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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Detalles Bibliográficos
Autores principales: Chou, Yiyu, Chang, Catie, Remedios, Samuel W., Butman, John A., Chan, Leighton, Pham, Dzung L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8971556/
https://www.ncbi.nlm.nih.gov/pubmed/35368292
http://dx.doi.org/10.3389/fnins.2022.768634

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8971556/
https://www.ncbi.nlm.nih.gov/pubmed/35368292
http://dx.doi.org/10.3389/fnins.2022.768634

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