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A Standardized Pipeline for Examining Human Cerebellar Grey Matter Morphometry using Structural Magnetic Resonance Imaging
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1Department of Neuroscience, Central Clinical School,Monash University, 2Department of Biomedical Engineering,The Johns Hopkins University, 3Department of Psychiatry,National Institute of Mental Health & Neuro Sciences (NIMHANS), 4Faculty of Computer Science,Dalhousie University, 5Department of Electrical and Computer Engineering,The Johns Hopkins University, 6Department of Computer Science,The Johns Hopkins University, 7Brain and Mind Institute, Department for Statistical and Actuarial Sciences, Department for Computer Science,Western University, 8Monash Biomedical Imaging,Monash University
Chapters
- 00:05Introduction
- 00:41Module 1: Automatic Cerebellum Anatomical Parcellation Using U-Net Locally Constrained Optimization (ACAPULCO)
- 04:44Module 2: SUIT Cerebellum-Optimized Voxel-Based Morphometry
- 08:47Results: Examining Cerebellum Grey Matter Morphometry in Friedreich Ataxia Patients and Healthy Controls
- 11:04Conclusion
A standardized pipeline is presented for examining cerebellum grey matter morphometry. The pipeline combines high-resolution, state-of-the-art approaches for optimized and automated cerebellum parcellation and voxel-based registration of the cerebellum for volumetric quantification.
