Sparse angle CT reconstruction with weighted dictionary learning algorithm based on adaptive group-sparsity regularization

CONCLUSIONS: This study demonstrates that new algorithm can better preserve structural details in reconstructed CT images. It eliminates the effect of excessive smoothing in sparse angle reconstruction, enhances the sparseness and non-local self-similarity of the image, and thus it is superior to several existing reconstruction algorithms.PMID:33843720 | DOI:10.3233/XST-210839
Source: Journal of X-Ray Science and Technology - Category: Radiology Authors: Source Type: research