50 citations · 91 across the 8 of their papers we have counts for
8 papers
Coordinate-Based Neural Representation Enabling Zero-Shot Learning for 3D Multiparametric Quantitative MRI
Guoyan Lao, Ruimin Feng, Haikun Qi +5
Quantitative magnetic resonance imaging (qMRI) offers tissue-specific physical parameters with significant potential for neuroscience research and clinical practice. However, lengt…
IMJENSE: Scan-specific Implicit Representation for Joint Coil Sensitivity and Image Estimation in Parallel MRI
Ruimin Feng, Qing Wu, Jie Feng +4
Parallel imaging is a commonly used technique to accelerate magnetic resonance imaging (MRI) data acquisition. Mathematically, parallel MRI reconstruction can be formulated as an i…
JSMoCo: Joint Coil Sensitivity and Motion Correction in Parallel MRI with a Self-Calibrating Score-Based Diffusion Model
Lixuan Chen, Xuanyu Tian, Jiangjie Wu +4
Magnetic Resonance Imaging (MRI) stands as a powerful modality in clinical diagnosis. However, it is known that MRI faces challenges such as long acquisition time and vulnerability…
Spatiotemporal implicit neural representation for unsupervised dynamic MRI reconstruction
Jie Feng, Ruimin Feng, Qing Wu +3
Supervised Deep-Learning (DL)-based reconstruction algorithms have shown state-of-the-art results for highly-undersampled dynamic Magnetic Resonance Imaging (MRI) reconstruction. H…
A scan-specific unsupervised method for parallel MRI reconstruction via implicit neural representation
Ruimin Feng, Qing Wu, Yuyao Zhang +1
Parallel imaging is a widely-used technique to accelerate magnetic resonance imaging (MRI). However, current methods still perform poorly in reconstructing artifact-free MRI images…
Self-Supervised Coordinate Projection Network for Sparse-View Computed Tomography
Qing Wu, Ruimin Feng, Hongjiang Wei +2
In the present work, we propose a Self-supervised COordinate Projection nEtwork (SCOPE) to reconstruct the artifacts-free CT image from a single SV sinogram by solving the inverse…
IREM: High-Resolution Magnetic Resonance (MR) Image Reconstruction via Implicit Neural Representation
Qing Wu, Yuwei Li, Lan Xu +7
For collecting high-quality high-resolution (HR) MR image, we propose a novel image reconstruction network named IREM, which is trained on multiple low-resolution (LR) MR images an…
MoDL-QSM: Model-based Deep Learning for Quantitative Susceptibility Mapping
Ruimin Feng, Jiayi Zhao, He Wang +8
Quantitative susceptibility mapping (QSM) has demonstrated great potential in quantifying tissue susceptibility in various brain diseases. However, the intrinsic ill-posed inverse…