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Proceedings Paper

Denoising medical imagery using a novel framework
Author(s): S. P. Kozaitis; J. M. Mehta; S. Ponkia
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Paper Abstract

We proposed a novel framework that allows a method optimized for white noise to be used for denoising CT imagery. We considered low-dose x-ray CT imagery where lowering the dose of x-rays results in an increase in quantum noise. We first denoised an image independently several times using different parameters. Then, we selected pixels from those denoised images to form a final composite image. We produced results using blockmatching denoising, but in principle other methods could work within this framework, as well. The proposed method was able to better reproduce regions of low-contrast than the conventional BM3D approach.

Paper Details

Date Published: 3 June 2011
PDF: 8 pages
Proc. SPIE 8058, Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering IX, 805809 (3 June 2011); doi: 10.1117/12.882896
Show Author Affiliations
S. P. Kozaitis, Florida Institute of Technology (United States)
J. M. Mehta, Florida Institute of Technology (United States)
S. Ponkia, Florida Institute of Technology (United States)


Published in SPIE Proceedings Vol. 8058:
Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering IX
Harold Szu, Editor(s)

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