A new three-dimensional linear predictive algorithm for digital subtraction angiography

The authors apply a 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. Two important issues are addressed by this technique. The first is the misregistration of the mask and the contrast image. The second is the temporal filtering of the DSA image sequence. Instead of treating these two issues separately, as in conventional DSA, the authors combine them into a 3-D LS prediction problem. Based on this approach they developed an efficient algorithm for the solution of normal equations. To match the image sequence physical characteristics, the authors have further optimized practical parameters of this algorithm. Actual patient data are used for the evaluation of this technique. Results show a significant improvement over the existing methods