IEEE Systems, Man and Cybernetics Magazine - July 2023 - 9
An ASD
Classification
Based on a Pseudo
4D ResNet
Utilizing Spatial and Temporal Convolution
by Shuaiqi Liu , Siqi Wang , Hong Zhang,
Shui-Hua Wang , Jie Zhao, and Jingwen Yan
T
he psychiatric condition known as autism
spectrum disorder (ASD) affects children and
adults alike. As a medical imaging technology,
functional magnetic resonance imaging
(fMRI) is widely used to study the brains of
persons with ASD. This study introduces a novel technique:
a pseudo 4D ResNet (P4D ResNet) to simultaneously
Digital Object Identifier 10.1109/MSMC.2022.3228381
Date of current version: 17 July 2023
extract and classify the brain activity of ASD patients. A
P4D ResNet can extract both temporal and spatial information
from fMRI data, which mainly consists of two different
residual blocks stacked together. In a P4D ResNet,
to reduce computational and parametric quantities, each
residual block is combined with a 3D spatial filter and a 1D
temporal filter instead of a 4D spatiotemporal convolution,
which can perform parallel computation. Due to the high
dimensionality of the complete data and the limited
amount of data, in this article, each piece of fMRI data are
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July 2023 IEEE SYSTEMS, MAN, & CYBERNETICS MAGAZINE
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IEEE Systems, Man and Cybernetics Magazine - July 2023
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IEEE Systems, Man and Cybernetics Magazine - July 2023 - Contents
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