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Proceedings Paper

Using relevant regions in image search and query refinement for medical CBIR
Author(s): Edward Kim; Sameer Antani; Xiaolei Huang; L. Rodney Long; Dina Demner-Fushman
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Paper Abstract

In clinical decision processes, relevant scientific publications and their associated medical images can provide valuable and insightful information. However, effectively searching through both text and image data is a difficult and arduous task. More specifically in the area of image search, finding similar images (or regions within images) poses another significant hurdle for effective knowledge dissemination. Thus, we propose a method using local regions within images to perform and refine medical image retrieval. In our first example, we define and extract large, characteristic regions within an image, and then show how to use these regions to match a query image to similar content. In our second example, we enable the formulation of a mixed query based upon text, image, and region information, to better represent the end user's search intentions. Given our new framework for region-based queries, we present an improved set of similar search results.

Paper Details

Date Published: 25 March 2011
PDF: 8 pages
Proc. SPIE 7967, Medical Imaging 2011: Advanced PACS-based Imaging Informatics and Therapeutic Applications, 796707 (25 March 2011); doi: 10.1117/12.878192
Show Author Affiliations
Edward Kim, Lehigh Univ. (United States)
Sameer Antani, National Library of Medicine (United States)
Xiaolei Huang, Lehigh Univ. (United States)
L. Rodney Long, National Library of Medicine (United States)
Dina Demner-Fushman, National Library of Medicine (United States)


Published in SPIE Proceedings Vol. 7967:
Medical Imaging 2011: Advanced PACS-based Imaging Informatics and Therapeutic Applications
William W. Boonn; Brent J. Liu, Editor(s)

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