Abstract
Computed Tomography (CT) Image Reconstruction is an important technique used in a wide range of applications, ranging from explosive detection, medical imaging to scientific imaging. Among available reconstruction methods, Model Based Iterative Reconstruction (MBIR) produces higher quality images and allows for the use of more general CT scanner geometries than is possible with more commonly used methods. The high computational cost of MBIR, however, often makes it impractical in applications for which it would otherwise be ideal. This paper describes a new MBIR implementation that significantly reduces the computational cost of MBIR while retaining its benefits. It describes a novel organization of the scanner data into super-voxels (SV) that, combined with a super-voxel buffer (SVB), dramatically increase locality and prefetching, enable parallelism across SVs and lead to an average speedup of 187 on 20 cores.
- S. Basu and Y. Bresler. O(N2 log2 N) Filtered Backprojection Reconstruction Algorithm for Tomography. IEEE Transactions on Image Processing, 9(10), 2000. Google Scholar
Digital Library
- J. E. Bowsher, M. Smith, J. Peter, and R. J. Jaszczak. A Comparison of OSEM and ICD for Iterative Reconstruction of SPECT Brain Images. Journal of Nuclear Medicine, 79(5), 1998.Google Scholar
- N. Clinthorne, T. S. Pan, P. C. Chiao, W. L. Rogers, and J. A. Stamos. Preconditioning Methods for Improved Convergence Rates in Iterative Reconstructions. IEEE Transactions on Medical Imaging, 12(1), 1993.Google Scholar
Cross Ref
- S. Degirmenci, D. G. Politte, C. Bosch, N. Tricha, and J. A. O'Sullivan. Acceleration of Iterative Image Reconstruction for X-Ray Imaging for Security Applications. In Proceedings of SPIE-IS&T Electronic Imaging, volume 9401, 2015.Google Scholar
- DHS/ALERT. Research and Development of Reconstruction Advances in CT-based Object Detection systems. https://myfiles.neu.edu/groups/ALERT/strategic_studies/TO3_FinalReport.pdf, 2009.Google Scholar
- Y. C. Eldar and G. Kutyniok. Compressed Sensing: Theory and Applications. Cambridge University Press, 2012.Google Scholar
Cross Ref
- J. Fessler. Analytical Tomographic Image Reconstruction Methods. University of Michigan-Ann Arbor, Ann Arbor, MI, 2009.Google Scholar
- J. Fessler and S. D. Booth. Conjugate-Gradient Preconditioning Methods for Shift-variant PET Image Reconstruction. IEEE Transactions on Image Processing, 8(5), 1999. Google Scholar
Digital Library
- J. A. Fessler and D. Kim. Axial Block Coordinate Descent (ABCD) Algorithm for X-ray CT Image Reconstruction. In 11th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2011.Google Scholar
- J. A. Fessler, E. Ficaro, N. Clinthorne, and K. Lange. Grouped-Coordinate Ascent Algorithms for Penalized-Likelihood Transmission Image Reconstruction. IEEE Transactions on Medical Imaging, 16(2), 1997.Google Scholar
- S. Ha and K. Mueller. An algorithm to compute independent sets of voxels for parallelization of icd-based statistical iterative reconstruction. In The 13th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2015.Google Scholar
- C. Hoilund. The Radon Transformation. http://mlsp.cs.cmu.edu/courses/fall2012/lectures/Carsten_Hoilund_Radon.pdf, 2007.Google Scholar
- P. Jin, E. Haneda, C. A. Bouman, and K. D. Sauer. A Model-based 3D Multi-slice Helical CT Reconstruction Algorithm for Transportation Security Application. In Second International Conference on Image Formation in X-Ray Computed Tomography, 2012.Google Scholar
- P. Jin, C. A. Bouman, and K. D. Sauer. A Method for Simultaneous Image Reconstruction and Beam Hardening Correction. In 2013 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), pages 1--5, 2013.Google Scholar
Cross Ref
- P. Jin, S. J. Kisner, T. Frese, and C. A. Bouman. Model-Based Iterative Reconstruction (MBIR) Software for X-ray CT. Available from https://engineering.purdue.edu/bouman/software/tomography/mbirct/, November 2013.Google Scholar
