Approach for semi-automated measurement of fiber diameter in murine and canine skeletal muscle.

Autor: Stevens CR; Department of Clinical Sciences, Cornell University College of Veterinary Medicine, Ithaca, New York, United States of America., Berenson J; Department of Clinical Sciences, Cornell University College of Veterinary Medicine, Ithaca, New York, United States of America., Sledziona M; Department of Clinical Sciences, Cornell University College of Veterinary Medicine, Ithaca, New York, United States of America., Moore TP; Department of Clinical Sciences, Cornell University College of Veterinary Medicine, Ithaca, New York, United States of America., Dong L; Department of Clinical Sciences, Cornell University College of Veterinary Medicine, Ithaca, New York, United States of America., Cheetham J; Department of Clinical Sciences, Cornell University College of Veterinary Medicine, Ithaca, New York, United States of America.
Jazyk: angličtina
Zdroj: PloS one [PLoS One] 2020 Dec 23; Vol. 15 (12), pp. e0243163. Date of Electronic Publication: 2020 Dec 23 (Print Publication: 2020).
DOI: 10.1371/journal.pone.0243163
Abstrakt: Currently available software tools for automated segmentation and analysis of muscle cross-section images often perform poorly in cases of weak or non-uniform staining conditions. To address these issues, our group has developed the MyoSAT (Myofiber Segmentation and Analysis Tool) image-processing pipeline. MyoSAT combines several unconventional approaches including advanced background leveling, Perona-Malik anisotropic diffusion filtering, and Steger's line detection algorithm to aid in pre-processing and enhancement of the muscle image. Final segmentation is based upon marker-based watershed segmentation. Validation tests using collagen V labeled murine and canine muscle tissue demonstrate that MyoSAT can determine mean muscle fiber diameter with an average accuracy of ~92.4%. The software has been tested to work on full muscle cross-sections and works well even under non-optimal staining conditions. The MyoSAT software tool has been implemented as a macro for the freely available ImageJ software platform. This new segmentation tool allows scientists to efficiently analyze large muscle cross-sections for use in research studies and diagnostics.
Competing Interests: The authors have declared that no competing interests exist.
Databáze: MEDLINE
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