Reduced iteration image reconstruction of incomplete projection CT using regularization strategy through Lp norm dictionary learning.

Journal: Journal of X-ray science and technology

Published Date: Jan 1, 2019

Abstract

BACKGROUND: For sparse and limited angle projection Computed Tomography (CT), the reconstructed image usually suffers from considerable artifacts due to undersampled data.

Authors

Junnian Gou

School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou, China.
Xiaoyuan Wu

School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou, China.
Haiying Dong

School of New Energy and Power Engineering, Lanzhou Jiaotong University, Lanzhou, China.

Keywords

Algorithms Artifacts Image Processing, Computer-Assisted Machine Learning Phantoms, Imaging Signal-To-Noise Ratio Tomography, X-Ray Computed

External Resources

View on PubMed Access via DOI PubMed (31177257)

Reduced iteration image reconstruction of incomplete projection CT using regularization strategy through Lp norm dictionary learning.

Abstract

Authors

Keywords

External Resources

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