Abstract
This paper presents a new approach to automated muscle fiber analysis based on segmenting myofibers with combined region and edge-based active contours. It provides reliable and fully-automated processing, thus, enabling time-saving batch processing of the entire biopsy sample stemming from routinely HE-stained cryostat sections. The method combines color, texture, and edge cues in a level set based active contour model succeeded by a refinement with morphological filters. False-positive segmentations as compared to former methods are minimized. A quantitative comparison between manual and automated analysis of muscle fibers images did not reveal any significant differences.
We gratefully acknowledge partial funding by the DFG.
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Brox, T., Kim, YJ., Weickert, J., Feiden, W. (2006). Fully-Automated Analysis of Muscle Fiber Images with Combined Region and Edge-Based Active Contours. In: Handels, H., Ehrhardt, J., Horsch, A., Meinzer, HP., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2006. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32137-3_18
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DOI: https://doi.org/10.1007/3-540-32137-3_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-32136-1
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