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

Krauss P, Metzner C, Lange J, Lang N, Fabry B - PLoS ONE (2012)

Bottom Line: 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 x 3 x 3 neighborhood.This optimization criterion makes our method free of user-defined parameters and the output exceptionally robust against imaging noise.

View Article: PubMed Central - PubMed

Affiliation: Department of Physics, Biophysics Group, Friedrich-Alexander University, Erlangen, Germany.

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 x 3 x 3 neighborhood. This optimization criterion makes our method free of user-defined parameters and the output exceptionally robust against imaging noise.

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Test of scale invariance.The same collagen gel has been recorded with three different optical resolutions (relative voxel sizes: high/medium/low  1/2/4). After reconstructing the three image stacks, the distribution of nearest obstacle distances were computed. The low and medium resolutions give similar results. Only at the highest resolution, the pores appear slightly smaller on average, because under these conditions even fine details of the network can be resolved.
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pone-0036575-g012: Test of scale invariance.The same collagen gel has been recorded with three different optical resolutions (relative voxel sizes: high/medium/low 1/2/4). After reconstructing the three image stacks, the distribution of nearest obstacle distances were computed. The low and medium resolutions give similar results. Only at the highest resolution, the pores appear slightly smaller on average, because under these conditions even fine details of the network can be resolved.

Mentions: Since the templates are adaptively generated from the input data, the algorithm is scale invariant. In order to test this, we recorded the same collagen gel with low resolution (256×256×286 voxels of size 600.6 nm×600.6 nm×168 nm), medium resolution (512×512×512 voxels of size 300.2 nm×300.2 nm×293.7 nm) and with high resolution (1024×1024×1000 voxels of size 150.2 nm×150.2 nm×167.8 nm). The three input stacks were reconstructed and for each binarized stack the distribution of nearest obstacle distances was determined. We found almost identical distributions for the low and medium resolution (Fig. 12). For the highest resolution, the average pore size was slightly smaller because finer structures of the network can be resolved. This trend was confirmed by repeating the experiment with two other gels, including also a dense gel with higher collagen concentration (data not shown).


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

Krauss P, Metzner C, Lange J, Lang N, Fabry B - PLoS ONE (2012)

Test of scale invariance.The same collagen gel has been recorded with three different optical resolutions (relative voxel sizes: high/medium/low  1/2/4). After reconstructing the three image stacks, the distribution of nearest obstacle distances were computed. The low and medium resolutions give similar results. Only at the highest resolution, the pores appear slightly smaller on average, because under these conditions even fine details of the network can be resolved.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3351466&req=5

pone-0036575-g012: Test of scale invariance.The same collagen gel has been recorded with three different optical resolutions (relative voxel sizes: high/medium/low 1/2/4). After reconstructing the three image stacks, the distribution of nearest obstacle distances were computed. The low and medium resolutions give similar results. Only at the highest resolution, the pores appear slightly smaller on average, because under these conditions even fine details of the network can be resolved.
Mentions: Since the templates are adaptively generated from the input data, the algorithm is scale invariant. In order to test this, we recorded the same collagen gel with low resolution (256×256×286 voxels of size 600.6 nm×600.6 nm×168 nm), medium resolution (512×512×512 voxels of size 300.2 nm×300.2 nm×293.7 nm) and with high resolution (1024×1024×1000 voxels of size 150.2 nm×150.2 nm×167.8 nm). The three input stacks were reconstructed and for each binarized stack the distribution of nearest obstacle distances was determined. We found almost identical distributions for the low and medium resolution (Fig. 12). For the highest resolution, the average pore size was slightly smaller because finer structures of the network can be resolved. This trend was confirmed by repeating the experiment with two other gels, including also a dense gel with higher collagen concentration (data not shown).

Bottom Line: 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 x 3 x 3 neighborhood.This optimization criterion makes our method free of user-defined parameters and the output exceptionally robust against imaging noise.

View Article: PubMed Central - PubMed

Affiliation: Department of Physics, Biophysics Group, Friedrich-Alexander University, Erlangen, Germany.

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 x 3 x 3 neighborhood. This optimization criterion makes our method free of user-defined parameters and the output exceptionally robust against imaging noise.

Show MeSH