Membership-based multiprotocol MR brain image segmentation

Ying Zhuge; Jiamin Liu; Jayaram K. Udupa

doi:10.1117/12.481410

15 May 2003 Membership-based multiprotocol MR brain image segmentation

Ying Zhuge, Jiamin Liu, Jayaram K. Udupa

Proceedings Volume 5032, Medical Imaging 2003: Image Processing; (2003) https://doi.org/10.1117/12.481410
Event: Medical Imaging 2003, 2003, San Diego, California, United States

Abstract

A simple,non-iterative,membership-based method for multiprotocol brain magnetic resonance image segmentation has been developed. The intensity in homogeneity correction and MR intensity standardization techniques are used first to make the MR image intensities have a tissue-specific meaning. The mean intensity vector and covariance matrix of each brain tissue are then estimated and fixed. Vectorial scale-based fuzzy connectedness and certain morphological operations are utilized to geernate the brain intracranial mask. The fuzzy membership value of each voxel for each brain tissue is then estimated within the intracranial mask via a multivariate Gaussian model. Finally, a maximum likelihood criterion with spatial constraints taken into account is utilized in classifying all voxels in the intracranial mask into gray matter, white matter, and cerebrospinal fluid. This method has been tested on 10 clinical MR data sets. These tests and a comparison with the method of C-means and fuzzy C-means clustering indicated the effectiveness of the method.

Citation Download Citation

Ying Zhuge, Jiamin Liu, and Jayaram K. Udupa "Membership-based multiprotocol MR brain image segmentation", Proc. SPIE 5032, Medical Imaging 2003: Image Processing, (15 May 2003); https://doi.org/10.1117/12.481410

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