The statistical sinogram smoothing via adaptive-weighted total variation regularization for low-dose X-ray CT-Reference-Cited by-同舟云学术

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The statistical sinogram smoothing via adaptive-weighted total variation regularization for low-dose X-ray CT

Published:2014-09 Issue:18 Volume:125 Page:5352-5356
ISSN:0030-4026
Container-title:Optik
language:en
Short-container-title:Optik

Author:

Cui Xueying,Gui Zhiguo,Zhang Quan,Liu Yi,Ma Ruifen

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials

Reference19 articles.

1. Estimated risks of radiation-induced fatal cancer from pediatric CT;Brenner;Am. J. Roentgenol.,2001

2. Risk of cancer from diagnostic X-rays: estimates for the UK and 14 other countries;de Gonzalez;Lancet,2004

3. Computed tomography-an increasing source of radiation exposure;Brenner;New Engl. J. Med.,2007

4. Noise properties of low-dose CT projections and noise treatment by scale transformations;Lu;Proc. IEEE NSS-MIC Conf. Rec.,2001

5. Reduction of noise and image artifacts in computed tomography by nonlinear filtration of the projection images;Demirkaya;Proc. SPIE Med. Imaging,2001

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1. LDCT image denoising algorithm based on two-dimensional variational mode decomposition and dictionary learning;Scientific Reports;2024-07-30

2. Semi-supervised iterative adaptive network for low-dose CT sinogram recovery;Physics in Medicine & Biology;2024-04-03

3. LDCT image denoising algorithm based on two-dimensional variational mode decomposition and dictionary learning;2024-01-01

4. Projection domain processing for low-dose CT reconstruction based on subspace identification;Journal of X-Ray Science and Technology;2023-01-27

5. A Dual-Channel Network Based GAN for Low-Dose CT Image Denoising;2022 China Automation Congress (CAC);2022-11-25

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