Segmentation, modelling and reconstruction of arterial bifurcations in digital angiography

The paper presents a method to model an arterial bifurcation from a pair of X-ray angiographic images. It is the initial step of a reconstruction process aiming at detecting and quantifying abnormal sites located on bifurcations. The method proposed consists of two steps. First, each image is independently segmented to extract the vessels in the images. The algorithm uses dynamic programming first to find the bifurcation centrelines from the original images, and secondly to extract vessel edges from the morphological gradient images, under a constraint of parallelism with the previously detected centrelines. Then, a three-dimensional bifurcation model is built by adapting cylinders around the three-dimensional bifurcation centrelines. These cylinders are obtained as a stack of binary orientable ellipses fitted to the projection densities in the corresponding cross-sections. Results obtained on simulated data, phantom and femoral bifurcations are displayed.