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3-D quantification and visualization of vascular structures from confocal microscopic images using skeletonization and voxel-coding.

Hamid Soltanian-Zadeh·Ali Shahrokni·Mohammad-Mehdi Khalighi·Zheng G Zhang·Reza A Zoroofi·Mahnaz Maddah·Michael Chopp
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Abstract

This paper presents an image processing approach for information extraction from three-dimensional (3-D) images of vasculature. It extracts quantitative information such as skeleton, length, diameter, and vessel-to-tissue ratio for different vessels as well as their branches. Furthermore, it generates 3-D visualization of vessels based on desired anatomical characteristics such as vessel diameter or 3-D connectivity. Steps of the proposed approach are: (1) pre-processing, (2) distance mappings, (3) branch labeling, (4) quantification, and (5) visualization. We have tested and evaluated the proposed algorithms using simulated images of multi-branch vessels and real confocal microscopic images of the vessels in rat brains. Experimental results illustrate performance of the methods and usefulness of the results for medical image analysis applications.

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AnimalsBlood VesselsBrainImaging, Three-DimensionalMicroscopy, ConfocalRatsJournal Article

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Hamid Soltanian-Zadeh, Ali Shahrokni, Mohammad-Mehdi Khalighi, Zheng G Zhang, Reza A Zoroofi, Mahnaz Maddah, Michael Chopp. 2005. 3-D quantification and visualization of vascular structures from confocal microscopic images using skeletonization and voxel-coding.. https://doi.org/10.1016/j.compbiomed.2004.06.009

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