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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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x-z cross-section of a 3D image stack.(A) Perpendicular cross-sections of collagen fibers appear as elliptical spots of finite size that can be easily recognized by 2D template matching. (B) The shape of the spot varies as the angle of intersection becomes less than 90 degrees. For angles less than 45 degrees, the distortion of the spot can become too large to match the template.
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pone-0036575-g004: x-z cross-section of a 3D image stack.(A) Perpendicular cross-sections of collagen fibers appear as elliptical spots of finite size that can be easily recognized by 2D template matching. (B) The shape of the spot varies as the angle of intersection becomes less than 90 degrees. For angles less than 45 degrees, the distortion of the spot can become too large to match the template.

Mentions: However, the situation is much simpler when only 2D cross-sections are used for the template matching: The vertical cross-section of a broadened line segment with a plane is a elliptical spot of finite size that can be easily recognized by 2D template matching (see marking A in Fig. 4). The shape of the spot will vary as the angle of intersection becomes less than 90 degrees. For angles less than 45 degrees, the distortion of the spot can become too large to match the template (see marking B in Fig. 4), but in this case the same line segment can be easily recognized by its intersection with a perpendicular plane. Therefore, all line segments (solid voxels) can be detected by sequentially scanning through the x-, y- and z-direction of the sample volume. As shown below, this binarization method turns out to be much more reliable and robust than the simple threshold method.


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)

x-z cross-section of a 3D image stack.(A) Perpendicular cross-sections of collagen fibers appear as elliptical spots of finite size that can be easily recognized by 2D template matching. (B) The shape of the spot varies as the angle of intersection becomes less than 90 degrees. For angles less than 45 degrees, the distortion of the spot can become too large to match the template.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3351466&req=5

pone-0036575-g004: x-z cross-section of a 3D image stack.(A) Perpendicular cross-sections of collagen fibers appear as elliptical spots of finite size that can be easily recognized by 2D template matching. (B) The shape of the spot varies as the angle of intersection becomes less than 90 degrees. For angles less than 45 degrees, the distortion of the spot can become too large to match the template.
Mentions: However, the situation is much simpler when only 2D cross-sections are used for the template matching: The vertical cross-section of a broadened line segment with a plane is a elliptical spot of finite size that can be easily recognized by 2D template matching (see marking A in Fig. 4). The shape of the spot will vary as the angle of intersection becomes less than 90 degrees. For angles less than 45 degrees, the distortion of the spot can become too large to match the template (see marking B in Fig. 4), but in this case the same line segment can be easily recognized by its intersection with a perpendicular plane. Therefore, all line segments (solid voxels) can be detected by sequentially scanning through the x-, y- and z-direction of the sample volume. As shown below, this binarization method turns out to be much more reliable and robust than the simple threshold method.

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
Related in: MedlinePlus