Fast High Resolution Algorithms for Nondestructive Evaluation Computed Tomography
Conference: Publication Date: 27 July 2015Testing Method:
The expectation-maximization (EM) algorithm is an iterative computed tomography (CT) algorithm, introduced in the 1980's for positron emission tomography (PET) [Shepp, 1982]. We developed a variant of this algorithm for nondestructive evaluation x-ray CT [Holmes, 2010, 2011, 2012]. It shows capabilities to improve image fidelity, including resolving power and contrast. A historical challenge has been processing time. We developed improvements so that processing times are approaching those of the filtered backprojection (FBP) algorithm. This is accomplished, in part, by the parallel computation using graphical processing units (GPU's). It is also due to a novel variant of the ordered subsets algorithm extensions [Hudson]. We call this novel variant the fast EM ordered subsets (FEMOS) algorithm. Resolving power is accomplished that shows details not seen by FBP and exceeds the standard pixel resolution.
- ASTM E2597, Standard Practice for Manufacturing Characterization of Digital Detector Arrays, 2013.
- Browne, J., Holmes, T., Developments with Maximum Likelihood X-ray Computed Tomography, IEEE Transactions on Medical Imaging, 11(1): 40-52, 1992.
- Browne, J., Holmes, T., Developments with Maximum Likelihood X-ray Computed Tomography: Initial Testing with Real Data, Applied Optics, 33(14) 1994.
- Browne, J., Holmes, T., Maximum Likelihood Algorithm Techniques in X-Ray Computed Tomography, Ch. 3: Medical Imaging Systems Techniques and Applications, C.T. Leondes, Editor, Gordon and Breach, 1997.
- Cheng, P., Snyder, D., O’Sullivan, J., Wang, G., Vannier, M., Iterative Process for Reconstructing Cone-Beam Tomographic Images, U.S. Patent 5,909,476, 1999.
- Feldkamp, L, Davis, L., Kress, J., Practical Cone- Beam Algorithm, JOSA, 1: 612-619, 1984.
- Gaskill, J., Linear Systems, Fourier Transforms and Optics, Wiley, 1978.
- Holmes, T., Maximum-Likelihood Image Restoration Adapted for Noncoherent Optical Imaging, Journal of the Optical Society of America A, 5(5):666-673, 1988.
- Holmes, T., Liu, Y., Acceleration of Maximum-Likelihood Image Restoration for Fluorescence Microscopy and Other Noncoherent Imagery, JOSA A, 8(6):893-907, 1991.
- Holmes, T., Beecher, D., Larkin, S., Trobaugh, J., Wickham, D., Computed Tomography Iterative EM Algorithm Adapted for Solid Rocket Motor Inspection, JANNAF, Orlando, Florida, 6-10 December 2010.
- Holmes, T., Beecher, D., Larkin, S., Trobaugh, J., Wickham, D., Computed Tomography Iterative EM Algorithm Adapted for Nondestructive Evaluation, ASNT Annual Meeting, Palm Springs CA, Oct. 2011.
- Holmes, T., Larkin, S., Miller, C., Myers, J., Wickham, D., Computer Tomography Processing for Non-routine Inspection of Solid Rocket Motor Defects, National Space and Missile Materials Symposium, Tampa, 2012.
- Hudson, H., et al, Accelerated image reconstruction using ordered subsets of projection data, IEEE TMI, 13: 1994.
- IAEA Report, Industrial Process Gamma Tomography, IAEA-TECDOC-1589, 2008.
- Inoue', S., Spring, K., Video Microscopy: the Fundamentals, 2nd Ed., Springer, 2012.
- Kak, A., Principles of Computerized Tomographic Imaging, SIAM, 2001.
- Munshi, A., Gaster, B., Mattson, T., Fung, J., OpenCL Programming Guide, Addison-Wesley, 2011.
- O'Sullivan, J., et al, Alternating minimization algorithms for transmission tomography, IEEE TMI, 26(3): 2007.
- Owens, J., Luebke, D., Govindaraju, N., Harris, M., Krüger, J., Lefohn, A., Purcell, T., A Survey of General- Purpose Computation on Graphics Hardware, Eurographics 2005, State of the Art Reports, 21-51, 2005.
- Shepp, L., Vardi, Y., Maximum Likelihood Reconstruction for Emission Tomography, IEEE TMI, 2: 1982.
- Snyder, D., Miller, M., Thomas, L., Politte, D. Noise and edge artifacts in maximum-likelihood reconstructions for emission tomography. IEEE Transactions on Medical Imaging, 6(3):228-238, 1987.
- Snyder, D., Miller, M., Random Point Processes in Time and Space, 2nd Ed., Springer-Verlag, 1991.
- Tang, X., Hsieh, J., Nilsen, R., Dutta, S., Samsonov, D., Hagiwara, A., A three-dimensional-weighted cone beam filtered backprojection (CB-FBP) algorithm for image reconstruction in volumetric CT-helical scanning, Phys Med Biol. Feb 21;51(4):855-874, 2006 .
- Zhao, Y., Zou, X.Yu, W., Iterative reconstruction algorithm for half-cover dual helical cone-beam computed tomography, Insight - Non-Destructive Testing and Condition Monitoring, 55(5):232-236, 2013.
103 Page Views
0 PDF Downloads
0 Facebook Shares