Denoising medical imagery using a novel framework

S. P. Kozaitis; J. M. Mehta; S. Ponkia

doi:10.1117/12.882896

3 June 2011 Denoising medical imagery using a novel framework

S. P. Kozaitis, J. M. Mehta, S. Ponkia

Proceedings Volume 8058, Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering IX; 805809 (2011) https://doi.org/10.1117/12.882896
Event: SPIE Defense, Security, and Sensing, 2011, Orlando, Florida, United States

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.

Citation Download Citation

S. P. Kozaitis, J. M. Mehta, and S. Ponkia "Denoising medical imagery using a novel framework", Proc. SPIE 8058, Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering IX, 805809 (3 June 2011); https://doi.org/10.1117/12.882896

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