CUDA and OpenCL implementations of 3D CT reconstruction for biomedical imaging

2012 IEEE Conference on High Performance Extreme Computing, HPEC 2012

Volumn , Issue , 2012, Pages

  Mukherjeet, Saoni ^a   Moore, Nicholas ^a   Brock, James ^a   Leeser, Miriam ^a  

^a Northeastern University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BACKPROJECT; BIOMEDICAL IMAGING; CONE-BEAM COMPUTED TOMOGRAPHY; CT RECONSTRUCTION; GRAPHIC PROCESSING UNITS (GPUS); HETEROGENEOUS SYSTEMS; HIGH-FIDELITY IMAGES; IMAGE ALGORITHMS; LARGE DATASETS; MATHEMATICAL PHANTOMS; PROJECTION DATA; RELATIVE PERFORMANCE; THREE-DIMENSIONAL CONSTRUCTION; TWO-DIMENSIONAL PROJECTION; WEIGHTED DATA;

IMAGE RECONSTRUCTION; MATLAB; MEDICAL IMAGING; PROGRAM PROCESSORS; THREE DIMENSIONAL;

COMPUTERIZED TOMOGRAPHY;

EID: 84873561970     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/HPEC.2012.6408674     Document Type: Conference Paper

References (17)

1. L. A. Feldkamp, L. C. Davis, J. W. Kress, Practical cone-beam algorithm, J. Opt. Soc. Am.,Volume 1(A), (1984).
2. F. Xu, K. Mueller, Real-time 3D computed tomographic reconstruction using commodity graphics hardware, Physics in Medicine and Biology, 52(12) (2007).
3. K. Mueller, F. Xu, N. Neophytou, Why do commodity graphics hardware boards (GPUs) work so well for acceleration of computed tomography?, Proceedings of the SPIE, Volume 6510, (2007).
4. K. Mueller, F. Xu, Practical consideration for GPU-accelerated CT, IEEE Int. Symp. Biomed. Imaging, (2006).
5. H. Yang, M. Li, K. Koizumi, H. Kudo, Accelerating Backprojections via CUDA Architecture, 9th International Meeting on Fully Three- Dimensional Image Reconstruction in Radiology and Nuclear Medicine, Volume 9, (2007).
6. M. Churchill, G. Pope, J. Penman, D. Riabkov, X. Xue, A. Cheryauka, Hardware-accelerated cone-beam reconstruction on a mobile C-arm, Proceedings of the SPIE, Volume 6510, (2007).
7. H. Scherl, B. Keck, M. Kowarschik, J. Hornegger, Fast gpu-based ct reconstruction using the common unified device architecture (cuda), Nuclear Science Symposium Conference Record, (2007).
8. M. Li, H. Yang, K. Koizumi, H. Kudo, Fast cone-beam CT reconstruction using CUDA architecture, Medical Imaging Technology 25(4), (2007).
9. M. Grass, T. Kohler, R. Proksa, 3D cone-beam CT reconstruction for circular trajectories, Physics in Medicine and Biology 45(2), (2000), 329347.
10. F. Ino, S. Yoshida, K. Hagihara, RGBA Packing for Fast Cone Beam Reconstruction on the GPU, Proc. of SPIE, Volume 7258, (2009).
11. P. Du, R. Weber, P. Luszczek, S. Tomov, G. Peterson, J. Dongarra, From CUDA to OpenCL: Towards a performance-portable solution for multiplatform GPU programming, September 2010.
12. NVIDIA corporation, NVIDIA CUDA C Programming Guide, CUDA Toolkit 4.1.
13. T. Ikeda, F. Ino, K. Hagihara, A code motion technique for accelerating general-purpose computation on GPU, Proc. 20th IEEE Int'l Parallel and Distributed Processing Symp., (2006).
14. Fessler's image reconstruction toolbox, http://www.eecs.umich.edu/- fessler/irt/fessler.tgz.
15. D. Yablonski, Numerical Accuracy Differences in CPU and GPGPU Codes, Masters thesis, Northeastern University.
16. https://en.wikipedia.org/wiki/AMDFireStream
17. PB Nöel, A Walczak, KR Hoffmann, J Xu, JJ Corso, S Schafer, Clinical Evaluation of GPU-Based Cone Beam Computed Tomography, Proc. of High-Performance Medical Image Computing and Computer-Aided Intervention (HP-MICCAI), (2008).