven, CT 06510. E-mail carl.jaffe{at}yale.edu
- Received 15 November 1996
- Accepted 21 January 1997
Abstract
Information contained in medical images differs considerably from that residing in alphanumeric format. The difference can be attributed to four characteristics: (1) the semantics of medical knowledge extractable from images is imprecise; (2) image information contains form and spatial data, which are not expressible in conventional language; (3) a large part of image information is geometric; (4) diagnostic inferences derived from images rest on an incomplete, continuously evolving model of normality. This paper explores the differentiating characteristics of text versus images and their impact on design of a medical image database intended to allow content-based indexing and retrieval. One strategy for implementing medical image databases is presented, which employs object-oriented iconic queries, semantics by association with prototypes, and a generic schema.
Footnotes
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This investigation was supported by a Public Health Service grant from the National Library of Medicine RO1-LM05007.
