Aging-related volume changes in the brain and cerebrospinal fluid using artificial intelligence-automated segmentation.

Journal: European radiology
PMID: 37060450

Abstract

OBJECTIVES: To verify the reliability of the volumes automatically segmented using a new artificial intelligence (AI)-based application and evaluate changes in the brain and CSF volume with healthy aging.

Authors

  • Shigeki Yamada
    Department of Clinical Pharmacy, Fujita Health University School of Medicine, Toyoake, Japan.
  • Tomohiro Otani
    Department of Obstetrics and Gynecology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8654, Japan.
  • Satoshi Ii
    Faculty of System Design, Tokyo Metropolitan University, Hachioji, Tokyo, Japan.
  • Hiroto Kawano
    Department of Neurosurgery, Shiga University of Medical Science, Ōtsu, Shiga, Japan.
  • Kazuhiko Nozaki
    Department of Neurosurgery, Shiga University of Medical Science, Ōtsu, Shiga, Japan.
  • Shigeo Wada
    Department of Mechanical Science and Bioengineering, Graduate School of Engineering Science, Osaka University, Osaka, Japan.
  • Marie Oshima
    Interfaculty Initiative in Information Studies / Institute of Industrial Science, The University of Tokyo, Tokyo, Japan.
  • Yoshiyuki Watanabe
    Department of Future Diagnostic Radiology, Osaka University Graduate School of Medicine.

Keywords

External Resources

Popular Topics
Recent Journals