In this paper, a low-dose CT denoising method based on
regularization method of Markov chain Monte Carlo is studied. Firstly, the mathematical model and regularization method of low-dose CT denoising are summarized, and then the theoretical basis of MCMC method and its application in image denoising are introduced. We evaluated the performance of various regularization strategies by comparing the denoising effects of
,
, and
regularization terms in MCMC sampling at Gaussian noise levels. The experimental results show that
regularization has the best performance in balancing noise removal and image detail retention, significantly superior to single
and
regularization, which proves its effectiveness for low-dose CT denoising.
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