research
∙
05/10/2022
Self-supervised regression learning using domain knowledge: Applications to improving self-supervised denoising in imaging
Regression that predicts continuous quantity is a central part of applic...
share
research
∙
05/08/2020
Learned Multi-layer Residual Sparsifying Transform Model for Low-dose CT Reconstruction
Signal models based on sparse representation have received considerable ...
research
∙
08/04/2019
BCD-Net for Low-dose CT Reconstruction: Acceleration, Convergence, and Generalization
Obtaining accurate and reliable images from low-dose computed tomography...
research
∙
06/01/2019
Multi-layer Residual Sparsifying Transform Learning for Image Reconstruction
Signal models based on sparsity, low-rank and other properties have been...
research
∙
11/02/2017
Sparse-View X-Ray CT Reconstruction Using ℓ_1 Prior with Learned Transform
A major challenge in X-ray computed tomography (CT) is reducing radiatio...
research
∙
07/10/2017
Low Dose CT Image Reconstruction With Learned Sparsifying Transform
A major challenge in computed tomography (CT) is to reduce X-ray dose to...
research
∙
03/27/2017