6 citations · 21 across the 11 of their papers we have counts for
12 papers
Learning Subject-Specific Anatomical Representations via Manifold Expansion: Application to Accelerated Multi-Contrast MRI
Ruimin Feng, Wanyu Bian, Albert Jang +2
Clinical MRI routinely acquires multiple contrast-weighted images of the same anatomy for complementary tissue characterization. However, current accelerated MRI methods typically…
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…
A Brief Overview of Optimization-Based Algorithms for MRI Reconstruction Using Deep Learning
Wanyu Bian
Magnetic resonance imaging (MRI) is renowned for its exceptional soft tissue contrast and high spatial resolution, making it a pivotal tool in medical imaging. The integration of d…
A Review of Electromagnetic Elimination Methods for low-field portable MRI scanner
Wanyu Bian, Panfeng Li, Mengyao Zheng +5
This paper analyzes conventional and deep learning methods for eliminating electromagnetic interference (EMI) in MRI systems. We compare traditional analytical and adaptive techniq…
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…
A Learnable Variational Model for Joint Multimodal MRI Reconstruction and Synthesis
Wanyu Bian, Qingchao Zhang, Xiaojing Ye +1
Generating multi-contrasts/modal MRI of the same anatomy enriches diagnostic information but is limited in practice due to excessive data acquisition time. In this paper, we propos…
An Optimization-Based Meta-Learning Model for MRI Reconstruction with Diverse Dataset
Wanyu Bian, Yunmei Chen, Xiaojing Ye +1
Purpose: This work aims at developing a generalizable MRI reconstruction model in the meta-learning framework. The standard benchmarks in meta-learning are challenged by learning o…
An Optimal Control Framework for Joint-channel Parallel MRI Reconstruction without Coil Sensitivities
Wanyu Bian, Yunmei Chen, Xiaojing Ye
Goal: This work aims at developing a novel calibration-free fast parallel MRI (pMRI) reconstruction method incorporate with discrete-time optimal control framework. The reconstruct…
Deep Parallel MRI Reconstruction Network Without Coil Sensitivities
Wanyu Bian, Yunmei Chen, Xiaojing Ye
We propose a novel deep neural network architecture by mapping the robust proximal gradient scheme for fast image reconstruction in parallel MRI (pMRI) with regularization function…