A comparison of Freesurfer and multi-atlas MUSE for brain anatomy segmentation: Findings about size and age bias, and inter-scanner stability in multi-site aging studies

Automatic segmentation of brain anatomy has been a key processing step in quantitative neuroimaging analyses. An extensive body of literature has relied on Freesurfer segmentations. Yet, in recent years, the multi-atlas segmentation framework has consistently obtained results with superior accuracy...

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Bibliographic Details
Published in:	NeuroImage (Orlando, Fla.) Vol. 223; p. 117248
Main Authors:	Srinivasan, Dhivya, Erus, Guray, Doshi, Jimit, Wolk, David A., Shou, Haochang, Habes, Mohamad, Davatzikos, Christos
Format:	Journal Article
Language:	English
Published:	United States Elsevier Inc 01.12.2020 Elsevier Limited Elsevier
Subjects:	Adult Aged Aging Algorithms Alzheimer's disease Anatomy Automation Bias Brain Brain - anatomy & histology Brain - diagnostic imaging Datasets Female Freesurfer Hippocampus Hippocampus - anatomy & histology Hippocampus - diagnostic imaging Humans Image Processing, Computer-Assisted - methods Magnetic Resonance Imaging Male Medical imaging MRI MUSE Neuroimaging Organ Size Protocol Quality control Registration Reproducibility of Results ROI Segmentation Software Software packages Young Adult Brain Freesurfer Segmentation MRI ROI MUSE
ISSN:	1053-8119, 1095-9572, 1095-9572
Online Access:	Get full text
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