14 citations · 14 across the 4 of their papers we have counts for
4 papers · 1 filter
A Convergent Generalized Krylov Subspace Method for Compressed Sensing MRI Reconstruction with Gradient-Driven Denoisers
Tao Hong, Umberto Villa, Jeffrey A. Fessler
Model-based reconstruction plays a key role in compressed sensing (CS) MRI, as it incorporates effective image regularizers to improve the quality of reconstruction. The Plug-and-P…
Convergent Complex Quasi-Newton Proximal Methods for Gradient-Driven Denoisers in Compressed Sensing MRI Reconstruction
Tao Hong, Zhaoyi Xu, Se Young Chun +2
In compressed sensing (CS) MRI, model-based methods are pivotal to achieving accurate reconstruction. One of the main challenges in model-based methods is finding an effective prio…
Using Randomized Nyström Preconditioners to Accelerate Variational Image Reconstruction
Tao Hong, Zhaoyi Xu, Jason Hu +1
Model-based iterative reconstruction plays a key role in solving inverse problems. However, the associated minimization problems are generally large-scale, nonsmooth, and sometimes…
Provable Preconditioned Plug-and-Play Approach for Compressed Sensing MRI Reconstruction
Tao Hong, Xiaojian Xu, Jason Hu +1
Model-based methods play a key role in the reconstruction of compressed sensing (CS) MRI. Finding an effective prior to describe the statistical distribution of the image family of…