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Proceedings Paper

Quantitative evaluation of ASiR image quality: an adaptive statistical iterative reconstruction technique
Author(s): Elke Van de Casteele; Paul Parizel; Jan Sijbers
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Paper Abstract

Adaptive statistical iterative reconstruction (ASiR) is a new reconstruction algorithm used in the field of medical X-ray imaging. This new reconstruction method combines the idealized system representation, as we know it from the standard Filtered Back Projection (FBP) algorithm, and the strength of iterative reconstruction by including a noise model in the reconstruction scheme. It studies how noise propagates through the reconstruction steps, feeds this model back into the loop and iteratively reduces noise in the reconstructed image without affecting spatial resolution. In this paper the effect of ASiR on the contrast to noise ratio is studied using the low contrast module of the Catphan phantom. The experiments were done on a GE LightSpeed VCT system at different voltages and currents. The results show reduced noise and increased contrast for the ASiR reconstructions compared to the standard FBP method. For the same contrast to noise ratio the images from ASiR can be obtained using 60% less current, leading to a reduction in dose of the same amount.

Paper Details

Date Published: 3 March 2012
PDF: 5 pages
Proc. SPIE 8313, Medical Imaging 2012: Physics of Medical Imaging, 83133F (3 March 2012); doi: 10.1117/12.911283
Show Author Affiliations
Elke Van de Casteele, Univ. of Antwerp (Belgium)
Paul Parizel, Univ. Hospital Antwerp (Belgium)
Jan Sijbers, Univ. of Antwerp (Belgium)


Published in SPIE Proceedings Vol. 8313:
Medical Imaging 2012: Physics of Medical Imaging
Norbert J. Pelc; Robert M. Nishikawa; Bruce R. Whiting, Editor(s)

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