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SubmittedOpen Access (License Unspecified), Open
Conference proceeding
Using Relevant Regions in Image Search and Query Refinement for Medical CBIR
MEDICAL IMAGING 2011: ADVANCED PACS-BASED IMAGING INFORMATICS AND THERAPEUTIC APPLICATIONS, v 7967(1), pp 796707-796708
01 Jan 2011
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.
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2 citations in Scopus
Details
- Title
- Using Relevant Regions in Image Search and Query Refinement for Medical CBIR
- Creators
- Edward Kim - Lehigh UniversitySameer Antani - United States National Library of MedicineXiaolei Huang - Lehigh UniversityL. Rodney Long - United States National Library of MedicineDina Demner-Fushman - College Station Medical Center
- Contributors
- W W Boonn (Editor)B J Liu (Editor)
- Publication Details
- MEDICAL IMAGING 2011: ADVANCED PACS-BASED IMAGING INFORMATICS AND THERAPEUTIC APPLICATIONS, v 7967(1), pp 796707-796708
- Series
- Proceedings of SPIE
- Publisher
- Spie-Int Soc Optical Engineering
- Number of pages
- 8
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Computer Science
- Web of Science ID
- WOS:000296329700005
- Scopus ID
- 2-s2.0-79957953024
- Other Identifier
- 991021884692004721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Optics
- Radiology, Nuclear Medicine & Medical Imaging