The paper presents the implementation of a parallel version of FDK （Felkamp, David e Kress） algorithm using graphics processing units. Discussion was briefly some elements the computed tomographic scan and FDK algor...The paper presents the implementation of a parallel version of FDK （Felkamp, David e Kress） algorithm using graphics processing units. Discussion was briefly some elements the computed tomographic scan and FDK algorithm; and some ideas about GPUs （Graphics Processing Units） and its use in general purpose computing were presented. The paper shows a computational implementation of FDK algorithm and the process of parallelization of this implementation. Compare the parallel version of the algorithm with the sequential version, used speedup as a performance metric. To evaluate the performance of parallel version, two GPUs, GeForce 9400GT （16 cores） a low capacity GPU and Quadro 2000 （192 cores） a medium capacity GPU was reached speedup of 3.37.展开更多
Three-dimensional image reconstruction with Feldkamp,Davis,and Kress(FDK)algorithm is the most time consuming part in Micro-CT.The parallel algorithm based on the computer cluster is capable of accelerating image reco...Three-dimensional image reconstruction with Feldkamp,Davis,and Kress(FDK)algorithm is the most time consuming part in Micro-CT.The parallel algorithm based on the computer cluster is capable of accelerating image reconstruction speed;however,the hardware is very expensive.In this paper,using the most current graphics processing units(GPU),we present a method based on common unified device architecture(CUDA)for speeding up the Micro-CT image reconstruction process.The most time consuming filtering and back-projection parts of the FDK algorithm are parallelized for the CUDA architecture.The CUDA-based reconstruction speed and image qualities are compared with CPU results for the projecting data of the Micro-CT system.The results show that the 3D image reconstruction speed based on CUDA is ten times faster than the speed with CPU.In conclusion the FDK algorithm based on CUDA for Micro-CT can reconstruct the 3D image right after the end of data acquisition.展开更多
文摘The paper presents the implementation of a parallel version of FDK （Felkamp, David e Kress） algorithm using graphics processing units. Discussion was briefly some elements the computed tomographic scan and FDK algorithm; and some ideas about GPUs （Graphics Processing Units） and its use in general purpose computing were presented. The paper shows a computational implementation of FDK algorithm and the process of parallelization of this implementation. Compare the parallel version of the algorithm with the sequential version, used speedup as a performance metric. To evaluate the performance of parallel version, two GPUs, GeForce 9400GT （16 cores） a low capacity GPU and Quadro 2000 （192 cores） a medium capacity GPU was reached speedup of 3.37.
基金the financial support by National Nature Science Foundation of China(Grant No.30070261).
文摘Three-dimensional image reconstruction with Feldkamp,Davis,and Kress(FDK)algorithm is the most time consuming part in Micro-CT.The parallel algorithm based on the computer cluster is capable of accelerating image reconstruction speed;however,the hardware is very expensive.In this paper,using the most current graphics processing units(GPU),we present a method based on common unified device architecture(CUDA)for speeding up the Micro-CT image reconstruction process.The most time consuming filtering and back-projection parts of the FDK algorithm are parallelized for the CUDA architecture.The CUDA-based reconstruction speed and image qualities are compared with CPU results for the projecting data of the Micro-CT system.The results show that the 3D image reconstruction speed based on CUDA is ten times faster than the speed with CPU.In conclusion the FDK algorithm based on CUDA for Micro-CT can reconstruct the 3D image right after the end of data acquisition.
