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Anisotropic Total Variation Denoising Technique for Low-Dose Cone-Beam Computed Tomography Imaging
Prog. Med. Phys. 2018;29(4):150-156
Published online December 31, 2018
© 2018 Korean Society of Medical Physics.

Ho Lee*, Jeongmin Yoon, Eungman Lee

*Department of Radiation Oncology, Yonsei University College of Medicine, Department of Radiation Oncology, Seoul National University Hospital, Department of Radiation Oncology, Ewha Womans University Medical Center, Seoul, Korea
Correspondence to: Ho Lee (holee@yuhs.ac)
Tel: 82-2-2228-4363  Fax: 82-2-2227-7823
Received November 26, 2018; Revised December 17, 2018; Accepted December 18, 2018.
This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
This study aims to develop an improved Feldkamp-Davis-Kress (FDK) reconstruction algorithm using anisotropic total variation (ATV) minimization to enhance the image quality of low-dose conebeam computed tomography (CBCT). The algorithm first applies a filter that integrates the SheppLogan filter into a cosine window function on all projections for impulse noise removal. A total variation objective function with anisotropic penalty is then minimized to enhance the difference between the real structure and noise using the steepest gradient descent optimization with adaptive step sizes. The preserving parameter to adjust the separation between the noise-free and noisy areas is determined by calculating the cumulative distribution function of the gradient magnitude of the filtered image obtained by the application of the filtering operation on each projection. With these minimized ATV projections, voxel-driven backprojection is finally performed to generate the reconstructed images. The performance of the proposed algorithm was evaluated with the catphan503 phantom dataset acquired with the use of a low-dose protocol. Qualitative and quantitative analyses showed that the proposed ATV minimization provides enhanced CBCT reconstruction images compared with those generated by the conventional FDK algorithm, with a higher contrast-to-noise ratio (CNR), lower root-mean-square-error, and higher correlation. The proposed algorithm not only leads to a potential imaging dose reduction in repeated CBCT scans via lower mA levels, but also elicits high CNR values by removing noisy corrupted areas and by avoiding the heavy penalization of striking features.
Keywords : Low-dose CBCT, FDK, Anisotropic total variation, Low mAs


December 2018, 29 (4)