Segmentation based on information fusion applied to brain tissue on MRI

Weibei Dou; Su Ruan; Daniel Bloyet; Jean-Mac Constans; Yanping Chen

doi:10.1117/12.526789

28 May 2004 Segmentation based on information fusion applied to brain tissue on MRI

Weibei Dou, Su Ruan, Daniel Bloyet, Jean-Mac Constans, Yanping Chen

Proceedings Volume 5298, Image Processing: Algorithms and Systems III; (2004) https://doi.org/10.1117/12.526789
Event: Electronic Imaging 2004, 2004, San Jose, California, United States

Abstract

An information fusion based fuzzy segmentation method applied to Magnetic Resonance Images (MRI) is proposed in this paper. It can automatically extract the normal and abnormal tissues of human brain from multispectral images such as T1-weighted, T2-weighted and Proton Density (PD) feature images. Fuzzy models of normal tissues corresponding to three MRI sequences images are derived from histogram according to a priori knowledge. Three different functions are chosen to calculate the fuzzy models of abnormal tissues. Then, the fuzzy features extracted by these fuzzy models are joined by a fuzzy relation operator which represents their fuzzy feature fusion. The final segmentation result is obtained by a fuzzy region growing based fuzzy decision rule. The experimental results of the proposed method are compared with the manually labeled segmentation by a neuroradiologist for abnormal tissues and with anatomic model of BrainWeb for normal tissues. The MRI images used in our experiment are imaged with a 1.5T GE for abnormal brain, with 3D MRI simulated brain database for normal brain by using an axial 3D IR T1-weighted (TI/TR/TE: 600/10/2), an axial FSE T2-weighted(TR/TE: 3500/102) and an axial FSE PD weighted (TR/TE: 3500/11). Based on 4 patients studied, the average probability of false detection of abnormal tissues is 5%. For the normal tissues, a false detection rate of 4% - 15% is obtained in images with 3% - 7% noise level. All of them show a good performance for our method.

Citation Download Citation

Weibei Dou, Su Ruan, Daniel Bloyet, Jean-Mac Constans, and Yanping Chen "Segmentation based on information fusion applied to brain tissue on MRI", Proc. SPIE 5298, Image Processing: Algorithms and Systems III, (28 May 2004); https://doi.org/10.1117/12.526789

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available