An extensible hierarchical graph convolutional network for early Alzheimer’s disease identification

•An extensible and adjustable EH-GCN learning framework is proposed.•Multi-modal image features and non-image information are analyzed comprehensively.•Gray matter atrophy and brain connectivity abnormalities are analyzed simultaneously.•The proposed population-based GCN improves the identification...

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Vydané v:	Computer methods and programs in biomedicine Ročník 238; s. 107597
Hlavní autori:	Tian, Xu, Liu, Yan, Wang, Ling, Zeng, Xiangzhu, Huang, Yulang, Wang, Zeng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Ireland Elsevier B.V 01.08.2023
Predmet:	Alzheimer Disease Alzheimer’S disease Brain - pathology Cerebral Cortex - pathology Computer-aided disease diagnosis Deep learning Graph convolutional networks Gray Matter - diagnostic imaging Humans Magnetic resonance imaging (MRI) Magnetic Resonance Imaging - methods Deep learning Magnetic resonance imaging (MRI) Computer-aided disease diagnosis Alzheimer’S disease Graph convolutional networks
ISSN:	0169-2607, 1872-7565, 1872-7565
On-line prístup:	Získať plný text
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