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Myo Vision: Software for automated high-content analysis of skeletal muscle immunohistochemistry

Producción científica: Articlerevisión exhaustiva

199 Citas (Scopus)

Resumen

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.

Idioma originalEnglish
Páginas (desde-hasta)40-51
Número de páginas12
PublicaciónJournal of Applied Physiology
Volumen124
N.º1
DOI
EstadoPublished - ene 2018

Nota bibliográfica

Publisher Copyright:
Copyright © 2018 American Physiological Society. All rights reserved.

Financiación

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.

FinanciadoresNúmero del financiador
National Institutes of Health (NIH)AR061939, UL1TR001998, AR060701
National Institute of Arthritis and Musculoskeletal and Skin DiseasesF32AR071753

    ASJC Scopus subject areas

    • Physiology
    • Physiology (medical)

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