ZHENG Hai-liang, LI Xing-dong, WANG Zhe, WEI Cun-feng, CHANG Tong. A Practice on Parallel Reconstruction Algorithm of High Resolution Cone Beam Micro-CT Based on NVDIA GPU Graphic Card[J]. CT Theory and Applications, 2014, 23(5): 805-814.
Citation:
ZHENG Hai-liang, LI Xing-dong, WANG Zhe, WEI Cun-feng, CHANG Tong. A Practice on Parallel Reconstruction Algorithm of High Resolution Cone Beam Micro-CT Based on NVDIA GPU Graphic Card[J]. CT Theory and Applications, 2014, 23(5): 805-814.
ZHENG Hai-liang, LI Xing-dong, WANG Zhe, WEI Cun-feng, CHANG Tong. A Practice on Parallel Reconstruction Algorithm of High Resolution Cone Beam Micro-CT Based on NVDIA GPU Graphic Card[J]. CT Theory and Applications, 2014, 23(5): 805-814.
Citation:
ZHENG Hai-liang, LI Xing-dong, WANG Zhe, WEI Cun-feng, CHANG Tong. A Practice on Parallel Reconstruction Algorithm of High Resolution Cone Beam Micro-CT Based on NVDIA GPU Graphic Card[J]. CT Theory and Applications, 2014, 23(5): 805-814.
1. Shijitian Hospital of Capital University of Medical Sciences, Beijing 100038, China;
2. National Institute of Metrology, Beijing 100013, China;
3. Key Laboratory of Nuclear Radiation and Nuclear Energy Technology, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
Objective: To explore the feasibility of parallel computing applying in high-resolution cone beam micro-CT reconstruction and its impact on reconstruction speed. Method: Allocating video memory to projection pictures and reconstruction voxels in GPU graphic card (NVIDIA QUADRO K5 000, Video Memory 4G) with parallel computing, and allocating thread to each pixel for adjusting and filtering projection picture, and then allocating thread to each voxel for Back Projection, thus, all section reconstruction is implemented in graphic card. Result: Less than 9 minutes spent for 2 048 × 2 048 × 128 pixel matrix reconstruction, which is equal to 1/3 of data gathering tirne and 2% of CPU based reconstruction, under the condition that one voxel is recorded by 32 float, and each projection picture size is 2 048 × 1 536, and 1 800 projections are gained in one scanning. Conclusion: Parallel computing applied in cone beam CT reconstruction can greatly increase reconstruction speed and data gathering can simultaneously operate with reconstruction.
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