Vessel Laminae Segmentation

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Vessel Segmentation

Background and motivation

Accurate and rapid segmentation of microvasculature from three-dimensional (3-D) images is important for diverse studies in neuroscience, tumor biology, stem-cell niches, cancer stem cell niches, and other areas. Vessel segmentation algorithm presents a robust 3-D algorithm to segment vasculature that is image by labeling laminae, rather than lumenal volume. The signal is weak, sparse, noisy, non-uniform, low-contrast, and exhibits gaps and spectral artifacts, so adaptive thresholding & Hessian filtering based methods are not effective.

A 2-D projection of a 3-D blood vessel image. Original res: 0.36 x 0.36 x 1.5 µm3. Original stack size: 1024x1024x77 voxels3

The Algorithm

Programs

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