Abstract
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 Tn (Toeplitz to then) 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.
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References
R.A. Kruger and S.J. Riederer,Basic Concepts of Digital Subtraction Angiography, G.K. Hall Medical Pub., 1984.
R.A. Kruger et al., Temporal Filtering Techniques for Digital Angiography,” inDigital Imaging in Cardiovascular Radiology, P.H. heintzen and R. Brennecke, eds., Stuttgart: Thieme, 1983, pp. 80–89.
J. Makhoul, “Linear Prediction: A Tutorial Review,”Proceedings of the IEEE, vol. 63, 1975, pp. 561–580.
N. Kalouptsidis, D. Manolakis, and G. Carayannis, “A Family of Computationally Efficient Algorithms for Multichannel Signal Processing—A Tutorial Review,”Signal Processing, vol. 5, 1983, pp. 5–19.
N. Kalouptsidis, D. Manolakis, and G. Carayannis, “Fast Algorithms for Block Toeplitz Matrices with Toeplitz Entries,”Signal Processing, vol. 6, 1984, pp. 77–81.
V. Digalakis, “Three Dimensional Linear Prediction and Its Application to Digital Angiography,” Master's thesis, Northeastern University, Boston, 1988.
J.H. Justice, “A Levinson-Type Algorithm for Two-Dimensional Weiner Filtering Using Bivariate Szego Polynomials,”Proceedings of the IEEE, vol. 65, 1977, pp. 882–886.
D.G. Manolakis and V.K. Ingle, “Fast Algorithms for 2-D FIR Wiener Filtering and Linear Prediction,”IEEE Transactions on Circuits and Systems, vol. CAS-34, 1987, pp. 181–187.
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Digalakis, V.V., Ingle, V.K. & Manolakis, D.G. Three-dimensional linear prediction and its application to digital angiography. Multidim Syst Sign Process 4, 307–329 (1993). https://doi.org/10.1007/BF00989649
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DOI: https://doi.org/10.1007/BF00989649