Automatic segmentation and analysis of fibrin networks in 3D confocal microscopy images

Xiaomin Liu, Jian Mu, Kellie R. Machlus, Alisa S. Wolberg, Elliot Rosen, Zhiliang Xu, Mark S. Alber, Danny Z. Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume8314
DOIs
StatePublished - 2012
EventMedical Imaging 2012: Image Processing - San Diego, CA, United States
Duration: Feb 6 2012Feb 9 2012

Other

OtherMedical Imaging 2012: Image Processing
CountryUnited States
CitySan Diego, CA
Period2/6/122/9/12

Fingerprint

fibrin
Confocal microscopy
Fibrin
Confocal Microscopy
microscopy
Surface reconstruction
Structural properties
Blood
Fibers
Chemical analysis
Experiments
Information Services
bleeding
Thrombosis
quantitative analysis
blood
Hemorrhage

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Radiology Nuclear Medicine and imaging

Cite this

Liu, X., Mu, J., Machlus, K. R., Wolberg, A. S., Rosen, E., Xu, Z., ... Chen, D. Z. (2012). Automatic segmentation and analysis of fibrin networks in 3D confocal microscopy images. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE (Vol. 8314). [831439] https://doi.org/10.1117/12.911712

Automatic segmentation and analysis of fibrin networks in 3D confocal microscopy images. / Liu, Xiaomin; Mu, Jian; Machlus, Kellie R.; Wolberg, Alisa S.; Rosen, Elliot; Xu, Zhiliang; Alber, Mark S.; Chen, Danny Z.

Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 8314 2012. 831439.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Liu, X, Mu, J, Machlus, KR, Wolberg, AS, Rosen, E, Xu, Z, Alber, MS & Chen, DZ 2012, Automatic segmentation and analysis of fibrin networks in 3D confocal microscopy images. in Progress in Biomedical Optics and Imaging - Proceedings of SPIE. vol. 8314, 831439, Medical Imaging 2012: Image Processing, San Diego, CA, United States, 2/6/12. https://doi.org/10.1117/12.911712
Liu X, Mu J, Machlus KR, Wolberg AS, Rosen E, Xu Z et al. Automatic segmentation and analysis of fibrin networks in 3D confocal microscopy images. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 8314. 2012. 831439 https://doi.org/10.1117/12.911712
Liu, Xiaomin ; Mu, Jian ; Machlus, Kellie R. ; Wolberg, Alisa S. ; Rosen, Elliot ; Xu, Zhiliang ; Alber, Mark S. ; Chen, Danny Z. / Automatic segmentation and analysis of fibrin networks in 3D confocal microscopy images. Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 8314 2012.
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