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Fast cone-beam CT image reconstruction using GPU hardware

Fast cone-beam CT image reconstruction using GPU hardware Three dimension Computed Tomography (CT) reconstruction is computationally demanding. To accelerate the speed of reconstruction, Application Specific Integrated Circuit (ASIC) or Field Programmable Gate Array (FPGA) has been used, but they are expensive, inflexible and not easy to upgrade. The modern Graphics Processing Unit (GPU) with its programmable features improves this situation and becomes one of the powerful and flexible tools for 3D CT reconstruction. In this paper, we implement Feldkamp-Davis-Kress (FDK) algorithm on commodity GPU using an acceleration scheme. In the scheme, two techniques are developed and combined. One is cyclic render-to-texture (CRTT) which saves the copy time, and the other is the combination of z-axis symmetry and multiple render targets (MRTs), which reduces the computational cost on the geometry mapping between slices to be reconstructed and projection views. Our algorithm performs reconstruction of a 512 ^{3} volume from 360 views of the size 512 × 512 about 5.2s on a single NVIDIA GeForce 8800GTX card. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of X-Ray Science and Technology IOS Press

Fast cone-beam CT image reconstruction using GPU hardware

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Publisher
IOS Press
Copyright
Copyright © 2008 by IOS Press, Inc
ISSN
0895-3996
eISSN
1095-9114
Publisher site
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Abstract

Three dimension Computed Tomography (CT) reconstruction is computationally demanding. To accelerate the speed of reconstruction, Application Specific Integrated Circuit (ASIC) or Field Programmable Gate Array (FPGA) has been used, but they are expensive, inflexible and not easy to upgrade. The modern Graphics Processing Unit (GPU) with its programmable features improves this situation and becomes one of the powerful and flexible tools for 3D CT reconstruction. In this paper, we implement Feldkamp-Davis-Kress (FDK) algorithm on commodity GPU using an acceleration scheme. In the scheme, two techniques are developed and combined. One is cyclic render-to-texture (CRTT) which saves the copy time, and the other is the combination of z-axis symmetry and multiple render targets (MRTs), which reduces the computational cost on the geometry mapping between slices to be reconstructed and projection views. Our algorithm performs reconstruction of a 512 ^{3} volume from 360 views of the size 512 × 512 about 5.2s on a single NVIDIA GeForce 8800GTX card.

Journal

Journal of X-Ray Science and Technology – IOS Press

Published: Jan 1, 2008

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