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Whole-brain Segmentation and Change-point Analysis of Anatomical Brain MRI—Application in Premanifest Huntington's Disease
 

Whole-brain Segmentation and Change-point Analysis of Anatomical Brain MRI—Application in Premanifest Huntington's Disease

Article DOI: 10.3791/57256-v • 09:06 min • June 9th, 2018
June 9th, 2018 •
1, 1, 2,3,4, 5, 1,6, 2,3,7
1The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 2Center for Imaging Science, Johns Hopkins University, 3Institute for Computational Medicine, Johns Hopkins University, 4Department of Applied Mathematics and Statistics, Johns Hopkins University, 5Division of Neurobiology, Departments of Psychiatry, Neurology, Neuroscience and Pharmacology, and Program in Cellular and Molecular Medicine, Johns Hopkins University School of Medicine, 6F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, 7Department of Biomedical Engineering, Johns Hopkins University

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This paper describes a statistical model for volumetric MRI data analysis, which identifies the "change-point" when brain atrophy begins in premanifest Huntington's disease. Whole-brain mapping of the change-points is achieved based on brain volumes obtained using an atlas-based segmentation pipeline of T1-weighted images.

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Keywords: Brain MRI Whole-brain Segmentation Change-point Analysis Huntington's Disease Neurodegenerative Disease Volumetric Analysis MRICloud MultiAtlas-based Segmentation Quantitative Analysis Brain Atrophy
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