Computer Vision Methods for the Automatic Analysis of Fibrous Structures in Biological Soft Tissues

Soft tissue like tendons, arteries, veins or skins are important biological materials. A greater understanding of the foundations and interactions of structure and function of soft tissue, and, in particular, the associated mechanobiology is of great interest in the field. A thorough understanding of the complex interrelations between mechanical factors and the associated biological responses may help to improve diagnostics which allow disease and injury to be treated earlier. The research proposed here will develop a fully automatic system for analyzing macroscopic structures obtained from histological images of arteries by means of modern computer vision techniques. Besides being interesting from the mechanobiological point of view the structural analysis of images of collagen fibers poses also several challenging questions from a computer vision point of view. In particular, due to the wide variety of different appearances of collagen fibers in images this task is non trivial. The main task of this research is the development of novel segmentation techniques for robustly segmenting individual fibril bundles and estimating their parameters, like location and shape, fibril density, mean fibril orientation, wriggling of fibrils etc. This will be achieved by developing novel perceptual grouping methods operating on the extracted orientation data of fibrils. Another major challenge of this research is to extend the structural analysis from 2D to 3D.