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Proceedings Paper

Design of knowledge-based image retrieval system: implications from radiologists' cognitive processes
Author(s): Olivia R. Liu Sheng; Chih-Ping Wei; Takeshi Ozeki; Theron W. Ovitt; Jiro Ishida
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Paper Abstract

In a radiological examination reading, radiologists usually compare a newly generated examination with previous examinations of the same patient. For this reason, the retrieval of old images is a critical design requirement of totally digital radiology using Picture Archiving and Communication Systems (PACS). To achieve the required performance in a PACS with a hierarchical and possibly distributed image archival system, pre-fetching of images from slower or remote storage devices to the local buffers of workstations is proposed. Image Retrieval Expert System (IRES) is a knowledge-based image retrieval system which will predict and then pre-fetch relevant old images. Previous work on IRES design focused on the knowledge acquisition phase and the development of an efficient modeling methodology and architecture. The goal of this paper is to evaluate the effectiveness of the current IRES design and to identify appropriate directions for exploring other design features and alternatives by means of a cognitive study and an associated survey study.

Paper Details

Date Published: 1 July 1992
PDF: 12 pages
Proc. SPIE 1654, Medical Imaging VI: PACS Design and Evaluation, (1 July 1992); doi: 10.1117/12.60276
Show Author Affiliations
Olivia R. Liu Sheng, Univ. of Arizona (United States)
Chih-Ping Wei, Univ. of Arizona (United States)
Takeshi Ozeki, Toshiba Corp. (United States)
Theron W. Ovitt, Univ. of Arizona (United States)
Jiro Ishida, Tokyo Medical College (Japan)

Published in SPIE Proceedings Vol. 1654:
Medical Imaging VI: PACS Design and Evaluation
R. Gilbert Jost, Editor(s)

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