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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...
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05/08/2020
Learned Multi-layer Residual Sparsifying Transform Model for Low-dose CT Reconstruction
Signal models based on sparse representation have received considerable ...
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08/04/2019
BCD-Net for Low-dose CT Reconstruction: Acceleration, Convergence, and Generalization
Obtaining accurate and reliable images from low-dose computed tomography...
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06/01/2019
Multi-layer Residual Sparsifying Transform Learning for Image Reconstruction
Signal models based on sparsity, low-rank and other properties have been...
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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...
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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...
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03/27/2017
