Partial volume effect modeling for segmentation and tissue classification of brain magnetic resonance images: A review

Jussi Tohka
2014 World Journal of Radiology  
Running title Partial volume segmentation in brain MRI Abstract 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 an
more » ... 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. Each voxel in a brain 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 MR image 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.
doi:10.4329/wjr.v6.i11.855 pmid:25431640 pmcid:PMC4241492 fatcat:kw6hfhyamjhrta6pczwi2pyive