Accuracy assessment of layer decomposition using simulated angiographic image sequences.

Abstract

Layer decomposition is a promising method for obtaining accurate densitometric profiles of diseased coronary artery segments. This method decomposes coronary angiographic image sequences into moving densitometric layers undergoing translation, rotation, and scaling. In order to evaluate the accuracy of this technique, we have developed a technique for embedding realistic simulated 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 correlation and fixed mask subtraction, respectively. Second, we compute the correlation coefficient between the true vessel profile and the raw and processed images in the region of the stenosis. We find that layer decomposition significantly improves the correlation coefficient.