A comparison of 3D cone-beam Computed Tomography (CT) image reconstruction performance on homogeneous multi-core processor and on other processors

Chen, Szi-Wen; Chu, Chang-Yuan

doi:10.1016/j.measurement.2011.08.012

Cited by 12 publications

References 27 publications

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Fast parallel image reconstruction for cone‐beam FDK algorithm

Zhang

Geng

Jian

2018

Concurrency and Computation

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SummaryFDK algorithm is a popular analytical reconstruction method for practical cone‐beam CT scanners. Compared with iterative methods, the FDK algorithm is computationally efficient. However, the reconstruction speed remains a limitation for its application when dealing with high resolution images. In this paper, we propose a fast method for parallel implementation of the FDK algorithm by the use of multi‐GPU. First, we optimize the backprojection operation of FDK according to the property of geometric symmetry and the correlation between adjacent slices. Then, we utilize the multi‐thread technology to realize the parallel implementation of the optimized FDK algorithm on multi‐GPU. Finally, we implement the proposed method on a multi‐GPU platform. Numerical experiment shows that the proposed multi‐GPU‐based approach can reconstruct a 512 cubed volume in 1.9 seconds from 360 projections of resolution 512 ×512, which is 511 times faster than a traditional CPU–based approach and 5 times faster than a single GPU–based approach. In addition, the reconstruction results also indicate that the proposed method can maintain the same precision with traditional method.

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