3D-CNN based discrimination of schizophrenia using resting-state fMRI.

Journal: Artificial intelligence in medicine

Published Date: Jun 22, 2019

Abstract

MOTIVATION: This study reports a framework to discriminate patients with schizophrenia and normal healthy control subjects, based on magnetic resonance imaging (MRI) of the brain. Resting-state functional MRI data from a total of 144 subjects (72 patients with schizophrenia and 72 healthy controls) was obtained from a publicly available dataset using a three-dimensional convolution neural network 3D-CNN based deep learning classification framework and ICA based features.

Authors

Muhammad Naveed Iqbal Qureshi

Department of Biomedical Science and Engineering (BMSE), Institute of Integrated Technology (IIT), Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea.
Jooyoung Oh

Department of Biomedical Science and Engineering (BMSE), Institute of Integrated Technology (IIT), Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea. These authors contributed equally to this work.
Boreom Lee

Department of Biomedical Science and Engineering (BMSE), Institute of Integrated Technology (IIT), Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea.

Keywords

Adult Area Under Curve Brain Case-Control Studies Deep Learning Discriminant Analysis Female Functional Neuroimaging Humans Magnetic Resonance Imaging Male Middle Aged Neural Networks, Computer Rest Schizophrenia Young Adult

External Resources

View on PubMed Access via DOI PubMed (31521248)

3D-CNN based discrimination of schizophrenia using resting-state fMRI.

Abstract

Authors

Keywords

External Resources

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