Interactive algorithms for the segmentation and quantitation of 3-D MRI brain scans
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Updated: Nov 2, 2026

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images
Published on: January 7, 2019
P A Freeborough1, N C Fox, R I Kitney
1Dementia Research Group, National Hospital for Neurology and Neurosurgery, London, UK.
Abstract:
Interactive algorithms are an attractive approach to the accurate segmentation of 3D brain scans as they potentially improve the reliability of fully automated segmentation while avoiding the labour intensiveness and inaccuracies of manual segmentation. We present a 3D image analysis package (MIDAS) with a novel architecture enabling highly interactive segmentation algorithms to be implemented as add on modules. Interactive methods based on intensity thresholding, region growing and the constrained application of morphological operators are also presented. The methods involve the application of constraints and freedoms on the algorithms coupled with real time visualisation of the effect. This methodology has been applied to the segmentation, visualisation and measurement of the whole brain and a small irregular neuroanatomical structure, the hippocampus. We demonstrate reproducible and anatomically accurate segmentations of these structures. The efficacy of one method in measuring volume loss (atrophy) of the hippocampus in Alzheimer's disease is shown and is compared to conventional methods.

