Region-Based Automatic Regularization Parameter Tuning in CT Reconstruction

In iterative CT reconstruction, the regularization parameter is quite important because it balances the fidelity term and penalty term. Images reconstructed with the optimal regularization parameter will keep the detail preserved and the noise restrained at the same time. While in conventional CT reconstruction, the selection of the regularization parameter is very time-consuming. Besides, the fixed regularization parameter during the iterations is not suitable for every area. For example, the bone area contains more noise than soft tissue areas. With fixed regularization parameter may sacrifice the other resolution. In order to solve this question, in this paper, we proposed an automatic regularization parameter tuning strategy based on region variance. The proposed method based on the region variance tunes the regularization parameter automatically. Experiments show that the proposed method exhibits well in small detail preservation and noise reduction.