21 citations · 122 across the 20 of their papers we have counts for
20 papers
Slicer Networks
Hang Zhang, Xiang Chen, Rongguang Wang +3
In medical imaging, scans often reveal objects with varied contrasts but consistent internal intensities or textures. This characteristic enables the use of low-frequency approxima…
Spatially Covariant Image Registration with Text Prompts
Xiang Chen, Min Liu, Rongguang Wang +4
Medical images are often characterized by their structured anatomical representations and spatially inhomogeneous contrasts. Leveraging anatomical priors in neural networks can gre…
DAGrid: Directed Accumulator Grid
Hang Zhang, Renjiu Hu, Xiang Chen +3
Recent research highlights that the Directed Accumulator (DA), through its parametrization of geometric priors into neural networks, has notably improved the performance of medical…
High-pass filtered fidelity-imposed network edit (HP-FINE) for robust quantitative susceptibility mapping from high-pass filtered phase
Jinwei Zhang, Alexey Dimov, Chao Li +4
Purpose: To improve the generalization ability of deep learning based predictions of quantitative susceptibility mapping (QSM) from high-pass filtered phase (HPFP) data. Methods: A…
mcLARO: Multi-Contrast Learned Acquisition and Reconstruction Optimization for simultaneous quantitative multi-parametric mapping
Jinwei Zhang, Thanh D. Nguyen, Eddy Solomon +6
Purpose: To develop a method for rapid sub-millimeter T1, T2, T2* and QSM mapping in a single scan using multi-contrast Learned Acquisition and Reconstruction Optimization (mcLARO)…
DeDA: Deep Directed Accumulator
Hang Zhang, Rongguang Wang, Renjiu Hu +2
Chronic active multiple sclerosis lesions, also termed as rim+ lesions, can be characterized by a hyperintense rim at the edge of the lesion on quantitative susceptibility maps. Th…
Spatially Covariant Lesion Segmentation
Hang Zhang, Rongguang Wang, Jinwei Zhang +3
Compared to natural images, medical images usually show stronger visual patterns and therefore this adds flexibility and elasticity to resource-limited clinical applications by inj…
LARO: Learned Acquisition and Reconstruction Optimization to accelerate Quantitative Susceptibility Mapping
Jinwei Zhang, Pascal Spincemaille, Hang Zhang +6
Quantitative susceptibility mapping (QSM) involves acquisition and reconstruction of a series of images at multi-echo time points to estimate tissue field, which prolongs scan time…
Temporal Feature Fusion with Sampling Pattern Optimization for Multi-echo Gradient Echo Acquisition and Image Reconstruction
Jinwei Zhang, Hang Zhang, Chao Li +4
Quantitative imaging in MRI usually involves acquisition and reconstruction of a series of images at multi-echo time points, which possibly requires more scan time and specific rec…
NeRD: Neural Representation of Distribution for Medical Image Segmentation
Hang Zhang, Rongguang Wang, Jinwei Zhang +5
We introduce Neural Representation of Distribution (NeRD) technique, a module for convolutional neural networks (CNNs) that can estimate the feature distribution by optimizing an u…
Ensembling Low Precision Models for Binary Biomedical Image Segmentation
Tianyu Ma, Hang Zhang, Hanley Ong +5
Segmentation of anatomical regions of interest such as vessels or small lesions in medical images is still a difficult problem that is often tackled with manual input by an expert.…
Geometric Loss for Deep Multiple Sclerosis lesion Segmentation
Hang Zhang, Jinwei Zhang, Rongguang Wang +5
Multiple sclerosis (MS) lesions occupy a small fraction of the brain volume, and are heterogeneous with regards to shape, size and locations, which poses a great challenge for trai…
Efficient Folded Attention for 3D Medical Image Reconstruction and Segmentation
Hang Zhang, Jinwei Zhang, Rongguang Wang +4
Recently, 3D medical image reconstruction (MIR) and segmentation (MIS) based on deep neural networks have been developed with promising results, and attention mechanism has been fu…
Probabilistic Dipole Inversion for Adaptive Quantitative Susceptibility Mapping
Jinwei Zhang, Hang Zhang, Mert Sabuncu +3
A learning-based posterior distribution estimation method, Probabilistic Dipole Inversion (PDI), is proposed to solve the quantitative susceptibility mapping (QSM) inverse problem…
Extending LOUPE for K-space Under-sampling Pattern Optimization in Multi-coil MRI
Jinwei Zhang, Hang Zhang, Alan Wang +5
The previously established LOUPE (Learning-based Optimization of the Under-sampling Pattern) framework for optimizing the k-space sampling pattern in MRI was extended in three fold…
Bayesian Learning of Probabilistic Dipole Inversion for Quantitative Susceptibility Mapping
Jinwei Zhang, Hang Zhang, Mert Sabuncu +3
A learning-based posterior distribution estimation method, Probabilistic Dipole Inversion (PDI), is proposed to solve quantitative susceptibility mapping (QSM) inverse problem in M…
RSANet: Recurrent Slice-wise Attention Network for Multiple Sclerosis Lesion Segmentation
Hang Zhang, Jinwei Zhang, Qihao Zhang +7
Brain lesion volume measured on T2 weighted MRI images is a clinically important disease marker in multiple sclerosis (MS). Manual delineation of MS lesions is a time-consuming and…
Fidelity Imposed Network Edit (FINE) for Solving Ill-Posed Image Reconstruction
Jinwei Zhang, Zhe Liu, Shun Zhang +5
Deep learning (DL) is increasingly used to solve ill-posed inverse problems in imaging, such as reconstruction from noisy or incomplete data, as DL offers advantages over explicit…
Blaze: Simplified High Performance Cluster Computing
Junhao Li, Hang Zhang
MapReduce and its variants have significantly simplified and accelerated the process of developing parallel programs. However, most MapReduce implementations focus on data-intensiv…
Robust Matrix Regression
Hang Zhang, Fengyuan Zhu, Shixin Li
Modern technologies are producing datasets with complex intrinsic structures, and they can be naturally represented as matrices instead of vectors. To preserve the latent data stru…