Performance of iterative tomographic algorithms applied to non-destructive evaluation with limited data

NDT and E International

Volumn 30, Issue 6, 1997, Pages 359-370

  Subbarao, P M V ^a   Munshi, P ^a   Muralidhar, K ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY KANPUR   (India)

Author keywords

Absorption; Convergence rates; Errors; Iterative algorithms; Sensitivity to noise; Tomography

Indexed keywords

ABSORPTION; ALGORITHMS; CONVERGENCE OF NUMERICAL METHODS; ITERATIVE METHODS; NONDESTRUCTIVE EXAMINATION; RELAXATION PROCESSES;

ITERATIVE TOMOGRAPHIC ALGORITHMS; MAXIMIZATION RECONSTRUCTION TECHNIQUE (MRT); MULTIPLICATIVE ALGEBRAIC RECONSTRUCTION TECHNIQUE (MART);

IMAGE RECONSTRUCTION;

EID: 0031355307     PISSN: 09638695     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0963-8695(97)00005-4     Document Type: Article

References (16)

1. Gordon, R., Bender, R. and Herman, G.T., Algebraic reconstruction techniques (ART) for three-dimensional electron microscopy and X-ray photography. J. Theor. Biol., 1970, 29, 471-481.
2. Verhoeven, D., Multiplicative algebraic computed tomographic algorithms for the reconstruction of multidirectional interferometric data. Opt. Eng. , 1993, 32, 410-419.
3. Minerbo, G., MENT: a maximum entropy algorithm for reconstructing a source from projection data. Computer Graphics Image Processing, 1979, 10, 48-68.
4. Censor, Y., Finite series-expansion reconstruction methods. Proc. IEEE, 1983, 71, 409-419.
5. Gull, S.F. and Newton, T.J., Maximum entropy tomography. Appl. Opt. , 1986, 25, 156-160.
6. Herman, G.T., Mathematical optimization versus practical performance: a case study based on the maximum entropy criterion in image reconstruction. Math. Prog. Study, 1981, 20, 96-112.
7. Myers, K.J. and Hanson, K.M., Comparison of the algebraic reconstruction technique with maximum entropy reconstruction technique for a variety of detection tasks. Medical Imaging IV: Image Formation, 1990, 1231, 176-186.
8. Reis, M.L. and Roberty, N.C., Maximum entropy algorithms for image reconstruction from projections. Inverse Problems, 1992, 8, 623-644.
9. Natterer, F., The Mathematics of Computerized Tomography, Wiley, Chichester, UK, 1986.
10. Bracewell, R.N., Strip integration in radio astronomy. Aust. J. Phys. , 1965, 9, 198-217.
11. Herman, G.T., Image from Projections, Academic Press, New York, 1980.
12. Munshi, P., Error analysis of tomographic filters I: theory. NDT & E. Int., 1992, 25, 191-194.
13. Subbarao, P.M.V. and Muralidhar, K., Noise removal, three dimensional reconstruction and data retrieval for optical images of stratified fluids, Report, Department of Science and Technology, Government of India, 1996.
14. Mayinger, F., Optical Measurements, Springer-Verlag, New York, 1994.
15. Gilbert, P.F.C., Iterative methods for three-dimensional reconstruction of an object from its projections. J. Theo. Biol., 1972, 36, 105-117.
16. Anderson, A.H. and Kak, A.C., Simultaneous algebraic reconstruction technique (SART): a superior implementation of the ART algorithm. Ultrason. Imaging, 1984, 6.