关键词: 低剂量X-CT, Bayesian估计, Gibbs先验, 广义Gibbs先验

Abstract: In order to obtain the high quality reconstruction images for low-dose X-CT，we proposed a new generalized Gibbs prior based low-dose X-CT reconstruction method.First，X-CT projection data was modeled as a statistics process.Then based on Bayesian maximum posteriori estimation method，we designed a novel Gibbs prior named as generalized Gibbs prior，which exploited nonlocal information of the data to suppress noise.Last，we used the filtered back-projection method to finish the final CT reconstruction.The reason for the name of generalized Gibbs prior is that it has been shown to suppress noise effectively while capturing sharp edges without oscillations through the selection of larger neighborhood and adaptive weight form with global information of an image.Comparisons between the new method and other models clearly demonstrate that the proposed generalized Gibbs prior based low-dose X-CT reconstruction method performs better in lowering the noise and preserving the edge and detail in the image.

Key words: low-dose X-CT, Bayesian estimation, Gibbs prior, generalized Gibbs prior