High-resolution micro-computed tomography (CT) scanners now exist for imaging small animals. In particular, such a scanner can generate very large three-dimensional (3-D) digital images of the rat's hepatic vasculature. These images provide data on the overall structure and function of such complex vascular trees. Unfortunately, human operators have extreme difficulty in extracting the extensive vasculature contained in the images. Also, no suitable tree representation exists that permits straight-forward structural analysis and information retrieval. This work proposes an automatic procedure for extracting and representing such a vascular tree. The procedure is both computation and memory efficient and runs on current PCs. As the results demonstrate, the procedure faithfully follows human-defined measurements and provides far more information than can be defined interactively.
ASJC Scopus subject areas
- Radiological and Ultrasound Technology
- Computer Science Applications
- Electrical and Electronic Engineering