Three-dimensional linear prediction and its application to digital angiography

In this article, we apply three-dimensional (3-D) linear least-squares (LS) prediction technique to the processing of digital subtraction angiography (DSA) image sequences. The main goal of this processing is the cancellation of motion artifacts, which is a visual structured noise that appears in current DSA images. We address two important issues with this new technique: first the misregistration between the mask and the contrast image and, second, the temporal filtering of DSA image sequence. Instead of treating these two issues separately, as conventional DSA methods do, we combine them into a 3-D LS prediction problem. Based on this approach, we develop a new efficient algorithm for the solution of normal equations. The algorithm is based on a new property of T super(n) (Toeplitz to the n) matrices that we prove. In order to match the image sequence physical characteristics, we further optimize practical parameters of this algorithm. Actual patient data is used for the evaluation of this new technique. Results show a significant improvement over the existing methods.