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Approach for semi-automated measurement of fiber diameter in murine and canine skeletal muscle.
- Source :
-
PLoS ONE . 12/23/2020, Vol. 15 Issue 12, p1-13. 13p. - Publication Year :
- 2020
-
Abstract
- 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. [ABSTRACT FROM AUTHOR]
- Subjects :
- *SOFTWARE development tools
*IMAGE intensifiers
*ALGORITHMS
*SCIENTISTS
*DIAMETER
Subjects
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 15
- Issue :
- 12
- Database :
- Academic Search Index
- Journal :
- PLoS ONE
- Publication Type :
- Academic Journal
- Accession number :
- 147754678
- Full Text :
- https://doi.org/10.1371/journal.pone.0243163