Accuracy assessment of layer decomposition using simulated angiographic image sequences

Layer decomposition is a promising method for obtaining accurate densitomet ric profiles of diseased coronary artery segments. This method decomposes c oronary angiographic image sequences into moving densitometric layers under going translation, rotation, and scaling. In order to evaluate the accuracy of this technique, we have developed a technique for embedding realistic s imulated moving stenotic arteries in real clinical coronary angiograms. We evaluate the accuracy of layer decomposition in two ways. First, we compute tracking errors as the distance between the true and estimated motion of a reference point in the arterial lesion. We find that noise-weighted phase correlation, and layered background subtraction are superior to cross corre lation and fixed mask subtraction, respectively. Second, we compute the cor relation coefficient between the true vessel profile and the raw and proces sed images in the region of the stenosis. We find that laver decomposition significantly improves the correlation coefficient.