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Proceedings Paper

Low signal correction scheme for low dose CBCT: the good, the bad, and the ugly
Author(s): Daniel Gomez-Cardona; John Hayes; Ran Zhang; Ke Li; Juan Pablo Cruz-Bastida; Guang-Hong Chen
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Paper Abstract

Reducing radiation dose in C-arm Cone-beam CT (CBCT) image-guided interventional procedures is of great importance. However, reducing radiation dose may increase noise magnitude and generate noise streaks in the reconstructed image. Several approaches, ranging from simple to highly complex methods, have been proposed in an attempt to reduce noise and mitigate artifacts caused by low detector counts. These approaches include apodizing the ramp kernel used before backprojection, using an adaptive trimmed mean filter based on local flux information, employing penalized-likelihood approaches or edge-preserving filters for sinogram smoothing, incorporating statistical models into the so-called model based iterative reconstruction framework, and more. This work presents a simple yet powerful scheme for low signal correction in low dose CBCT by applying local anisotropic diffusion filtration to the raw detector data prior to the logarithmic transform. It was found that low signal correction efficiently reduced noise magnitude and noise streaks without considerably sacrificing spatial resolution. Yet caution must be taken when selecting the parameters used for low signal correction so that no spurious information is enhanced and noise streaks are effectively reduced.

Paper Details

Date Published: 9 March 2017
PDF: 7 pages
Proc. SPIE 10132, Medical Imaging 2017: Physics of Medical Imaging, 101320Z (9 March 2017); doi: 10.1117/12.2255531
Show Author Affiliations
Daniel Gomez-Cardona, Univ. of Wisconsin School of Medicine and Public Health (United States)
John Hayes, Univ. of Wisconsin School of Medicine and Public Health (United States)
Ran Zhang, Univ. of Wisconsin School of Medicine and Public Health (United States)
Ke Li, Univ. of Wisconsin School of Medicine and Public Health (United States)
Juan Pablo Cruz-Bastida, Univ. of Wisconsin School of Medicine and Public Health (United States)
Guang-Hong Chen, Univ. of Wisconsin School of Medicine and Public Health (United States)


Published in SPIE Proceedings Vol. 10132:
Medical Imaging 2017: Physics of Medical Imaging
Thomas G. Flohr; Joseph Y. Lo; Taly Gilat Schmidt, Editor(s)

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