2 citations · 4 across the 8 of their papers we have counts for
10 papers
DeepPV-MRF: End-to-End Partial-Volume Fraction Estimation from MR Fingerprinting Time Series
Tianyi Ding, Yang Gao, Zhuang Xiong +4
Background: Estimating subvoxel tissue fractions from magnetic resonance fingerprinting (MRF) is challenging. Conventional dictionary matching and segmentation pipelines can propag…
DINO-MVR: Multi-View Readout of Frozen DINOv3 for Annotation-Efficient Medical Segmentation
Wei Jiang, Feng Liu, Nan Ye +1
Adapting foundation models to medical segmentation typically requires either backbone fine-tuning or high-capacity task-specific decoders, both of which are difficult to fit reliab…
GateFuseNet: An Adaptive 3D Multimodal Neuroimaging Fusion Network for Parkinson's Disease Diagnosis
Rui Jin, Chen Chen, Yin Liu +4
Accurate diagnosis of Parkinson's disease (PD) from MRI remains challenging due to symptom variability and pathological heterogeneity. Most existing methods rely on conventional ma…
Adaptive Gate-Aware Mamba Networks for Magnetic Resonance Fingerprinting
Tianyi Ding, Hongli Chen, Yang Gao +4
Magnetic Resonance Fingerprinting (MRF) enables fast quantitative imaging by matching signal evolutions to a predefined dictionary. However, conventional dictionary matching suffer…
SUSEP-Net: Simulation-Supervised and Contrastive Learning-based Deep Neural Networks for Susceptibility Source Separation
Min Li, Chen Chen, Zhenghao Li +9
Quantitative susceptibility mapping (QSM) provides a valuable tool for quantifying susceptibility distributions in human brains; however, two types of opposing susceptibility sourc…
Highly Undersampled MRI Reconstruction via a Single Posterior Sampling of Diffusion Models
Jin Liu, Qing Lin, Zhuang Xiong +7
Incoherent k-space undersampling and deep learning-based reconstruction methods have shown great success in accelerating MRI. However, the performance of most previous methods will…
IR2QSM: Quantitative Susceptibility Mapping via Deep Neural Networks with Iterative Reverse Concatenations and Recurrent Modules
Min Li, Chen Chen, Zhuang Xiong +6
Quantitative susceptibility mapping (QSM) is an MRI phase-based post-processing technique to extract the distribution of tissue susceptibilities, demonstrating significant potentia…
QSMDiff: Unsupervised 3D Diffusion Models for Quantitative Susceptibility Mapping
Zhuang Xiong, Wei Jiang, Yang Gao +2
Quantitative Susceptibility Mapping (QSM) dipole inversion is an ill-posed inverse problem for quantifying magnetic susceptibility distributions from MRI tissue phases. While super…
Multi-scale MRI reconstruction via dilated ensemble networks
Wendi Ma, Marlon Bran Lorenzana, Wei Dai +2
As aliasing artefacts are highly structural and non-local, many MRI reconstruction networks use pooling to enlarge filter coverage and incorporate global context. However, this ina…
Fast Controllable Diffusion Models for Undersampled MRI Reconstruction
Wei Jiang, Zhuang Xiong, Feng Liu +2
Supervised deep learning methods have shown promise in undersampled Magnetic Resonance Imaging (MRI) reconstruction, but their requirement for paired data limits their generalizabi…