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纸质出版日期:2011,
网络出版日期:2010-7-25,
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张元科,张军英,卢虹冰.基于MCMC方法的自适应低剂量CT图像去噪[J].工程科学与技术,2011,43(3):96-103.
Adaptive Noise Reduction of Low-dose CT Sinograms Based on MCMC Method[J]. Advanced Engineering Sciences, 2011,43(3):96-103.
中文摘要: 针对低剂量CT图像的低信噪比的问题,提出了一种新的基于MCMC方法的低剂量CT投影图像的自适应降噪算法。该算法是在对投影图像先验模型中的平滑参数以及噪声方差进行自适应估计的基础上,求解理想投影图像在观察投影图像条件下的期望值,以此期望值作为理想投影图像的估计值,从而达到图像降噪的目的。其中对先验概率模型中的平滑参数以及非平稳噪声的方差在运用EM算法进行估计过程中,引入MCMC技术中的Gibbs采样,很好解决了参数估计中的计算问题,并在此基础上,通过再一次运用MCMC的Gibbs采样,以获得理想数据的条件期望值。计算机仿真实验以及真实投影图像的实验均表明了本文所提出的算法在低剂量CT图像降噪中能够取得良好的效果。
Abstract:In order to improve the SNR of low-dose CT image
a novel adaptive noise reduction algorithm for low-dose CT sinogram was proposed based on the MCMC method. The algorithm adaptively estimated the smoothness parameter of the priori model and the noise variance
and then utilized the conditional expectation of the noisy sinogram as the restored sinogram. The parameters were estimated by an EM algorithm and in this procedure a Gibbs sampler was used to draw samples from the local posterior distribution to handle the complicated computation problem
and then the Gibbs sampler was used once again to compute the conditional expectation of the noisy sinogram. The effectiveness of the proposed algorithm was validated by both computer simulations and experimental studies. The gain of the proposed approach over other methods was quantified by noise-resolution tradeoff curves.
低剂量CT图像降噪参数估计MCMC算法EM算法
low-dose X-ray CTnoise reductionparameter estimationMCMC algorithmEM algorithm
La Riviere, P.J. ;Billmire, D.M.,Reduction of noise-induced streak artifacts in X-ray computed tomography through spline-based penalized-likelihood sinogram smoothing,IEEE Transactions on Medical Imaging ,2005, 24(1).
I.A.Elbakri;J.A.Fessler,Statistical image reconstruction for polyenergetic x-ray computed tomography,IEEE Transactions on Medical Imaging
Sauer, K. ;Bouman, C.,A local update strategy for iterative reconstruction from projections,IEEE Transactions on Signal Processing ,1993, 41(2).
Lange K;Carson R,EM reconstruction algorithms for emission and transmission tomography,Journal of Computer Assisted Tomography,1984.
Ramirez Giraldo J C;Kelm Z S,Comparative study of two image space noise reduction methods for computed tomography:bilateral filter and nonlocal means,2009.
S.German;D.German,Tochastic relaxation,Gibbs distribution and the Bayesian restoration in imsges,IEEE Transactions on Pattern Analysis and Machine Intelligence
Lei, T. ;Sewchand, W.,Statistical approach to X-ray CT imaging and its applications in image analysis. I. Statistical analysis of X-ray CT imaging,IEEE Transactions on Medical Imaging ,1992, 11(1).
王东明,卢虹冰,张军英.基于统计特性的小波噪声抑制在低剂量CT中的应用[J].中国图象图形学报,2008(5)
Wang Jing;Lu Hongbing;Wen J,Multiscale penalized weighted least-squares sinogram restoration for low-dose X-Ray computed tomography,IEEE Transactions on Biomedical Engineering,2008(3).
Jing Wang ;Tianfang Li ;Hongbing Lu ;Zhengrong Liang,Penalized weighted least-squares approach to sinogram noise reduction and image reconstruction for low-dose X-ray computed tomography,IEEE Transactions on Medical Imaging ,2006, 25(10).
Tabuchi M;Yamame N;Morikawa Y,Adaptive Wiener filter based on Gaussian Mixture Model for denoising chest X Ray CT image,Nippon Hoshasen Gijutsu Gakkai Zasshi,2008(5).
Lu Hongbing;Hsiao I;Li X,Noise properties of lowdose CT projections and noise treatment by scale transformations,2001.
Wang, G.-C. ;Huber, J.S. ;Moses, W.W. ;Qi, J. ;Choong, W.-S.,Characterization of the LBNL PEM camera,IEEE Transactions on Nuclear Science ,2006, 53(3).
Li S Z,Markov random field modeling in image analysis,Springer-verlag,2009.
J Hsieh,Adaptive streak artifacts reduction in computed tomography resulting from excessive x-ray photon noise,Medical Physics
Perez P,Markov random fields and images,CWI Quarterly,1998(4).
Dempster A P;Laird N M;Rubin D B,Maximum likelihood from incomplete data via the E -M algorithm,Journal of the Royal Statistical Society,Series B:Statistical Methodology,1977.
Saquib, S.S. ;Bouman, C.A.,ML parameter estimation for Markov random fields with applications to Bayesian tomography,IEEE Transactions on Image Processing ,1998, 7(7).
Li T;Li X;Wang J,Nonlinear sinogram smoothing for low-dose X-ray CT,IEEE Transactions on Nuclear Science,2004(5).
La Riviere, P.J. ;Bian, J. ;Vargas, P.A.,Penalized-Likelihood Sinogram Restoration for Computed Tomography,IEEE Transactions on Medical Imaging ,2006, 25(8).
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