3 citations · 9 across the 5 of their papers we have counts for
5 papers
An Optimal Control Approach for Inverse Problems with Deep Learnable Regularizers
Wanyu Bian
This paper introduces an optimal control framework to address the inverse problem using a learned regularizer, with applications in image reconstruction. We build upon the concept…
Multi-task Magnetic Resonance Imaging Reconstruction using Meta-learning
Wanyu Bian, Albert Jang, Fang Liu
Using single-task deep learning methods to reconstruct Magnetic Resonance Imaging (MRI) data acquired with different imaging sequences is inherently challenging. The trained deep l…
Diffusion Modeling with Domain-conditioned Prior Guidance for Accelerated MRI and qMRI Reconstruction
Wanyu Bian, Albert Jang, Fang Liu
This study introduces a novel approach for image reconstruction based on a diffusion model conditioned on the native data domain. Our method is applied to multi-coil MRI and quanti…
Magnetic Resonance Parameter Mapping using Self-supervised Deep Learning with Model Reinforcement
Wanyu Bian, Albert Jang, Fang Liu
This paper proposes a novel self-supervised learning method, RELAX-MORE, for quantitative MRI (qMRI) reconstruction. The proposed method uses an optimization algorithm to unroll a…
Optimization-Based Deep learning methods for Magnetic Resonance Imaging Reconstruction and Synthesis
Wanyu Bian
This dissertation is devoted to provide advanced nonconvex nonsmooth variational models of (Magnetic Resonance Image) MRI reconstruction, efficient learnable image reconstruction a…