DeepAtrophy: Teaching a neural network to detect progressive changes in longitudinal MRI of the hippocampal region in Alzheimer's disease

Measures of change in hippocampal volume derived from longitudinal MRI are a well-studied biomarker of disease progression in Alzheimer's disease (AD) and are used in clinical trials to track therapeutic efficacy of disease-modifying treatments. However, longitudinal MRI change measures based o...

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Veröffentlicht in:	NeuroImage (Orlando, Fla.) Jg. 243; S. 118514
Hauptverfasser:	Dong, Mengjin, Xie, Long, Das, Sandhitsu R., Wang, Jiancong, Wisse, Laura E.M., deFlores, Robin, Wolk, David A., Yushkevich, Paul A.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Elsevier Inc 01.11.2021 Elsevier Limited Elsevier
Schlagworte:	Aged Aged, 80 and over Aging Algorithms Alzheimer Disease - pathology Alzheimer's disease Atrophy Biomarkers Clinical Medicine Clinical trials Cognitive Dysfunction - pathology Deep learning Disease Progression Female Hippocampus Hippocampus - pathology Hippocampus area Humans Interscan interval Klinisk medicin Longitudinal analysis Longitudinal Studies Magnetic resonance imaging Magnetic Resonance Imaging - methods Male Medical and Health Sciences Medicin och hälsovetenskap Morphometry Neural networks Neural Networks, Computer Neurodegenerative diseases Neuroimaging Neuroimaging - methods Neurologi Neurology Radiologi och bildbehandling Radiology and Medical Imaging Registration Substantia grisea T1-weighted MRI Teaching Longitudinal analysis Hippocampus area T1-weighted MRI Interscan interval Alzheimer's disease Disease progression
ISSN:	1053-8119, 1095-9572, 1095-9572
Online-Zugang:	Volltext
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