Abstract: High-resolution micro-CT scanners permit the generation of three-dimensional (3D) digital images containing extensive vascular networks. These images provide data needed to study the overall structure and function of such complex networks. Unfortunately, human operators have extreme difficulty in extracting the hundreds of vascular segments contained in the images. Also, no suitable network representation exists that permits straightforward structural analysis and information retrieval. This work proposes an automatic procedure for extracting and analyzing the vascular network contained in very large 3D CT images, such as can be generated by 3D micro- CT and by helical CT scanners. The procedure is efficient in terms of both execution time and memory usage. As results demonstrate, the procedure faithfully follows human-defined measurements and provides far more information than can be defined interactively. !31
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