title: Histological image retrieval based on semantic content analysis.
abstract: The demand for automatically recognizing and retrieving medical images for screening, reference, and management is growing faster than ever. In this paper, we present an intelligent content-based image retrieval system called I-Browse, which integrates both iconic and semantic content for histological image analysis. The I-Browse system combines low-level image processing technology with high-level semantic analysis of medical image content through different processing modules in the proposed system architecture. Similarity measures are proposed and their performance is evaluated. Furthermore, as a byproduct of semantic analysis, I-Browse allows textual annotations to be generated for unknown images. As an image browser, apart from retrieving images by image example, it also supports query by natural language.
authors.affiliation: Department of Computing, University of Surrey, Guildford, Surrey GU2 7XH, U.K. h.tang@surrey.ac.uk
authors.forename: H Lilian
authors.initials: HL
authors.lastname: Tang
authors.forename: Rudolf
authors.initials: R
authors.lastname: Hanka
authors.forename: Horace H S
authors.initials: HH
authors.lastname: Ip
mesh_terms: D003952:Diagnostic Imaging; D016247:Information Storage and Retrieval