1 citations · 1 across the 19 of their papers we have counts for
21 papers
PerFact: Perception-Derived Fact Prompting for 3D Brain MRI Report Generation
Jianyu Sun, Zhenxuan Zhang, Guang Yang +1
Radiology report generation has matured almost entirely on 2D chest radiographs, where the default route to better reports is a larger backbone or a pre-training one on medical dat…
BagShift: Measuring How Patch Selection Changes the Evidence Seen by Whole-Slide MIL
Ruicheng Yuan, Zhenxuan Zhang, Liwei Hu +4
Whole-slide multiple-instance learning (MIL) observes only the patches admitted by its selector. Deployment can alter this selector through compute limits, tissue masking, or regio…
MoE-dqINR: A Unified Mixture-of-Experts Implicit Neural Representation Framework for Scan-Specific Dynamic and Quantitative MRI Reconstruction
Yinzhe Wu, Fanwen Wang, Zhenxuan Zhang +3
Undersampled magnetic resonance imaging (MRI) reconstruction seeks to recover temporally or contrast-varying image series from incomplete multicoil k-space data while preserving st…
Seeing Through Experts Eyes A Foundational Vision Language Model Trained on Radiologists Gaze and Reasoning
Kinhei Lee, Peiyuan Jing, Zhenxuan Zhang +5
Large scale vision language models have shown promise in automating chest Xray interpretation, yet their clinical utility remains limited by a gap between model outputs and radiolo…
Unleashing Video Language Models for Fine-grained HRCT Report Generation
Yingying Fang, Huichi Zhou, KinHei Lee +4
Generating precise diagnostic reports from High-Resolution Computed Tomography (HRCT) is critical for clinical workflow, yet it remains a formidable challenge due to the high patho…
3D Wavelet-Based Structural Priors for Controlled Diffusion in Whole-Body Low-Dose PET Denoising
Peiyuan Jing, Yue Yang, Chun-Wun Cheng +8
Low-dose Positron Emission Tomography (PET) imaging reduces patient radiation exposure but suffers from increased noise that degrades image quality and diagnostic reliability. Alth…
MAP-Diff: Multi-Anchor Guided Diffusion for Progressive 3D Whole-Body Low-Dose PET Denoising
Peiyuan Jing, Chun-Wun Cheng, Liutao Yang +7
Low-dose Positron Emission Tomography (PET) reduces radiation exposure but suffers from severe noise and quantitative degradation. Diffusion-based denoising models achieve strong f…
HiPath: Hierarchical Vision-Language Alignment for Structured Pathology Report Prediction
Ruicheng Yuan, Zhenxuan Zhang, Anbang Wang +5
Pathology reports are structured, multi-granular documents encoding diagnostic conclusions, histological grades, and ancillary test results across one or more anatomical sites; yet…
ReDiff: Reliability-Guided Diffusion for Trustworthy Ultra-Low-Field to High-Field MRI Synthesis
Zhenxuan Zhang, Peiyuan Jing, Ruicheng Yuan +9
Low-field to high-field MRI synthesis has emerged as a promising strategy to improve image quality when access to high-field scanners is limited. However, in ultra-low-field settin…
Enabling Ultra-Fast Cardiovascular Imaging Across Heterogeneous Clinical Environments with A Generalist Foundation Model and Multimodal Database
Zi Wang, Mingkai Huang, Zhang Shi +61
Multimodal cardiovascular magnetic resonance (CMR) imaging provides comprehensive and non-invasive insights into cardiovascular disease (CVD) diagnosis and underlying mechanisms. D…
Musical Score Understanding Benchmark: Evaluating Large Language Models' Comprehension of Complete Musical Scores
Congren Dai, Yue Yang, Krinos Li +12
Understanding complete musical scores entails integrated reasoning over pitch, rhythm, harmony, and large-scale structure, yet the ability of Large Language Models and Vision--Lang…
Cyclic Self-Supervised Diffusion for Ultra Low-field to High-field MRI Synthesis
Zhenxuan Zhang, Peiyuan Jing, Zi Wang +12
Synthesizing high-quality images from low-field MRI holds significant potential. Low-field MRI is cheaper, more accessible, and safer, but suffers from low resolution and poor sign…
From Noisy Labels to Intrinsic Structure: A Geometric-Structural Dual-Guided Framework for Noise-Robust Medical Image Segmentation
Tao Wang, Zhenxuan Zhang, Yuanbo Zhou +5
The effectiveness of convolutional neural networks in medical image segmentation relies on large-scale, high-quality annotations, which are costly and time-consuming to obtain. Eve…
From Coarse to Continuous: Progressive Refinement Implicit Neural Representation for Motion-Robust Anisotropic MRI Reconstruction
Zhenxuan Zhang, Lipei Zhang, Yanqi Cheng +10
In motion-robust magnetic resonance imaging (MRI), slice-to-volume reconstruction is critical for recovering anatomically consistent 3D brain volumes from 2D slices, especially und…
Dynamic Dual Buffer with Divide-and-Conquer Strategy for Online Continual Learning
Congren Dai, Huichi Zhou, Jiahao Huang +5
Online Continual Learning (OCL) involves sequentially arriving data and is particularly challenged by catastrophic forgetting, which significantly impairs model performance. To add…
Decoupling Multi-Contrast Super-Resolution: Self-Supervised Implicit Re-Representation for Unpaired Cross-Modal Synthesis
Yinzhe Wu, Hongyu Rui, Fanwen Wang +5
Multi-contrast super-resolution (MCSR) is crucial for enhancing MRI but current deep learning methods are limited. They typically require large, paired low- and high-resolution (LR…
Reason Like a Radiologist: Chain-of-Thought and Reinforcement Learning for Verifiable Report Generation
Peiyuan Jing, Kinhei Lee, Zhenxuan Zhang +7
Radiology report generation is critical for efficiency but current models lack the structured reasoning of experts, hindering clinical trust and explainability by failing to link v…
Task-oriented Uncertainty Collaborative Learning for Label-Efficient Brain Tumor Segmentation
Zhenxuan Zhang, Hongjie Wu, Jiahao Huang +5
Multi-contrast magnetic resonance imaging (MRI) plays a vital role in brain tumor segmentation and diagnosis by leveraging complementary information from different contrasts. Each…
Pretext Task Adversarial Learning for Unpaired Low-field to Ultra High-field MRI Synthesis
Zhenxuan Zhang, Peiyuan Jing, Coraline Beitone +4
Given the scarcity and cost of high-field MRI, the synthesis of high-field MRI from low-field MRI holds significant potential when there is limited data for training downstream tas…
GEMA-Score: Granular Explainable Multi-Agent Scoring Framework for Radiology Report Evaluation
Zhenxuan Zhang, Kinhei Lee, Peiyuan Jing +8
Automatic medical report generation has the potential to support clinical diagnosis, reduce the workload of radiologists, and demonstrate potential for enhancing diagnostic consist…
Lightweight Hypercomplex MRI Reconstruction: A Generalized Kronecker-Parameterized Approach
Haosen Zhang, Jiahao Huang, Yinzhe Wu +4
Magnetic Resonance Imaging (MRI) is crucial for clinical diagnostics but is hindered by prolonged scan times. Current deep learning models enhance MRI reconstruction but are often…