1. Segmentation of supragranular and infragranular layers in ultra-high-resolution 7T ex vivo MRI of the human cerebral cortex.
- Author
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Zeng X, Puonti O, Sayeed A, Herisse R, Mora J, Evancic K, Varadarajan D, Balbastre Y, Costantini I, Scardigli M, Ramazzotti J, DiMeo D, Mazzamuto G, Pesce L, Brady N, Cheli F, Saverio Pavone F, Hof PR, Frost R, Augustinack J, van der Kouwe A, Eugenio Iglesias J, and Fischl B
- Subjects
- Humans, Image Processing, Computer-Assisted methods, Female, Male, Aged, Middle Aged, Adult, Magnetic Resonance Imaging methods, Cerebral Cortex diagnostic imaging
- Abstract
Accurate labeling of specific layers in the human cerebral cortex is crucial for advancing our understanding of neurodevelopmental and neurodegenerative disorders. Building on recent advancements in ultra-high-resolution ex vivo MRI, we present a novel semi-supervised segmentation model capable of identifying supragranular and infragranular layers in ex vivo MRI with unprecedented precision. On a dataset consisting of 17 whole-hemisphere ex vivo scans at 120 $\mu $m, we propose a Multi-resolution U-Nets framework that integrates global and local structural information, achieving reliable segmentation maps of the entire hemisphere, with Dice scores over 0.8 for supra- and infragranular layers. This enables surface modeling, atlas construction, anomaly detection in disease states, and cross-modality validation while also paving the way for finer layer segmentation. Our approach offers a powerful tool for comprehensive neuroanatomical investigations and holds promise for advancing our mechanistic understanding of progression of neurodegenerative diseases., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)
- Published
- 2024
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