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Proceedings Paper

Cone beam filtered backprojection (CB-FBP) image reconstruction by tracking re-sampled projection data
Author(s): Xiangyang Tang; Jiang Hsieh; Roy A. Nilsen; Scott M. Mcolash
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Paper Abstract

The tomographic images reconstructed from cone beam projection data with a slice thickness larger than the nominal detector row width (namely thick image) is of practical importance in clinical CT imaging, such as neuro- and trauma- applications as well as applications for treatment planning in image guided radiation therapy. To get a balance optimization between image quality and computational efficiency, a cone beam filtered backprojection (CB-FBP) algorithm to reconstruct a thick image by tracking adaptively up-sampled cone beam projection of virtual reconstruction planes is proposed in this paper. Theoretically, a thick image is a weighted summation of a number of images with slice thickness corresponding to the nominal detector row width (namely thin image), and each thin image corresponds to a virtual reconstruction plane. To obtain the most achievable computational efficiency, the weighted summation has to be carried out in projection domain. However, it has been experimentally found that, to obtain a thick image with the reconstruction accuracy comparable to that of a thin image, the CB-FBP reconstruction algorithm has to be applied by tracking adaptively up-sampled cone beam projection data, which is the novelty of the proposed algorithm. The tracking process is carried out by making use of the cone beam projection data corresponding to the involved virtual reconstruction planes only, while the adaptive up-sampling process is implemented by interpolation along the z-direction at an adequate up-sampling rate. By using a helical body phantom, the performance of the proposed cone beam reconstruction algorithm, particularly its capability of suppressing artifacts, are experimentally evaluated and verified.

Paper Details

Date Published: 7 September 2006
PDF: 9 pages
Proc. SPIE 6318, Developments in X-Ray Tomography V, 63180P (7 September 2006); doi: 10.1117/12.681170
Show Author Affiliations
Xiangyang Tang, GE Healthcare (United States)
Jiang Hsieh, GE Healthcare (United States)
Roy A. Nilsen, GE Healthcare (United States)
Scott M. Mcolash, GE Healthcare (United States)


Published in SPIE Proceedings Vol. 6318:
Developments in X-Ray Tomography V
Ulrich Bonse, Editor(s)

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