title: Medical image databases: a content-based retrieval approach.
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.
authors.affiliation: Department of Diagnostic Radiology, Yale University, New Haven, CT 06510, USA.
authors.forename: H D
authors.initials: HD
authors.lastname: Tagare
authors.forename: C C
authors.initials: CC
authors.lastname: Jaffe
authors.forename: J
authors.initials: J
authors.lastname: Duncan
mesh_terms: D000043:Abstracting and Indexing; D003196:Computer Graphics; D016208:Databases, Factual; D003952:Diagnostic Imaging; D006801:Humans; D007091:Image Processing, Computer-Assisted; D016247:Information Storage and Retrieval; D012660:Semantics