Refining Muscle Morphometry Through Machine Learning and Spatial Analysis.

Journal: Neuropathology and applied neurobiology
PMID: 40125691

Abstract

AIMS: Muscle morphology provides important information in differentiating disease aetiology, but its measurement remains challenging because of the lack of an efficient and objective method. This study aimed to quantitatively refine the morphological features of muscle fibres in neuromuscular diseases using machine learning.

Authors

  • Daisuke Ono
    Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, USA.
  • Honami Kawai
    Department of Neurology and Neurological Science, Institute of Science Tokyo, Bunkyo-Ku, Tokyo, Japan.
  • Hiroya Kuwahara
    Department of Neurology and Neurological Science, Institute of Science Tokyo, Bunkyo-Ku, Tokyo, Japan.
  • Takanori Yokota
    Department of Neurology and Neurological Science, Institute of Science Tokyo, Bunkyo-Ku, Tokyo, Japan.

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