The vascular system is a multi-scale network whose functionality depends on its structure, and for which structural alterations can be linked to pathological shifts. Though biologists use multiple 3D imaging techniques to visualize vascular networks, the 3D image processing methodologies remain sources of biases, and the extraction of quantitative morphometric descriptors remains flawed. The article, first, reviews the current 3D image processing methodologies, and morphometric descriptors of vascular network images mainly obtained by light-sheet microscopy on optically cleared organs, found in the literature. Second, it proposes operator-independent segmentation and skeletonization methodologies using the freeware ImageJ. Third, it gives more extractable network-level (density, connectivity, fractal dimension) and segment-level (length, diameter, tortuosity) 3D morphometric descriptors and how to statistically analyze them. Thus, it can serve as a guideline for biologists using 3D imaging techniques of vascular networks, allowing the production of more comparable studies in the future.
