Article Article
Adaptive Discretization for Computerized Tomography

Two adaptive discretization frameworks are tested for computerized tomography (CT) data reconstruction. Removal of inactive pixels is primary motivation. Efficient and user independent entropy optimized masking is employed for spatial filtering purposes. Density of nodes at high gradient of reconstructed physical property is used as adaptation criterion. An alternative option, independent from noisy projection data and nature of the physical properties, is also discussed. Sensitivity analysis between the uniform and nonuniform (evolved via adaptive route) reconstruction grid reveals the utility of nonuniform grids. Iterative and transform based reconstruction techniques are used. Outcomes are tested successfully on three real world projection data from two different compact CT setups and one commercial high-resolution micro-CT scanner.


[1] C. Olerni, J. Jia, and M. Wang. Measurement Science and Technology. 24(3) (2013).

[2] N. Terzija, W. Yin, G. Gerbeth, F. Stefani, K. Timmel, T. Wondrak, and A. Peytona. Flow Measurement and Instrumentation 22(3): 10–16 (2011).

[3] M. E. Bruvik, T. B. Hjertaker, and A. Hallanger. Flow Measurement and Instrumentation 21(3):240–248 (2010).

[4] P. Subbarao, P. Munshi, and K. Muralidhar. NDT& E International 30(6):359–370 (1997).

[5] M. Goswami, S. Shakya, A. Saxena, P., and P. Munshi. NDT & E International 72:17–24 (2015).

[6] Z. Wéber. Physics of the Earth and Planetary Interiors 124:33–43 (2001).

[7] J. B. Ajo-Franklin, J. A. Urban, and J. M. Harris. Journal of Seismic Exploration 14:371–392 (2006).

[8] M. Goswami, S. Shakya, A. Saxena, and P. Munshi. Research in Nondestructive Evaluation 27(2):69–85 (2016).

[9] D. Xue and N. Tianye. Med. Phys. 39(10):5901–5909 (2012).

[10] M. Goswami, P. Munshi, A. Khanna, and A. Saxena. Sensors Journal, IEEE 15(2):1198–1207 (2015).

[11] J. H. Jorgensen, E. Y. Sidky, and X. Pan. IEEE Trans. Med. Imaging 32: 460–473 (2013).

[12] M. Goswami, P. Munshi, and A. Saxena. Nuclear Science and Engineering 176(2):240–253 (2014).

[13] G. Paltauf, R. Nuster, M. Haltmeier, and P. Burgholzer. Inverse Problems 23:S81 (2007). doi:10.1088/0266-5611/23/6/S07.

[14] D. L. Donoho and J. Tanner. Proceedings of the IEEE 98:913–924 (2010).

[15] F. Natterer. The Mathematics of Computerized Tomography. Wiley, New York, pp. 118 (1986).

[16] F. Scarano. Meas. Sci. Technol. 24:012001 (2013).

[17] M. Goswami, P. Munshi, A. Saxena, M. K. Gupta, and A. Kumar. FED 89(11):2659–2665 (2014).

[18] S. Roux, H. Leclerc, and F. Hild. J. Phys.: Conf. Ser. 386:012–014 (2012).

[19] M. Goswami, A. Saxena, and P. Munshi. Proceedings of 52nd Annual Conference of BINDT, NDT, Telford, U.K., Paper 4B4, pp. 1–10 (2013).

[20] H. Zhu, H. Shu, J. Zhou, X. Dai, and L. Luo. Comp. Med. Imag & Grap. 31:166–177 (2007).

[21] M. Muyazawa and M. Kato. Geophys. J. Int. 158:169–178 (2004).

[22] R. J. Michelena and J. M. Harris. Geophysics 56:635–644 (1991).

[23] A. Adler and W. R. B. Lionheart. Journal of Physics: Conference Series 224:012021 (2010).

[24] C. De Mol. In Inverse Problems in Scattering and Imaging. M. Bertero and E. R. Pike (eds.) Adam Hilger, Bristol, pp. 345–370 (1991).

[25] J. G. Daugman. J. Opt. Soc. Am. A. 2(7):1160–1169 (1985).

[26] J. Shtok, M. Elad, and M. Zibulevsky. In 2008 IEEE 25th Convention of Electrical and Electronics Engineers in Israel (IEEEI 2008). pp. 528–532 (2008).

[27] S. Shakya, P. Munshi, M. Behling, A. Luke, and D. Mewes. Int. J. Multiphase Flow 58:57-71 (2014).

[28] S. Shakya, P. Munshi, A. Luke, and D. Mewes. Research in Nondestructive Evaluation 26(2):1–58 (2015).


[29] S. Shakya and P. Munshi. Royal Society 373(2043):1–19 (2015).

Usage Shares
Total Views
105 Page Views
Total Shares
0 Tweets
0 PDF Downloads
0 Facebook Shares
Total Usage