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...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	NeuroImage (Orlando, Fla.) Ročník 223; s. 117248
Hlavní autori:	Srinivasan, Dhivya, Erus, Guray, Doshi, Jimit, Wolk, David A., Shou, Haochang, Habes, Mohamad, Davatzikos, Christos
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Elsevier Inc 01.12.2020 Elsevier Limited Elsevier
Predmet:	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
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!