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Computational and Mathematical Methods in Medicine
Volume 2014, Article ID 982695, 9 pages
http://dx.doi.org/10.1155/2014/982695
Research Article

3D Alternating Direction TV-Based Cone-Beam CT Reconstruction with Efficient GPU Implementation

1National Digital Switching System Engineering & Technological R&D Centre, Zhengzhou, Henan 450002, China
2Henan Province People’s Hospital, Zhengzhou 450002, China

Received 19 February 2014; Accepted 28 May 2014; Published 19 June 2014

Academic Editor: Kumar Durai

Copyright © 2014 Ailong Cai et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Iterative image reconstruction (IIR) with sparsity-exploiting methods, such as total variation (TV) minimization, claims potentially large reductions in sampling requirements. However, the computation complexity becomes a heavy burden, especially in 3D reconstruction situations. In order to improve the performance for iterative reconstruction, an efficient IIR algorithm for cone-beam computed tomography (CBCT) with GPU implementation has been proposed in this paper. In the first place, an algorithm based on alternating direction total variation using local linearization and proximity technique is proposed for CBCT reconstruction. The applied proximal technique avoids the horrible pseudoinverse computation of big matrix which makes the proposed algorithm applicable and efficient for CBCT imaging. The iteration for this algorithm is simple but convergent. The simulation and real CT data reconstruction results indicate that the proposed algorithm is both fast and accurate. The GPU implementation shows an excellent acceleration ratio of more than 100 compared with CPU computation without losing numerical accuracy. The runtime for the new 3D algorithm is about 6.8 seconds per loop with the image size of and 36 projections of the size of .