Paper
14 February 2012 Automatic segmentation and analysis of fibrin networks in 3D confocal microscopy images
Xiaomin Liu, Jian Mu, Kellie R. Machlus, Alisa S. Wolberg, Elliot D. Rosen, Zhiliang Xu, Mark S. Alber, Danny Z. Chen
Author Affiliations +
Abstract
Fibrin networks are a major component of blood clots that provides structural support to the formation of growing clots. Abnormal fibrin networks that are too rigid or too unstable can promote cardiovascular problems and/or bleeding. However, current biological studies of fibrin networks rarely perform quantitative analysis of their structural properties (e.g., the density of branch points) due to the massive branching structures of the networks. In this paper, we present a new approach for segmenting and analyzing fibrin networks in 3D confocal microscopy images. We first identify the target fibrin network by applying the 3D region growing method with global thresholding. We then produce a one-voxel wide centerline for each fiber segment along which the branch points and other structural information of the network can be obtained. Branch points are identified by a novel approach based on the outer medial axis. Cells within the fibrin network are segmented by a new algorithm that combines cluster detection and surface reconstruction based on the α-shape approach. Our algorithm has been evaluated on computer phantom images of fibrin networks for identifying branch points. Experiments on z-stack images of different types of fibrin networks yielded results that are consistent with biological observations.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xiaomin Liu, Jian Mu, Kellie R. Machlus, Alisa S. Wolberg, Elliot D. Rosen, Zhiliang Xu, Mark S. Alber, and Danny Z. Chen "Automatic segmentation and analysis of fibrin networks in 3D confocal microscopy images", Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 831439 (14 February 2012); https://doi.org/10.1117/12.911712
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Image segmentation

3D image processing

Confocal microscopy

Reconstruction algorithms

3D acquisition

Network security

Structured optical fibers

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