Classifying Autism Spectrum Disorder Using the Temporal Statistics of Resting-State Functional MRI Data With 3D Convolutional Neural Networks

Classifying Autism Spectrum Disorder Using the Temporal Statistics of Resting-State Functional MRI Data With 3D Convolutional Neural Networks

Resting-state functional magnetic resonance imaging (rs-fMRI) data are 4-dimensional volumes (3-space + 1-time) that have been posited to reflect the underlying mechanisms of information exchange between brain regions, thus making it an attractive modality to develop diagnostic biomarkers of brain d...

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Bibliographic Details
Main Authors: Rajat Mani Thomas, Selene Gallo, Leonardo Cerliani, Paul Zhutovsky, Ahmed El-Gazzar, Guido van Wingen
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-05-01
Series:Frontiers in Psychiatry
Subjects:
neuroimaging
3D convolutional neural network
classification
autism
Autism Brain Imaging Data Exchange
deep learning
Online Access:https://www.frontiersin.org/article/10.3389/fpsyt.2020.00440/full

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https://www.frontiersin.org/article/10.3389/fpsyt.2020.00440/full

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