Regression that predicts continuous quantity is a central part of
applic...
The recently proposed sparsifying transform models incur low computation...
Dual-energy computed tomography (DECT) has been widely used in many
appl...
Achieving high-quality reconstructions from low-dose computed tomography...
Signal models based on sparse representations have received considerable...
Signal models based on sparse representation have received considerable
...
This paper applies the recent fast iterative neural network framework,
M...
Recent years have witnessed growing interest in machine learning-based m...
Obtaining accurate and reliable images from low-dose computed tomography...
Signal models based on sparsity, low-rank and other properties have been...
Dual energy computed tomography (DECT) imaging plays an important role i...
A major challenge in X-ray computed tomography (CT) is reducing radiatio...
A major challenge in computed tomography (CT) is to reduce X-ray dose to...
The development of computed tomography (CT) image reconstruction methods...