Myosoft: An automated muscle histology analysis tool using machine learning algorithm utilizing FIJI/ImageJ software

PLoS One. 2020 Mar 4;15(3):e0229041. doi: 10.1371/journal.pone.0229041. eCollection 2020.

Abstract

Methods: Muscle sections were stained for cell boundary (laminin) and myofiber type (myosin heavy chain isoforms). Myosoft, running in the open access software platform FIJI (ImageJ), was used to analyze myofiber size and type in transverse sections of entire gastrocnemius/soleus muscles.

Results: Myosoft provides an accurate analysis of hundreds to thousands of muscle fibers within 25 minutes, which is >10-times faster than manual analysis. We demonstrate that Myosoft is capable of handling high-content images even when image or staining quality is suboptimal, which is a marked improvement over currently available and comparable programs.

Conclusions: Myosoft is a reliable, accurate, high-throughput, and convenient tool to analyze high-content muscle histology. Myosoft is freely available to download from Github at https://github.com/Hyojung-Choo/Myosoft/tree/Myosoft-hub.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms*
  • Anatomy, Cross-Sectional / methods
  • Animals
  • Cell Size
  • High-Throughput Screening Assays / methods*
  • Histological Techniques / methods*
  • Image Processing, Computer-Assisted / methods*
  • Machine Learning
  • Mice
  • Mice, Inbred C57BL
  • Mice, Transgenic
  • Muscle Fibers, Skeletal / cytology
  • Muscle Fibers, Skeletal / pathology
  • Muscle, Skeletal / cytology
  • Muscle, Skeletal / pathology*
  • Reproducibility of Results
  • Software*