12 citations · 32 across the 15 of their papers we have counts for
6 papers · 1 filter
FundusGAN: A Hierarchical Feature-Aware Generative Framework for High-Fidelity Fundus Image Generation
Qingshan Hou, Meng Wang, Peng Cao +4
Recent advancements in ophthalmology foundation models such as RetFound have demonstrated remarkable diagnostic capabilities but require massive datasets for effective pre-training…
Confidence-aware multi-modality learning for eye disease screening
Ke Zou, Tian Lin, Zongbo Han +6
Multi-modal ophthalmic image classification plays a key role in diagnosing eye diseases, as it integrates information from different sources to complement their respective performa…
Federated Uncertainty-Aware Aggregation for Fundus Diabetic Retinopathy Staging
Meng Wang, Lianyu Wang, Xinxing Xu +5
Deep learning models have shown promising performance in the field of diabetic retinopathy (DR) staging. However, collaboratively training a DR staging model across multiple instit…
Reliable Multimodality Eye Disease Screening via Mixture of Student's t Distributions
Ke Zou, Tian Lin, Xuedong Yuan +4
Multimodality eye disease screening is crucial in ophthalmology as it integrates information from diverse sources to complement their respective performances. However, the existing…
A Review of Uncertainty Estimation and its Application in Medical Imaging
Ke Zou, Zhihao Chen, Xuedong Yuan +3
The use of AI systems in healthcare for the early screening of diseases is of great clinical importance. Deep learning has shown great promise in medical imaging, but the reliabili…
TBraTS: Trusted Brain Tumor Segmentation
Ke Zou, Xuedong Yuan, Xiaojing Shen +2
Despite recent improvements in the accuracy of brain tumor segmentation, the results still exhibit low levels of confidence and robustness. Uncertainty estimation is one effective…