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Updated: Jul 17, 2026
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Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images
Published on: January 7, 2019
Automated recursive segmentation of large neocortical images using standard deviation as termination criteria
A Konkachbaev1, M Casanova, J Graham
1Computer Engineering and Computer Science, University Of Louisville Louisville, KY 40292.
Abstract:
In this paper we present an improved segmentation algorithm that recursively explores various thresholding levels until it reaches a termination criteria. This segmentation algorithm is based on earlier work adapting Otsu's thresholding approach to myelinated bundles of axons in cortical tissue. Experimentation using over 120 images has confirmed that this termination criteria provides visibly acceptable segmentation in an automated fashion.
