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Proceedings Paper

Automatic brain tumor extraction using fuzzy information fusion
Author(s): Weibei Dou; Qingmin Liao; Su Ruan; Daniel Bloyet; Jean-Mac Constans; Yanping Chen
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Paper Abstract

This paper presents a fuzzy information fusion method to automatically extract tumor areas of human brain from multispectral magnetic resonance (MR) images. The multispectral images consist of T1 -weighted (T1), proton density (PD), and 12-weighted (T2) feature images, in which signal intensities of a tumor are different. Some tissue is more visible in one image type than the others. The fusion of information is therefore necessary. Our method, based on the fusion of information, model the fuzzy information about the tumor by membership functions. Thismodelisation is based on the a priori knowledge of radiology experts and the MR signals of the brain tissues. Three membership functions related to the three images types are proposed according to their characteristics. The brain extraction is then carried out by using the fusion of all three fuzzy information. The experimental results (based on 5 patients studied) show a mean false-negative of 2% and a mean false-positive of 1 .3%, comparing to the results obtained by a radiology using manual tracing.

Paper Details

Date Published: 31 July 2002
PDF: 6 pages
Proc. SPIE 4875, Second International Conference on Image and Graphics, (31 July 2002); doi: 10.1117/12.477203
Show Author Affiliations
Weibei Dou, Tsinghua Univ. (China)
Qingmin Liao, Tsinghua Univ. (China)
Su Ruan, GREYC-ISMRA (France)
Daniel Bloyet, GREYC-ISMRA (France)
Jean-Mac Constans, Ctr. Hospitalier Regional Univ. de Caen (France)
Yanping Chen, Nanfang Hospital (China)


Published in SPIE Proceedings Vol. 4875:
Second International Conference on Image and Graphics

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