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