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Proceedings Paper

Novel tensor transform-based method of image reconstruction from limited-angle projection data
Author(s): Artyom M. Grigoryan; Nan Du
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Paper Abstract

The tensor representation is an effective way to reconstruct the image from a finite number of projections, especially, when projections are limited in a small range of angles. The image is considered in the image plane and reconstruction is in the Cartesian lattice. This paper introduces a new approach for calculating the splittingsignals of the tensor transform of the discrete image f(xi, yj ) from a fine number of ray-integrals of the real image f(x, y). The properties of the tensor transform allows for calculating a large part of the 2-D discrete Fourier transform in the Cartesian lattice and obtain high quality reconstructions, even when using a small range of projections, such as [0°, 30°) and down to [0°, 20°). The experimental results show that the proposed method reconstructs images more accurately than the known method of convex projections and filtered backprojection.

Paper Details

Date Published: 7 March 2014
PDF: 12 pages
Proc. SPIE 9020, Computational Imaging XII, 90200F (7 March 2014); doi: 10.1117/12.2038255
Show Author Affiliations
Artyom M. Grigoryan, The Univ. of Texas at San Antonio (United States)
Nan Du, The Univ. of Texas at San Antonio (United States)

Published in SPIE Proceedings Vol. 9020:
Computational Imaging XII
Charles A. Bouman; Ken D. Sauer, Editor(s)

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