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Updated: Jul 18, 2026

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images
Published on: January 7, 2019
Automatic segmentation of left and right cerebral hemispheres from MRI brain volumes using the graph cuts algorithm
Lichen Liang1, Kelly Rehm, Roger P Woods
1Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN 55455, USA.
Abstract:
An automated algorithm has been developed to segment stripped (non-brain tissue excluded) T1-weighted MRI brain volumes into left and right cerebral hemispheres and cerebellum+brainstem. The algorithm, which uses the Graph Cuts technique, performs a fully automated segmentation in approximately 30 s following pre-processing. It is robust and accurate and has been tested on datasets from two scanners using different field strengths and pulse sequences. We describe the Graph Cuts algorithm and compare the results of Graph Cuts segmentations against "gold standard" manual segmentations and segmentations produced by three popular software packages used by neuroimagers: BrainVisa, CLASP, and SurfRelax.
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