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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References
Dubowitz V. Muscle Biopsy: A Practical Approach. London: Bailliere Tindall; 1985.
Dudley AW, Spittal RM, Dayoff RE, Ledley RS. Computed image analysis techniques of skeletal muscle. In: Jasmin G, Proschek L, editors. Microanalysis and Quantification. Basel: Karger; 1984. p. 34–57.
Castleman KR, Chui LA, Martin TP, Edgerton VR. Quantitative muscle biopsy analysis. Monographs in Clinical Cytology 1984;9:101–116.
Collumbien R, Zukowski F, Claeys A, Roels F. Automated analysis of muscle fibre images. Analytical Cellular Pathology 1990;2:373–387.
Klemenčič A, Kovačič S, Pernus F. Automated segmentation of muscle fiber images using active contour models. Cytometry 1998;32:317–326.
Kass M, Witkin A, Terzopoulos D. Snakes: Active contour models. International Journal of Computer Vision 1988;1:321–331.
Caselles V, Kimmel R, Sapiro G. Geodesic active contours. International Journal of Computer Vision 1997;22:61–79.
Kichenassamy S, Kumar A, Olver P, Tannenbaum A, Yezzi A. Conformal curvature flows: from phase transitions to active vision. Archive for Rational Mechanics and Analysis 1996;134:275–301.
Chan T, Vese L. Active contours without edges. IEEE Transactions on Image Processing 2001;10(2):266–277.
Paragios N, Deriche R. Geodesic active regions: A new paradigm to deal with frame partition problems in computer vision. Journal of Visual Communication and Image Representation 2002;13(1/2):249–268.
Brox T, Rousson M, Deriche R, Weickert J. Unsupervised segmentation incorporating colour, texture, and motion. In: Petkov N, Westenberg MA, editors. Computer Analysis of Images and Patterns. vol. 2756 of Lecture Notes in Computer Science. Berlin: Springer; 2003. p. 353–360.
Brox T, Weickert J. A TV flow based local scale estimate and its application to texture discrimination. Journal of Visual Communication and Image Representation 2006. To appear.
Soille P. Morphological Image Analysis. Berlin: Springer; 1999.
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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
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