Bi-Dimensional Zero Padding Angular Interpolation for Arc Handling in Computed Tomography Scanner


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Abstract


In this work we examine the accuracy of our proposed interpolation algorithm by zero-padding comparing to standard techniques for the task of interpolating additional projections to be insert in sinogram witch lost some projections caused by an X-ray tube arcing in computed tomography scanners. During the time that the X-ray tube recovers to full voltage after an arc, image data is not collected and data projections are lost caused poor image quality in the tomography reconstruction process. We have developed an algorithm based on an estimated calculation of a virtual projection using the zero-padding interpolation. The results show a significant reduction of the star effect noise on the reconstructed image. Our algorithm was compared to simple interpolation linear method using statistical hypothesis testing .Our test simulation was experimented with a R × R (R number of pixels in row and column) value phantom simulating the human body while the programming is carried out in MATLAB 6.5.
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Keywords


Filtered Back Projection; Computed Tomography; Zero Padding; linear interpolation; Radon Projection Estimations

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References


A. C. Kak and M. Slaney, Principles of Computerized Tomographic Imaging. New York: IEEE Press, 1988.

Watzke O, Kalendar WA, A pragmatic approach to metal artifact reduction in CT, merging of metal artifact reduced images. Eur J Radiol Vol.14,5,pp.849–56,2004.

J. H. Siewerdsen et al., Volume CT with a flat-panel detector on a mobile, isocentric C-arm: Pre-clinical investigation in guidance of minimally invasive surgery, Med. Phy., vol. 32, n. 1, pp. 241–254, 2005.

M. Bertram, J. Wiegert, D. Schafer, T. Aach and G. Rose, Directional View Interpolation for Compensation of Sparse Angular Sampling in Cone-Beam CT, IEEE Transactions on Medical Imaging 28(7), pp. 1011-1022,2009.

Honda T, Taguchi W. X-ray, computed tomography apparatus. US Patent 64,49, 337, 2002.

Kalender WA. Computed tomography, fundamentals, system technology, image quality, applications. 2nd revised edition Publicis Corporate Publishing; 2005.

Harris CH. Road to RSNA 2008: CT Preview, Auntminnie.com; 29 October 2008.

Patrick J. La Riviere and Xiaochuan Pan, Comparison of angular interpolation approaches in few-view tomography using statistical hypothesis testing, SPIE, Vol,3661, pp, 398–407,1999.

G. J. Grevera and J. K. Udupa, An objective comparison of 3-D image interpolation methods,IEEE Trans. Med. Imag, vol. 17, no. 4, pp. 642–652, 1998.

J. Hladuvka and E. Gröller, Direction-driven shape-based interpolation of volume data, in Proc. Vis., Model., Visualizat, pp.113–120, 2001.

J. Rajwadea, L. Millerb, D.Simonc, ‘Partial-data interpolation method for arc handling in a computed tomography scanner’, Computerized Medical Imaging and Graphics Vol, 36,pp, 387– 395, 2012.

M. Li, H. Yang, H. Kudo, An accurate iterative reconstruction Algorithm for sparse objects: Application to 3-D blood vessel reconstruction from a limited number of projections, Phys. Med. Biol, Vol.47, pp. 2599–2609, 2002.

Sabri, A., Senhaji, S., Aarab, A., Accelerating the BEMD by reducing the number of extrema points to interpolate in the SP, (2011) International Review on Computers and Software (IRECOS), 6 (2), pp. 264-268.

O. Debeir, P. Dunham, L. Engels, T. Leloup, X. Baele, N. Warzée, High Resolution 3D Acquisition of the Olivier Strebelle's Sculpture, (2007) International Review on Computers and Software (IRECOS), 2 (5), pp. 541 -545.


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