Abstract
Analysis of skeletal muscle cross sections is an important experimental technique in muscle biology. Many aspects of immunohistochemistry and fluorescence microscopy can now be automated, but most image quantification techniques still require extensive human input, slowing progress and introducing the possibility of user bias. MyoVision is a new software package that was developed to overcome these limitations. The software improves upon previously reported automatic techniques and analyzes images without requiring significant human input and correction. When compared with data derived by manual quantification, MyoVision achieves an accuracy of > 94% for basic measurements such as fiber number, fiber type distribution, fiber cross-sectional area, and myonuclear number. Scientists can download the software free from www.MyoVision.org and use it to automate the analysis of their own experimental data. This will improve the efficiency and consistency of the analysis of muscle cross sections and help to reduce the burden of routine image quantification in muscle biology.
Original language | English |
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Pages (from-to) | 40-51 |
Number of pages | 12 |
Journal | Journal of Applied Physiology |
Volume | 124 |
Issue number | 1 |
DOIs | |
State | Published - Jan 2018 |
Bibliographical note
Publisher Copyright:Copyright © 2018 American Physiological Society. All rights reserved.
Funding
This work was made possible by grants from the National Institutes of Health to J. J. McCarthy (AR061939), to C. A. Peterson and J. J. McCarthy (AR060701), and to K. A. Murach (AR071753), with salary support (UL1TR001998) to K. S. Campbell.
Funders | Funder number |
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National Institutes of Health (NIH) | AR061939, UL1TR001998, AR060701 |
National Institute of Arthritis and Musculoskeletal and Skin Diseases | F32AR071753 |
Keywords
- Automation software
- Cell morphology
- High-content microscopy
- Image analysis
- Skeletal muscle
ASJC Scopus subject areas
- Physiology
- Physiology (medical)