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Updated: Jul 10, 2026

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images
Published on: January 7, 2019
Evaluation of two segmentation methods on MRI brain tissue structures
1Dept. of Electr. & Comput. Eng. & Comput. Sci., Cincinnati Univ., OH 45221, USA. caixg@ececs.uc.edu
Abstract:
In this paper, we evaluate two segmentation methods on 15 brain tissue structures. One is narrow band level set method and the other is pattern classification method based on maximum a posteriori (MAP) probability framework. Two sets of experiments are conducted on 18 verified MRI brain data sets. Dice Similarity Index (DSI) is used to evaluate the closeness between our segmentation results and the gold standards, which were provided by experienced radiologists. The results for comparison of two methods are given and their potential applicability is discussed. Tissue structures such as left and right lateral ventricle have achieved over 70% DSI, while other structures such as third ventricle, caudate nucleus, globus pallidus, putamen and thalamus have achieved above 60% DSI.

