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Proceedings Paper

A web collaboration system for content-based image retrieval of medical images
Author(s): Dave Tahmoush; Hanan Samet
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Paper Abstract

Building effective content-based image retrieval (CBIR) systems involves the combination of image creation, storage, security, transmission, analysis, evaluation feature extraction, and feature combination in order to store and retrieve medical images effectively. This requires the involvement of a large community of experts across several fields. We have created a CBIR system called Archimedes which integrates the community together without requiring disclosure of sensitive details. Archimedes' system design enables researchers to upload their feature sets and quickly compare the effectiveness of their methods against other stored feature sets. Additionally, research into the techniques used by radiologists is possible in Archimedes through double-blind radiologist comparisons based on their annotations and feature markups. This research archive contains the essential technologies of secure transmission and storage, textual and feature searches, spatial searches, annotation searching, filtering of result sets, feature creation, and bulk loading of features, while creating a repository and testbed for the community.

Paper Details

Date Published: 21 March 2007
PDF: 11 pages
Proc. SPIE 6516, Medical Imaging 2007: PACS and Imaging Informatics, 65160E (21 March 2007); doi: 10.1117/12.702592
Show Author Affiliations
Dave Tahmoush, Univ. of Maryland/College Park (United States)
Hanan Samet, Univ. of Maryland/College Park (United States)


Published in SPIE Proceedings Vol. 6516:
Medical Imaging 2007: PACS and Imaging Informatics
Steven C. Horii; Katherine P. Andriole, Editor(s)

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