Parameter-free binarization and skeletonization of fiber networks from confocal image stacks

Journal article


Publication Details

Author(s): Krauß P, Metzner C, Lange J, Lang N, Fabry B
Journal: PLoS ONE
Publisher: Public Library of Science
Publication year: 2012
Volume: 7
Journal issue: 5
ISSN: 1932-6203


Abstract


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 3×3×3 neighborhood. This optimization criterion makes our method free of user-defined parameters and the output exceptionally robust against imaging noise. © 2012 Krauss et al.


FAU Authors / FAU Editors

Fabry, Ben Prof. Dr.
Lehrstuhl für Biophysik
Lang, Nadine
Lehrstuhl für Biophysik
Lange, Janina
Lehrstuhl für Biophysik
Metzner, Claus PD Dr.
Lehrstuhl für Biophysik

Last updated on 2019-18-07 at 16:53