QuantiMus: A Machine Learning-Based Approach for High Precision Analysis of Skeletal Muscle Morphology

QuantiMus: A Machine Learning-Based Approach for High Precision Analysis of Skeletal Muscle Morphology

Skeletal muscle injury provokes a regenerative response, characterized by the de novo generation of myofibers that are distinguished by central nucleation and re-expression of developmentally restricted genes. In addition to these characteristics, myofiber cross-sectional area (CSA) is widely used t...

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Bibliographic Details
Main Authors: Jenna M. Kastenschmidt, Kyle L. Ellefsen, Ali H. Mannaa, Jesse J. Giebel, Rayan Yahia, Rachel E. Ayer, Phillip Pham, Rodolfo Rios, Sylvia A. Vetrone, Tahseen Mozaffar, S. Armando Villalta
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-11-01
Series:Frontiers in Physiology
Subjects:
muscle regeneration
cross-sectional area
central nucleation
Duchenne muscular dystrophy
machine learning
histological analysis
Online Access:https://www.frontiersin.org/article/10.3389/fphys.2019.01416/full

Internet

https://www.frontiersin.org/article/10.3389/fphys.2019.01416/full

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