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Multi GPU Implementation of Iterative Tomographic Reconstruction Algorithms

Byunghyun Jang, David R. Kaeli, Synho Do, Homer Pien
Northeastern University, Department of ECE, Boston, MA U.S.A.
IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2009. ISBI ’09. p.185-188

@conference{jang2009multi,

   title={Multi GPU implementation of iterative tomographic reconstruction algorithms},

   author={Jang, B. and Kaeli, D. and Do, S. and Pien, H.},

   booktitle={Biomedical Imaging: From Nano to Macro, 2009. ISBI’09. IEEE International Symposium on},

   pages={185–188},

   issn={1945-7928},

   year={2009},

   organization={IEEE}

}

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Although iterative reconstruction techniques (IRTs) have been shown to produce images of superior quality over conventional filtered back projection (FBP) based algorithms, the use of IRT in a clinical setting has been hampered by the significant computational demands of these algorithms. In this paper we present results of our efforts to overcome this hurdle by exploiting the combined computational power of multiple graphical processing units (GPUs). We have implemented forward and backward projection steps of reconstruction on an NVIDIA Tesla S870 hardware using CUDA. We have been able to accelerate forward projection by 71x and backward projection by 137x. We generate these results with no perceptible difference in image quality between the GPU and serial CPU implementations. This work illustrates the power of using commercial off-the-shelf relatively low-cost GPUs, potentially allowing IRT tomographic image reconstruction to be run in near real time, lowering the barrier to entry of IRT, and enabling deployment in the clinic.
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