6 citations · 16 across the 9 of their papers we have counts for
9 papers
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…
Uncertainty-aware Medical Diagnostic Phrase Identification and Grounding
Ke Zou, Yang Bai, Bo Liu +9
Medical phrase grounding is crucial for identifying relevant regions in medical images based on phrase queries, facilitating accurate image analysis and diagnosis. However, current…
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-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…
Towards Reliable Medical Image Segmentation by Modeling Evidential Calibrated Uncertainty
Ke Zou, Yidi Chen, Ling Huang +6
Medical image segmentation is critical for disease diagnosis and treatment assessment. However, concerns regarding the reliability of segmentation regions persist among clinicians,…
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…
The Effect of Population Size for Pathogen Transmission on Prediction of COVID-19 Pandemic Spread
Xuqi Zhang, Haiqi Liu, Hanning Tang +3
Extreme public health interventions play a critical role in mitigating the local and global prevalence and pandemic potential of COVID-19. Here, we use population size for pathogen…