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SIAM J. on Scientific Computing / Volume 31 / Issue 6

SIAM J. Sci. Comput. 31, pp. 4204-4221 (18 pages)

GPU-Based Volume Reconstruction from Very Few Arbitrarily Aligned X-Ray Images

Daniel Gross, Ulrich Heil, Ralf Schulze, Elmar Schoemer, and Ulrich Schwanecke

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This paper presents a three-dimensional GPU-accelerated algebraic reconstruction method in a few-projection cone-beam setting with arbitrary acquisition geometry. To achieve artifact-reduced reconstructions in the challenging case of unconstrained geometry and extremely limited input data, we use linear methods and an artifact-avoiding projection algorithm to provide high reconstruction quality. We apply the conjugate gradient method in the linear case of Tikhonov regularization and the two-point-step-size gradient method in the nonlinear case of total variation regularization to solve the system of equations. By taking advantage of modern graphics hardware we achieve acceleration of up to two orders of magnitude over classical CPU implementations.

© 2009 Society for Industrial and Applied Mathematics

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KEYWORDS

AMS Subject Headings

92C55, 65F22, 92C50, 65R32, 65N21

PUBLICATION DATA

ISSN

1064-8275 (print)  
1095-7197 (online)

Publisher

$abstract.society.value is a Member of CrossRef Society for Industrial and Applied Mathematics

ARTICLE DATA

History
Received September 23, 2008
Accepted July 13, 2009
Published online November 25, 2009
Digital Object Identifier
http://dx.doi.org/10.1137/080736739

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