A surface-based method for detection of coronary vessel boundaries in poor quality X-ray angiogram images

Abstract

In this paper, we propose a surface-based method for simultaneous detection of left and right coronary borders that is suitable for analysis of poor quality X-ray angiogram images. Coronary artery is modelled with a 3D generalized cylinder (GC) with elliptic cross-sections. Based on this model, we developed a 2D surface function for the projection intensity distribution of a vessel part. The parameters associated with vessel edges are estimated from this model. The model takes into account local background intensity, noise and blurring. In simulation and real experiments over a range of imaging conditions, the proposed method consistently produced lower estimation error and variability in detecting edges than our previously reported 1D profile-based method. The improvement is most significant especially for noisy and low-contrast angiograms.