3 citations · 3 across the 5 of their papers we have counts for
6 papers
Geometry-Aligned Semantic Matching for Cross-Modal Planar Image Registration
Zhiwei Wang, Defeng He, Yuxing Li +2
Cross-modal image matching establishes stable and accurate geometric correspondences across modalities for planar registration. Existing semantic representations provide cross-moda…
Joint Segmentation and Grading with Iterative Optimization for Multimodal Glaucoma Diagnosis
Zhiwei Wang, Yuxing Li, Meilu Zhu +2
Accurate diagnosis of glaucoma is challenging, as early-stage changes are subtle and often lack clear structural or appearance cues. Most existing approaches rely on a single modal…
Personalized Federated Learning with Residual Fisher Information for Medical Image Segmentation
Meilu Zhu, Yuxing Li, Zhiwei Wang +1
Federated learning enables multiple clients (institutions) to collaboratively train machine learning models without sharing their private data. To address the challenge of data het…
FedBM: Stealing Knowledge from Pre-trained Language Models for Heterogeneous Federated Learning
Meilu Zhu, Qiushi Yang, Zhifan Gao +2
Federated learning (FL) has shown great potential in medical image computing since it provides a decentralized learning paradigm that allows multiple clients to train a model colla…
DEeR: Deviation Eliminating and Noise Regulating for Privacy-preserving Federated Low-rank Adaptation
Meilu Zhu, Axiu Mao, Jun Liu +1
Integrating low-rank adaptation (LoRA) with federated learning (FL) has received widespread attention recently, aiming to adapt pretrained foundation models (FMs) to downstream med…
Personalized Retrogress-Resilient Framework for Real-World Medical Federated Learning
Zhen Chen, Meilu Zhu, Chen Yang +1
Nowadays, deep learning methods with large-scale datasets can produce clinically useful models for computer-aided diagnosis. However, the privacy and ethical concerns are increasin…