12 citations · 32 across the 15 of their papers we have counts for
7 papers · 1 filter
A Multi-view Impartial Decision Network for Frontotemporal Dementia Diagnosis
Guoyao Deng, Ke Zou, Meng Wang +3
Frontotemporal Dementia (FTD) diagnosis has been successfully progress using deep learning techniques. However, current FTD identification methods suffer from two limitations. Firs…
Uncertainty-inspired Open Set Learning for Retinal Anomaly Identification
Meng Wang, Tian Lin, Lianyu Wang +21
Failure to recognize samples from the classes unseen during training is a major limitation of artificial intelligence in the real-world implementation for recognition and classific…
Model Barrier: A Compact Un-Transferable Isolation Domain for Model Intellectual Property Protection
Lianyu Wang, Meng Wang, Daoqiang Zhang +1
As scientific and technological advancements result from human intellectual labor and computational costs, protecting model intellectual property (IP) has become increasingly impor…
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…
Uncertainty-informed Mutual Learning for Joint Medical Image Classification and Segmentation
Kai Ren, Ke Zou, Xianjie Liu +5
Classification and segmentation are crucial in medical image analysis as they enable accurate diagnosis and disease monitoring. However, current methods often prioritize the mutual…
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…