Hierarchical fuzzy segmentation of brain MR images

In brain magnetic resonance (MR) images, image segmentation and 3D visualization are very useful tools for the diagnosis of abnormalities. Segmentation of white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) is the basic process for 3D visualization of brain MR images. Of the many algorithms, the fuzzy c-means (FCM) technique has been widely used for segmentation of brain MR images. However, the FCM technique does not yield sufficient results under radio frequency (RF) nonuniformity. We propose a hierarchical FCM (HFCM), which provides good segmentation results under RF nonuniformity and does not require any parameter setting. We also generate Talairach templates of the brain that are deformed to 3D brain MR images. Using the deformed templates, only the cerebrum region is extracted from the 3D brain MR images. Then, the proposed HFCM partitions the cerebrum region into WM, GM, and CSF. (C) 2003 Wiley Periodicals, Inc.
Publisher
JOHN WILEY SONS INC
Issue Date
2003
Language
ENG
Keywords

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Citation

INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, v.13, no.2, pp.115 - 125

ISSN
0899-9457
URI
http://hdl.handle.net/10203/3144
Appears in Collection
EE-Journal Papers(저널논문)
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