Compared with the conventional X-ray absorption imaging, the X-ray phase-contrast imaging shows higher contrast on samples with low attenuation coefficient like blood vessels and soft tissues. Among the modalities of ...Compared with the conventional X-ray absorption imaging, the X-ray phase-contrast imaging shows higher contrast on samples with low attenuation coefficient like blood vessels and soft tissues. Among the modalities of phase-contrast imaging, the grating-based phase contrast imaging has been widely accepted owing to the advantage of wide range of sample selections and exemption of coherent source. However, the downside is the substantially larger amount of data generated from the phase-stepping method which slows down the reconstruction process. Graphic processing unit(GPU) has the advantage of allowing parallel computing which is very useful for large quantity data processing. In this paper, a compute unified device architecture(CUDA) C program based on GPU is introduced to accelerate the phase retrieval and filtered back projection(FBP) algorithm for grating-based tomography. Depending on the size of the data, the CUDA C program shows different amount of speed-up over the standard C program on the same Visual Studio 2010 platform. Meanwhile, the speed-up ratio increases as the size of data increases.展开更多
基金the National Basic Research Program(973) of China(No.2010CB834300)the Biomedical Engineering Cross-Research Fund of Shanghai Jiao Tong University(Nos.YG2011MS49 and YG2013MS65)
文摘Compared with the conventional X-ray absorption imaging, the X-ray phase-contrast imaging shows higher contrast on samples with low attenuation coefficient like blood vessels and soft tissues. Among the modalities of phase-contrast imaging, the grating-based phase contrast imaging has been widely accepted owing to the advantage of wide range of sample selections and exemption of coherent source. However, the downside is the substantially larger amount of data generated from the phase-stepping method which slows down the reconstruction process. Graphic processing unit(GPU) has the advantage of allowing parallel computing which is very useful for large quantity data processing. In this paper, a compute unified device architecture(CUDA) C program based on GPU is introduced to accelerate the phase retrieval and filtered back projection(FBP) algorithm for grating-based tomography. Depending on the size of the data, the CUDA C program shows different amount of speed-up over the standard C program on the same Visual Studio 2010 platform. Meanwhile, the speed-up ratio increases as the size of data increases.
