Parameter-Free Binarization and Skeletonization of Fiber Networks from Confocal Image StacksReport as inadecuate




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We present a method to reconstruct a disordered network of thin biopolymers, such as collagen gels, from three-dimensional 3D image stacks recorded with a confocal microscope. The method is based on a template matching algorithm that simultaneously performs a binarization and skeletonization of the network. The size and intensity pattern of the template is automatically adapted to the input data so that the method is scale invariant and generic. Furthermore, the template matching threshold is iteratively optimized to ensure that the final skeletonized network obeys a universal property of voxelized random line networks, namely, solid-phase voxels have most likely three solid-phase neighbors in a neighborhood. This optimization criterion makes our method free of user-defined parameters and the output exceptionally robust against imaging noise.



Author: Patrick Krauss, Claus Metzner, Janina Lange, Nadine Lang, Ben Fabry

Source: http://plos.srce.hr/



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