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Proceedings Paper

Content based image retrieval applied to contrast enhancing brain tumors
Author(s): Hussain Z. Tameem; Shishir Dube; Usha Sinha
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Paper Abstract

This work focuses on image retrieval utilizing principal component analysis (PCA) and linear discriminant analysis (LDA) techniques for brain tumors from Magnetic Resonance (MR) studies. The research has been broken into three stages. Stage 1 consists of developing the PCA and LDA algorithms to be used for content based image retrieval (CBIR) systems. Stage 2 consists of evaluation of PCA and LDA algorithms on synthetic tumor images with added noise and shading artifacts. Stage 3 consists of tailoring the algorithm specifically for automated detection and CBIR system of MR contrast enhancing tumors matching a given query image. The algorithm has been developed and tested successfully for synthetic tumor images and actual contrast enhanced tumors. We hope to integrate the PCA and LDA algorithms to perform an indexing of the tumor shapes derived from actual MR images. Two relevant indices: size and location will also be used to index the data.

Paper Details

Date Published: 13 March 2008
PDF: 6 pages
Proc. SPIE 6919, Medical Imaging 2008: PACS and Imaging Informatics, 691910 (13 March 2008); doi: 10.1117/12.771030
Show Author Affiliations
Hussain Z. Tameem, Univ. of California, Los Angeles (United States)
Shishir Dube, Univ. of California, Los Angeles (United States)
Usha Sinha, Univ. of California, Los Angeles (United States)
San Diego State Univ. (United States)

Published in SPIE Proceedings Vol. 6919:
Medical Imaging 2008: PACS and Imaging Informatics
Katherine P. Andriole; Khan M. Siddiqui, Editor(s)

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