Pattern recognition of schizophrenia based on multidimensional spatial feature fusion

Shuqi Guo; Yuhang Lin; Shi Zhao; Yan Cui; Yang Xia; Ke Chen; Dezhong Yao; Daqing Guo

doi:10.1080/27706710.2023.2249036

Brain-Apparatus Communication (Dec 2023)

Pattern recognition of schizophrenia based on multidimensional spatial feature fusion

Shuqi Guo,
Yuhang Lin,
Shi Zhao,
Yan Cui,
Yang Xia,
Ke Chen,
Dezhong Yao,
Daqing Guo

Affiliations

Shuqi Guo: School of Life Science and Technology, Centre for Information in Medicine, MOE Key Lab for NeuroInformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China
Yuhang Lin: School of Life Science and Technology, Centre for Information in Medicine, MOE Key Lab for NeuroInformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China
Shi Zhao: School of Life Science and Technology, Centre for Information in Medicine, MOE Key Lab for NeuroInformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China
Yan Cui: School of Life Science and Technology, Centre for Information in Medicine, MOE Key Lab for NeuroInformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China
Yang Xia: School of Life Science and Technology, Centre for Information in Medicine, MOE Key Lab for NeuroInformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China
Ke Chen: School of Life Science and Technology, Centre for Information in Medicine, MOE Key Lab for NeuroInformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China
Dezhong Yao: School of Life Science and Technology, Centre for Information in Medicine, MOE Key Lab for NeuroInformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China
Daqing Guo: School of Life Science and Technology, Centre for Information in Medicine, MOE Key Lab for NeuroInformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China

DOI: https://doi.org/10.1080/27706710.2023.2249036
Journal volume & issue: Vol. 2, no. 1

Abstract

Read online

Purpose Schizophrenia (SCH) is a severe psychiatric disorder associated with brain connectivity abnormalities, and early diagnosis can significantly reduce the burden on the families of the patients. Though several classification methods have been created to identify SCH, a reliable method is yet to be found. In this study, we explore the performance of multidimensional spatial feature fusion in the recognition of SCH. Materials and methods Using an MRI connectomes dataset, we extract the spatial pattern network (SPN) and diffusion map embedding (DME) features from functional connectivity (FC) and structural connectivity (SC) networks of both schizophrenic patients and healthy subjects, and we use both single mode features and fused features to classify the two groups. Results Compared to the single mode features, the fused features showed superior performance in classification. By fusing the SPN and DME features of the structural network, we obtained the highest accuracy of 87.50%. Conclusions Multidimensional spatial feature fusion is promising as a reliable method for the recognition of SCH.

Published in Brain-Apparatus Communication

ISSN: 2770-6710 (Online)
Publisher: Taylor & Francis Group
Country of publisher: United Kingdom
LCC subjects: Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry: Neurology. Diseases of the nervous system
Website: https://www.tandfonline.com/journals/tbac20

About the journal

Abstract

Keywords