- C. Kamphuis and F. J. Beekman. Accelerated Iterative Transmission CT Reconstruction Using an Ordered Subsets Convex Algorithm. IEEE Transactions on Medical Imaging, 17(6), 1998.Google Scholar
Cross Ref
- S. J. Kisner, E. Haneda, C. A. Bouman, S. Skatter, M. Kourinny, and S. Bedford. Model-Based CT Reconstruction from Sparse Views. In Second International Conference on Image Formation in X-Ray Computed Tomography, pages 444--447, June 2012.Google Scholar
- B. D. Man, S. Basu, J.-B. Thibault, J. Hsieh, J. A. Fessler, C. A. Bouman, and K. Sauer. A Study of Different Minimization Approaches for Iterative Reconstruction in X-ray CT. In IEEE Nuclear Science Symposium, volume 5, pages 2708--2710, 2005.Google Scholar
- K. A. Mohan, S. V. Venkatakrishnan, J. W. Gibbs, E. B. Gulsoy, X. Xiao, M. D. Graef, P. W. Voorhees, and C. A. Bouman. TIMBER: A Method for Time-Space Reconstruction from Interlaced Views. IEEE Transactions on Computational Imaging, 1(2):96--111, June 2015.Google Scholar
Cross Ref
- K. Sauer and C. Bouman. A Local Update Strategy for Iterative Reconstruction from Projections. IEEE Transactions on Signal Processing, 41(2), 1993. Google Scholar
Digital Library
- J. Shewchuk. An Introduction to the Conjugate Gradient Method Without the Agonizing Pain. Carnegie Mellon University, Pittsburgh, PA, 1994.Google Scholar
- J. B. Thibault, K. D. Sauer, C. A. Bouman, and J. Hsieh. A Three-Dimensional Statistical Approach to Improved Image Quality for Multi-Slice Helical CT. Medical Physics, 34(11), 2007.Google Scholar
- X. Wang, C. A. Bouman, and S. P. Midkiff. High Performance Model Based Image Reconstruction. In 2015 ACM/IEEE Conference on Supercomputing, November 2015. URL http://sc15.supercomputing.org/sites/all/themes/SC15images/src_poster/poster_files/spost107s2-file1.pdf.Google Scholar
- X. Wang, K. A. Mohan, S. J. Kisner, C. A. Bouman, and S. P. Midkiff. Fast Voxel Line Update for Time-Space Image Reconstruction. In The 41st IEEE International Conference on Acoustics, Speech and Signal Processing, 2016.Google Scholar
- Z. Yu, J.-B. Thibault, C. Bouman, K. Sauer, and J. Hsieh. Edge-Localized Iterative Reconstruction for Computed Tomography. In 10th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2009.Google Scholar
- Z. Yu, J.-B. Thibault, C. A. Bouman, K. D. Sauer, and J. Hsieh. Fast Model-Based X-Ray CT Reconstruction Using Spatially Nonhomogeneous ICD Optimization. IEEE Transactions on Image Processing, 20(1), 2011. Google Scholar
Digital Library
- J. Zheng, S. S. Saquib, K. Sauer, and C. A. Bouman. Parallelizable Bayesian Tomography Algorithms with Rapid, Guaranteed Convergence. IEEE Transactions on Image Processing, 9(10), 2000. Google Scholar
Digital Library
Index Terms
High performance model based image reconstruction
Recommendations
Model-based Iterative CT Image Reconstruction on GPUs
PPoPP '17: Proceedings of the 22nd ACM SIGPLAN Symposium on Principles and Practice of Parallel ProgrammingComputed Tomography (CT) Image Reconstruction is an important technique used in a variety of domains, including medical imaging, electron microscopy, non-destructive testing and transportation security. Model-based Iterative Reconstruction (MBIR) using ...
High performance model based image reconstruction
PPoPP '16: Proceedings of the 21st ACM SIGPLAN Symposium on Principles and Practice of Parallel ProgrammingComputed Tomography (CT) Image Reconstruction is an important technique used in a wide range of applications, ranging from explosive detection, medical imaging to scientific imaging. Among available reconstruction methods, Model Based Iterative ...
Exterior Computed Tomography Image Reconstruction Based on Wavelet Tight Frame and ι0 Quasi-norm
ISICDM 2018: Proceedings of the 2nd International Symposium on Image Computing and Digital MedicineComputed tomography (CT) has been widely used in medical imaging and industrial Non-Destructive testing. Exterior CT was firstly used in medical imaging to reduce the motion artifacts caused by the heart beating since the CT scanning speed is very slow ...






Comments