Three-Dimensional Convolutional Autoencoder Extracts Features of Structural Brain Images With a “Diagnostic Label-Free” Approach: Application to Schizophrenia Datasets

Three-Dimensional Convolutional Autoencoder Extracts Features of Structural Brain Images With a “Diagnostic Label-Free” Approach: Application to Schizophrenia Datasets

There has been increasing interest in performing psychiatric brain imaging studies using deep learning. However, most studies in this field disregard three-dimensional (3D) spatial information and targeted disease discrimination, without considering the genetic and clinical heterogeneity of psychiat...

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Bibliographic Details
Main Authors: Hiroyuki Yamaguchi, Yuki Hashimoto, Genichi Sugihara, Jun Miyata, Toshiya Murai, Hidehiko Takahashi, Manabu Honda, Akitoyo Hishimoto, Yuichi Yamashita
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-07-01
Series:Frontiers in Neuroscience
Subjects:
deep learning
machine learning
neuroimaging
schizophrenia
structural MRI
convolutional autoencoder
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2021.652987/full

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https://www.frontiersin.org/articles/10.3389/fnins.2021.652987/full

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