A Mutual Multi-Scale Triplet Graph Convolutional Network for Classification of Brain Disorders Using Functional or Structural Connectivity

Brain connectivity alterations associated with mental disorders have been widely reported in both functional MRI (fMRI) and diffusion MRI (dMRI). However, extracting useful information from the vast amount of information afforded by brain networks remains a great challenge. Capturing network topolog...

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Veröffentlicht in:	IEEE transactions on medical imaging Jg. 40; H. 4; S. 1279 - 1289
Hauptverfasser:	Yao, Dongren, Sui, Jing, Wang, Mingliang, Yang, Erkun, Jiaerken, Yeerfan, Luo, Na, Yap, Pew-Thian, Liu, Mingxia, Shen, Dinggang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.04.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Artificial neural networks Brain Brain - diagnostic imaging Brain connectivity Brain Diseases Brain mapping Brain modeling Classification Convolution Diseases Functional magnetic resonance imaging Fuses graph convolutional network Humans Learning Magnetic Resonance Imaging Mental disorders Network topologies Neural networks Neuroimaging Representations Structure-function relationships Topology triplet White matter
ISSN:	0278-0062, 1558-254X, 1558-254X
Online-Zugang:	Volltext
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