We describe a parallel structured algorithm that suppresses motion artifacts in coronary digital subtraction angiography (DSA). DSA involves the subtraction of a "mask" -- an image of the heart before injection of contrast medium -- from a "live" image. The mask and live images are x-ray images of the heart before and after, respectively, the injection of contrast medium. Although the two images are at the same or nearly the same phase of the cardiac cycle, physical changes occurring in the interim between the acquisition of the images produce several artifacts and distortions. Among these artifacts and distortions are mean gray-level shift, rotation, translation and nonisotropic scaling. The artifacts and distortions are spatially and temporally varying. In our algorithm each image is partitioned into an array of rectangular segments. Each segment is first matched to the mask, then transformations of rotation, translation and nonisotropic scaling are carried out iteratively, converging to the best match in the least squares sense. This algorithm, we believe, is an improvement over earlier methods, because it is fully automatic, it overcomes nonisotropic scaling artifacts, it gives a good correction for gray level variations, and it offers a matching accuracy of 0.1 pixel or better. Experimental results on both phantoms and real images are presented.

Date Published: 18 July 1988
PDF: 9 pages
Proc. SPIE 0939, Hybrid Image and Signal Processing, (18 July 1988); doi: 10.1117/12.947063

Published in SPIE Proceedings Vol. 0939:
Hybrid Image and Signal Processing
David P. Casasent; Andrew G. Tescher, Editor(s)