Deep Feature Extraction for Resting-State Functional MRI by Self-Supervised Learning and Application to Schizophrenia Diagnosis

Deep Feature Extraction for Resting-State Functional MRI by Self-Supervised Learning and Application to Schizophrenia Diagnosis

In this study, we propose a deep-learning technique for functional MRI analysis. We introduced a novel self-supervised learning scheme that is particularly useful for functional MRI wherein the subject identity is used as the teacher signal of a neural network. The neural network is trained solely b...

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Bibliographic Details
Main Authors: Yuki Hashimoto, Yousuke Ogata, Manabu Honda, Yuichi Yamashita
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-08-01
Series:Frontiers in Neuroscience
Subjects:
deep-learning
functional MRI
neural network
feature extraction
psychiatric diagnosis
self-supervised learning
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2021.696853/full

Internet

https://www.frontiersin.org/articles/10.3389/fnins.2021.696853/full

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