Skip to main content

Segmentation of Skeletal Muscle Fibres for Applications in Computational Skeletal Muscle Mechanics

  • Conference paper
  • First Online:

Abstract

We present a semi-automatic method to segment single muscle fibres from skeletal muscle cross-section images. As a pre-processing step we apply different filters depending on the type of the manually selected image region to obtain an edge image. Then we detect circles within the image by a circular Hough transform as initial rough approximation to the muscle fibre slices. This approximation is improved by active contours, where the circles are deformed to fit to the specific shape of the muscle fibres. The implementation of the segmentation method was done in Matlab. We show qualitative and quantitative results for different image regions and also outline a straight-forward method to combine several slices to obtain a 3D piece of a muscle fibre, which forms the input to an electro-mechanical skeletal muscle model.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Hodgkin, A. L., Huxley, A. F., 1952. A quantitative description of membrane current and its application to conduction and excitation in nerve. J Physiol 117 (4), 500–44.

    Google Scholar 

  2. Shorten, P., O’Callaghan, P., Davidson, J., Soboleva, T., 2007. A mathematical model of fatigue in skeletal muscle force contraction. J Muscle Res. Cell Motil. 28 (6), 293–313.

    Google Scholar 

  3. Ding, J., Wexler, A. S., Binder-Macleod, S. A., 2000. Development of a mathematical model that predicts optimal muscle activation patterns by using brief trains. J of Appl. Physiol. 88 (3), 917–925.

    Google Scholar 

  4. Zajac, F. E., 1989. Muscle and tendon: properties, models, scaling, and application to biomechanics and motor control. Crit Rev Biomed Eng 17 (4), 359–411.

    Google Scholar 

  5. Johansson, T., Meier, P., Blickhan, R., 2000. A finite-element model for the mechanical analysis of skeletal muscles. J Theor Biol 206 (1), 131–49.

    Article  Google Scholar 

  6. Oomens, C. W. J., Maenhout, M., van Oijen, C. H., Drost, M. R., Baaijens, F. P., 2003. Finite element modelling of contracting skeletal muscle. Philos. Trans. R. Soc. London, Ser. B, 358 (1437), 1453–1460.

    Google Scholar 

  7. Blemker, S. S., Pinsky, P. M., Delp, S. L., 2005. A 3d model of muscle reveals the causes of nonuniform strains in the biceps brachii, J. Biomech. 38 (4), 657–665.

    Article  Google Scholar 

  8. Böl, M., Reese, S., 2007. A new approach for the simulation of skeletal muscles using the tool of statistical mechanics. Materialwiss. Werkstofftech. 38 (12), 955–964.

    Article  Google Scholar 

  9. Röhrle, O., Davidson, J., Pullan, A., 2008. Bridging scales: a three-dimensional electromechanical finite element model of skeletal muscle. SIAM J. Sci. Comput. 30 (6), 2882–2904.

    Article  MathSciNet  MATH  Google Scholar 

  10. Röhrle, O., 2010. Simulating the electro-mechanical behavior of skeletal muscles. IEEE CiSE, DOI 10.1109/MCSE.2010.30.

    Google Scholar 

  11. Sands, G.B., Gerneke, D.A., Hooks, D.A., Green, C.R., Smaill, B.H., LeGrice, I.J., 2005. Automated imaging of extended tissue volumes using confocal microscopy. Microsc Res Tech 67 (5), 227–39.

    Article  Google Scholar 

  12. Jähne, B., 2005. Digitale Bildverarbeitung, Springer-Verlag.

    Google Scholar 

  13. Ballard, D.H., 1981. Generalizing the Hough transform to detect arbitrary shapes, Pattern Recognit., 13, 111–122.

    Article  MATH  Google Scholar 

  14. Kass M., Witkin, A., Terzopoulos, D., 1988. Snakes-active contour models, Int. J. Comput. Vision 1, pp. 321–331.

    Article  Google Scholar 

  15. Osher, S., Fedkiw, R.P., 2002. Level set methods and dynamic implicit surfaces, Springer Verlag.

    Google Scholar 

  16. Osher, S., Paragios, N., 2003. Geometric level set methods in imaging, vision and graphics, Springer Verlag.

    Google Scholar 

  17. Li, B., Acton, S.T., 2007. Active Contour External Force Using Vector Field Convolution For Image Segmentation, IEEE Trans. Image Process. 16 (6), 2096–2106.

    Article  MathSciNet  Google Scholar 

  18. Maas, H., Baan, G. C., Huijing, P. A., 2001. Intermuscular interaction via myofascial force transmission: effects of tibialis anterior and extensor hallucis longus length on force transmission from rat extensor digitorum longus muscle. J Biomech 34 (7), 927–940.

    Article  Google Scholar 

  19. Bloch, R., Gonzalez-Serratos, H., 2003. Lateral force transmission across costameres in skeletal muscle. Exercise Sport Sci R 31 (2), 73–78.

    Article  Google Scholar 

Download references

Acknowledgements

The authors thank Dane Gerneke from the Auckland Bioengineering Institute (ABI) at the University of Auckland, New Zealand, for his tremendous effort, help, and expertise in preparing and imaging the skeletal muscle sample. The authors also thank A/Prof. Ian LeGrice from the ABI for providing the necessary lab space and access to the Welcome Trust extended-volume imaging system.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to O. Röhrle .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer Science+Business Media, LLC

About this paper

Cite this paper

Röhrle, O., Köstler, H., Loch, M. (2011). Segmentation of Skeletal Muscle Fibres for Applications in Computational Skeletal Muscle Mechanics. In: Wittek, A., Nielsen, P., Miller, K. (eds) Computational Biomechanics for Medicine. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-9619-0_12

Download citation

  • DOI: https://doi.org/10.1007/978-1-4419-9619-0_12

  • Published:

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4419-9618-3

  • Online ISBN: 978-1-4419-9619-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics