7 citations · 14 across the 6 of their papers we have counts for
7 papers
Joint Rigid Motion Correction and Sparse-View CT via Self-Calibrating Neural Field
Qing Wu, Xin Li, Hongjiang Wei +2
Neural Radiance Field (NeRF) has widely received attention in Sparse-View Computed Tomography (SVCT) reconstruction tasks as a self-supervised deep learning framework. NeRF-based S…
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…
Continuous longitudinal fetus brain atlas construction via implicit neural representation
Lixuan Chen, Jiangjie Wu, Qing Wu +2
Longitudinal fetal brain atlas is a powerful tool for understanding and characterizing the complex process of fetus brain development. Existing fetus brain atlases are typically co…
Noise2SR: Learning to Denoise from Super-Resolved Single Noisy Fluorescence Image
Xuanyu Tian, Qing Wu, Hongjiang Wei +1
Fluorescence microscopy is a key driver to promote discoveries of biomedical research. However, with the limitation of microscope hardware and characteristics of the observed sampl…
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…
Learning-based Single-step Quantitative Susceptibility Mapping Reconstruction Without Brain Extraction
Hongjiang Wei, Steven Cao, Yuyao Zhang +4
Quantitative susceptibility mapping (QSM) estimates the underlying tissue magnetic susceptibility from MRI gradient-echo phase signal and typically requires several processing step…