Automated Classification of Resting-State fMRI ICA Components Using a Deep Siamese Network

Automated Classification of Resting-State fMRI ICA Components Using a Deep Siamese Network

Manual classification of functional resting state networks (RSNs) derived from Independent Component Analysis (ICA) decomposition can be labor intensive and requires expertise, particularly in large multi-subject analyses. Hence, a fully automatic algorithm that can reliably classify these RSNs is d...

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Bibliographic Details
Main Authors: Yiyu Chou, Catie Chang, Samuel W. Remedios, John A. Butman, Leighton Chan, Dzung L. Pham
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-03-01
Series:Frontiers in Neuroscience
Subjects:
resting-state functional MRI
independent component analysis
deep learning
siamese network
classification
magnetic resonance imaging (MRI)
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2022.768634/full

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https://www.frontiersin.org/articles/10.3389/fnins.2022.768634/full

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