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Sart-Type Half-Threshold Filtering Approach for CT Reconstruction
2014
IEEE Access
The regularization problem has been widely used to solve the sparsity constrained problems. To enhance the sparsity constraint for better imaging performance, a promising direction is to use the norm (0 < p < 1) and solve the minimization problem. Very recently, Xu et al. developed an analytic solution for the regularization via an iterative thresholding operation, which is also referred to as half-threshold filtering. In this paper, we design a simultaneous algebraic reconstruction technique
doi:10.1109/access.2014.2326165
pmid:25530928
pmcid:PMC4269945
fatcat:lzmkw2522jcjhbhzgqkzyvlvv4