A Standardized Pipeline for Examining Human Cerebellar Grey Matter Morphometry using Structural Magnetic Resonance Imaging

3.9K Views

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11:50 min

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February 4th, 2022

DOI :

10.3791/63340-v

February 4th, 2022

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Rebecca Kerestes¹, Shuo Han², Srinivas Balachander³, Carlos Hernandez-Castillo⁴, Jerry L. Prince⁵^,⁶, Jörn Diedrichsen⁷, Ian H. Harding¹^,⁸

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

Summary

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Cerebellar Morphometry

Structural Magnetic Resonance Imaging

Anatomical Parcellation

Voxel based Morphometry

Quality Control

Automated Pipeline

Acapulco Container

NIFTI Gz Format

Statistical Outlier Detection

Image Processing

Chapters in this video

0:05

Introduction

0:41

Module 1: Automatic Cerebellum Anatomical Parcellation Using U-Net Locally Constrained Optimization (ACAPULCO)

4:44

Module 2: SUIT Cerebellum-Optimized Voxel-Based Morphometry

8:47

Results: Examining Cerebellum Grey Matter Morphometry in Friedreich Ataxia Patients and Healthy Controls

11:04

Conclusion

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