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

doi:10.1007/s12204-014-1539-x

Abstract

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)

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)

CLC Number:

R 318.6

CHEN Xiao-qinga (陈晓庆), WANG Yu-jieb (王宇杰), SUN Jian-qia*(孙建奇). Graphic Processing Unit Based Phase Retrieval and CT Reconstruction for Differential X-Ray Phase Contrast Imaging[J]. Journal of shanghai Jiaotong University (Science), 2014, 19(5): 550-554.

References

[1] Jerjen I, Revol V, Kottler C, et al. Phase contrast cone beam tomography with an X-ray grating interferometer [C]//American Institute of Physics Conference Proceedings. New York, USA: American Institute of Physics, 2010: 227-231.
[2] Nvidia C, Cuda C. Programming guide [M]. Santa Clara, USA: NVIDIA Corporation Cuda Toolkit, 2014.
[3] Scherl H, Keck B, Kowarschik M, et al. Fast GPU-based CT reconstruction using the common unified device architecture (CUDA) [C]//Nuclear Science Symposium Conference Record. Hawaii, USA: IEEE.2007: 4464-4466.
[4] Mukherjeet S, Moore N, Brock J, et al. CUDA and OpenCL implementations of 3D CT reconstruction for biomedical imaging [C]//IEEE Conference on High Performance Extreme Computing (HPEC). Massachusetts,USA: IEEE, 2012: 1-6.
[5] Nvidia C. C programming best practices guide [M].USA: NVIDIA Corporation Cuda Toolkit, 2014.
[6] Pfeiffer F, Weitkamp T, Bunk O, et al. Phase retrieval and differential phase-contrast imaging with low-brilliance X-ray sources [J]. Nature Physics, 2006,2(4): 258-261.
[7] Zanette I, Weitkamp T, Donath T, et al. Twodimensional x-ray grating interferometer [J]. Physical Review Letters, 2010, 105(24): 248102-1-248102-4.
[8] Araiza-Esquivel M A, Martinez-Leon L, Javidi B, et al. Single-shot color digital holography based on the fractional Talbot effect [J]. Applied Optics, 2011.50(7): B96-B101.
[9] Weitkamp T, Diaz A, David C, et al. X-ray phase imaging with a grating interferometer [J]. Optics Express,2005, 13(16): 6296-6304.
[10] Takeda M, Ina H, Kobayashi S. Fourier-transform method of fringe-pattern analysis for computer-based topography and interferometry [J]. Journal of the Optical Society of America, 1982, 72(1): 156-160.
[11] Zhu P, Zhang K, Wang Z, et al. Low-dose, simple,and fast grating-based X-ray phase-contrast imaging[J]. Proceedings of the National Academy of Sciences,2010, 107(31): 13576-13581.
[12] Bech M. X-ray imaging with a grating interferometer[D]. Copenhagen, Denmark: Niels Bohr Institute,University of Copenhagen, 2009.
[13] Bech M, Jensen T H, Bunk O, et al. Advanced contrast modalities for X-ray radiology: Phase-contrast and dark-field imaging using a grating interferometer[J]. Journal of Medical Physics, 2010, 20(1): 7-16.
[14] Zhuang T. The principle and algorithm of CT [M]. Shanghai, China: Shanghai Jiao Tong University Press, 1992 (in Chinese).