Thin network extraction in 3D images: application to medical angiograms

Thin network extraction from three dimensional images is a new issue in computer vision. It is of major importance in medical vascular imaging for diagnostic, therapy planning and surgery. In this paper, we develop a framework for automatic thin network extraction from the volumic image. The approach consists in treating the 3D image as a hyper-surface of IR/sup 4/. It is shown that the crest points of this hyper-surface correspond to the center line of the thin network in the image. Using a simple mathematical model, we establish the relationship between the computed principal curvatures of the hyper-surface and the geometry of the network. Promising results are shown on synthetic and real vascular images.