11 citations · 13 across the 9 of their papers we have counts for
9 papers
Artificial Intelligence Across the Cardiac Amyloidosis Diagnostic and Management Pathway: From Single-Modality Detection to Multimodal Clinical Integration
Diana Shadibaeva, Rochak Dhakal, Kui Zhang +4
Cardiac amyloidosis (CA) is increasingly recognized but remains substantially underdiagnosed because its clinical and imaging phenotype overlaps with more common cardiomyopathies.…
BrainDINO: A Brain MRI Foundation Model for Generalizable Clinical Representation Learning
Yizhou Wu, Shansong Wang, Yuheng Li +5
Brain MRI underpins a wide range of neuroscientific and clinical applications, yet most learning-based methods remain task-specific and require substantial labeled data. Here we sh…
Evaluating GPT-5 as a Multimodal Clinical Reasoner: A Landscape Commentary
Alexandru Florea, Shansong Wang, Mingzhe Hu +5
The transition from task-specific artificial intelligence toward general-purpose foundation models raises fundamental questions about their capacity to support the integrated reaso…
MedDINOv3: How to adapt vision foundation models for medical image segmentation?
Yuheng Li, Yizhou Wu, Yuxiang Lai +2
Accurate segmentation of organs and tumors in CT and MRI scans is essential for diagnosis, treatment planning, and disease monitoring. While deep learning has advanced automated se…
Capabilities of GPT-5 on Multimodal Medical Reasoning
Shansong Wang, Mingzhe Hu, Qiang Li +2
Recent advances in large language models (LLMs) have enabled general-purpose systems to perform increasingly complex domain-specific reasoning without extensive fine-tuning. In the…
A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning
Mingzhe Hu, Yuan Gao, Yuheng Li +10
Purpose: Accurate segmentation of clinical target volumes (CTV) and organs-at-risk is crucial for optimizing gynecologic brachytherapy (GYN-BT) treatment planning. However, anatomi…
Current Progress of Digital Twin Construction Using Medical Imaging
Feng Zhao, Yizhou Wu, Mingzhe Hu +4
Medical imaging has played a pivotal role in advancing and refining digital twin technology, allowing for the development of highly personalized virtual models that represent human…
AnatoMask: Enhancing Medical Image Segmentation with Reconstruction-guided Self-masking
Yuheng Li, Tianyu Luan, Yizhou Wu +3
Due to the scarcity of labeled data, self-supervised learning (SSL) has gained much attention in 3D medical image segmentation, by extracting semantic representations from unlabele…
Mammo-CLIP: Leveraging Contrastive Language-Image Pre-training (CLIP) for Enhanced Breast Cancer Diagnosis with Multi-view Mammography
Xuxin Chen, Yuheng Li, Mingzhe Hu +5
Although fusion of information from multiple views of mammograms plays an important role to increase accuracy of breast cancer detection, developing multi-view mammograms-based com…