Abstract
Arteries are prominent organs composed of soft tissues which have to distend in response to pulse waves. Once it is possible to develop reliable mechanical models of these soft tissues, a better understanding of several cardiovascular diseases, such as atherosclerosis, and interventional treatments, such as balloon angioplasty, might be possible. Numerical simulations which are based on realistic and efficient mechanobiological models could help to find optimal medical treatment strategies against diseases and injuries. In order to obtain reliable models of blood vessels, one aim is to describe the concentration and structural arrangements of collagen fibers in the associated soft tissue. A new approach for an automatic structural analysis of collagen in the outermost layer of the human blood vessel, i.e., the adventitia (tunica externa), is proposed. The method uses light microscopic images of thinly sliced tissue samples for data extraction. Robust clustering in the RGB space and morphological operations are used to select fiber regions and mask non-fiber regions. Based on ridge and valley detections, the fiber orientations of small fiber patches are robustly calculated. Finally, region growing is used to combine the fiber patches to regions of a homogeneous fiber orientation. Experimental results demonstrate the accurate fiber orientation detection. The extracted data are intended to be used in biomechanical models for blood vessels.
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This is a standard embedding material in histology.
This is a standard stain in histology.
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Acknowledgements
Financial support for this research was provided by the Austrian Science Foundation under START-Award Y74-TEC and by the Amt der Steiermärkischen Landesregierung – Abteilung für Wissenschaft und Forschung. The first author was supported by a doctoral scholarship program granted by the Austrian Academy of Sciences. These supports are gratefully acknowledged.
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Elbischger, P.J., Bischof, H., Regitnig, P. et al. Automatic analysis of collagen fiber orientation in the outermost layer of human arteries. Pattern Anal Applic 7, 269–284 (2004). https://doi.org/10.1007/s10044-004-0224-3
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DOI: https://doi.org/10.1007/s10044-004-0224-3