Quantitative assessment of brain structural abnormalities in children with autism spectrum disorder based on artificial intelligence automatic brain segmentation technology and machine learning methods.

Journal: Psychiatry research. Neuroimaging
Published Date: Sep 16, 2024

Abstract

RATIONALE AND OBJECTIVES: To explore the characteristics of brain structure in Chinese children with autism spectrum disorder (ASD) using artificial intelligence automatic brain segmentation technique, and to diagnose children with ASD using machine learning (ML) methods in combination with structural magnetic resonance imaging (sMRI) features.

Authors

  • Xiaowen Xu
    Key Laboratory for Colloid and Interface Chemistry of Education Ministry, School of Chemistry and Chemical Engineering, Shandong University, 250100 Jinan, PR China. Electronic address: xuxw@sdu.edu.cn.
  • Yang Li
    Occupation of Chinese Center for Disease Control and Prevention, Beijing, China.
  • Ning Ding
    Graduate School of Global Convergence, Kangwon National University, Chuncheon-si, Kangwon Province, 24341, Republic of Korea.
  • Yukun Zang
    Department of Radiology, Qingdao University Affiliated Women and Children's Hospital, 6 Tongfu Road, Qingdao, Shandong 266034, China.
  • Shanshan Sun
    Shandong Institute for Food and Drug Control, Ji'nan 250101, China.
  • Gaoyu Shen
    Shanghai United Imaging Intelligence, Shanghai, China.
  • Xiufeng Song
    Department of Radiology, Qingdao University Affiliated Women and Children's Hospital, 6 Tongfu Road, Qingdao, Shandong 266034, China. Electronic address: song-sxf@163.com.

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