Journal
WORLD JOURNAL OF RADIOLOGY
Volume 6, Issue 11, Pages 855-864Publisher
BAISHIDENG PUBLISHING GROUP INC
DOI: 10.4329/wjr.v6.i11.855
Keywords
Magnetic resonance imaging; Segmentation; Tissue classification; White matter; Gray matter; Image processing; Brain imaging; Image analysis
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Quantitative analysis of magnetic resonance (MR) brain images are facilitated by the development of automated segmentation algorithms. A single image voxel may contain of several types of tissues due to the finite spatial resolution of the imaging device. This phenomenon, termed partial volume effect (PVE), complicates the segmentation process, and, due to the complexity of human brain anatomy, the PVE is an important factor for accurate brain structure quantification. Partial volume estimation refers to a generalized segmentation task where the amount of each tissue type within each voxel is solved. This review aims to provide a systematic, tutorial-like overview and categorization of methods for partial volume estimation in brain MRI. The review concentrates on the statistically based approaches for partial volume estimation and also explains differences to other, similar image segmentation approaches. (c) 2014 Baishideng Publishing Group Inc. All rights reserved.
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