104 citations · 232 across the 22 of their papers we have counts for
22 papers
Zero-Shot Image Denoising for High-Resolution Electron Microscopy
Xuanyu Tian, Zhuoya Dong, Xiyue Lin +5
High-resolution electron microscopy (HREM) imaging technique is a powerful tool for directly visualizing a broad range of materials in real-space. However, it faces challenges in d…
DPER: Diffusion Prior Driven Neural Representation for Limited Angle and Sparse View CT Reconstruction
Chenhe Du, Xiyue Lin, Qing Wu +9
Limited-angle and sparse-view computed tomography (LACT and SVCT) are crucial for expanding the scope of X-ray CT applications. However, they face challenges due to incomplete data…
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…
Self-Prompting Large Vision Models for Few-Shot Medical Image Segmentation
Qi Wu, Yuyao Zhang, Marawan Elbatel
Recent advancements in large foundation models have shown promising potential in the medical industry due to their flexible prompting capability. One such model, the Segment Anythi…
Unsupervised Polychromatic Neural Representation for CT Metal Artifact Reduction
Qing Wu, Lixuan Chen, Ce Wang +4
Emerging neural reconstruction techniques based on tomography (e.g., NeRF, NeAT, and NeRP) have started showing unique capabilities in medical imaging. In this work, we present a n…
Mining fMRI Dynamics with Parcellation Prior for Brain Disease Diagnosis
Xiaozhao Liu, Mianxin Liu, Lang Mei +4
To characterize atypical brain dynamics under diseases, prevalent studies investigate functional magnetic resonance imaging (fMRI). However, most of the existing analyses compress…
Self-supervised arbitrary scale super-resolution framework for anisotropic MRI
Haonan Zhang, Yuhan Zhang, Qing Wu +7
In this paper, we propose an efficient self-supervised arbitrary-scale super-resolution (SR) framework to reconstruct isotropic magnetic resonance (MR) images from anisotropic MRI…
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…
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…
Model Predictive Control Design of a 3-DOF Robot Arm Based on Recognition of Spatial Coordinates
Zhangxi Zhou, Yuyao Zhang, Yezhang Li
This paper uses Model Predictive Control (MPC) to optimise the input torques of a Three-Degrees-of-Freedom (DOF) robotic arm, enabling it to operate to the target position and gras…
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…
An Arbitrary Scale Super-Resolution Approach for 3D MR Images via Implicit Neural Representation
Qing Wu, Yuwei Li, Yawen Sun +4
High Resolution (HR) medical images provide rich anatomical structure details to facilitate early and accurate diagnosis. In MRI, restricted by hardware capacity, scan time, and pa…
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…
PIANO: A Parametric Hand Bone Model from Magnetic Resonance Imaging
Yuwei Li, Minye Wu, Yuyao Zhang +2
Hand modeling is critical for immersive VR/AR, action understanding, or human healthcare. Existing parametric models account only for hand shape, pose, or texture, without modeling…
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…
Scene Flow to Action Map: A New Representation for RGB-D based Action Recognition with Convolutional Neural Networks
Pichao Wang, Wanqing Li, Zhimin Gao +3
Scene flow describes the motion of 3D objects in real world and potentially could be the basis of a good feature for 3D action recognition. However, its use for action recognition,…
Large-scale Continuous Gesture Recognition Using Convolutional Neural Networks
Pichao Wang, Wanqing Li, Song Liu +3
This paper addresses the problem of continuous gesture recognition from sequences of depth maps using convolutional neutral networks (ConvNets). The proposed method first segments…