上海交通大学学报(英文版) ›› 2014, Vol. 19 ›› Issue (5): 550-554.doi: 10.1007/s12204-014-1539-x

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Graphic Processing Unit Based Phase Retrieval and CT Reconstruction for Differential X-Ray Phase Contrast Imaging

CHEN Xiao-qinga (陈晓庆), WANG Yu-jieb (王宇杰), SUN Jian-qia*(孙建奇)   

  1. (a. School of Biomedical Engineering; b. Department of Physics and Astronomy, Shanghai Jiaotong University, Shanghai 200240, China)
  • 出版日期:2014-10-31 发布日期:2014-11-12
  • 通讯作者: SUN Jian-qi(孙建奇) E-mail:milesun@sjtu.edu.cn

Graphic Processing Unit Based Phase Retrieval and CT Reconstruction for Differential X-Ray Phase Contrast Imaging

CHEN Xiao-qinga (陈晓庆), WANG Yu-jieb (王宇杰), SUN Jian-qia*(孙建奇)   

  1. (a. School of Biomedical Engineering; b. Department of Physics and Astronomy, Shanghai Jiaotong University, Shanghai 200240, China)
  • Online:2014-10-31 Published:2014-11-12
  • Contact: SUN Jian-qi(孙建奇) E-mail:milesun@sjtu.edu.cn

摘要: 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.

关键词: grating-based phase contrast imaging, parallel computing, graphic processing unit (GPU), compute unified device architecture (CUDA), filtered back projection (FBP)

Abstract: 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.

Key words: grating-based phase contrast imaging, parallel computing, graphic processing unit (GPU), compute unified device architecture (CUDA), filtered back projection (FBP)

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