We propose a new method for CT reconstruction that combines penalized weighted-least squares reconstruction (PWLS) with regularization based on a sparsifying ...
LOW DOSE CT IMAGE RECONSTRUCTION WITH LEARNED SPARSIFYING TRANSFORM. Xuehang Zheng1, Zening Lu1, Saiprasad Ravishankar2, Yong Long*1, Jeffrey A. Fessler2.
Numerical experiments on the XCAT phantom show that for low dose levels, the proposed PWLS-ST method dramatically improves the quality of reconstructed ...
We propose a new method for CT reconstruction that combines penalized weighted-least squares reconstruction (PWLS) with regularization based on a sparsifying ...
We propose a new method for CT reconstruction that combines penalized weighted-least squares reconstruction (PWLS) with regularization based on a sparsifying ...
We propose a new method for CT reconstruction that combines penalized weighted-least squares reconstruction (PWLS) with regularization based on a sparsifying ...
Apr 9, 2022 · This study exploits the ability of sparse representation to learn sparse transformations of information and combines it with image decomposition theory.
[PDF] Union of Learned Sparsifying Transforms Based Low-Dose 3D ...
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Abstract—We propose a new penalized weighted-least squares. (PWLS) reconstruction method that exploits regularization based on an efficient Union of Learned ...
Aug 12, 2019 · Pre-learned square sparsifying transforms have been recently incorporated into 2D LDCT image reconstruction with both post-log Gaussian ...
This paper proposes a discriminative sparse transform iterative reconstruction algorithm inspired by the previous image compressed sensing reconstruction.