Published online Nov 28, 2014. doi: 10.4329/wjr.v6.i11.855
Revised: September 3, 2014
Accepted: September 23, 2014
Published online: November 28, 2014
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.
Core tip: Each voxel in a brain magnetic resonance imaging (MRI) may contain multiple types of tissue. Partial volume estimation refers to a generalized image segmentation task where the amount of each tissue type within each image voxel of brain MRI is solved. This is important for volume quantification and cortical thickness analysis due to the geometrical complexity of human brain structure. This review aims to provide a systematic, tutorial-like overview of methods for partial volume estimation in brain MRI.