4 citations · 6 across the 8 of their papers we have counts for
5 papers · 1 filter
SeATrans: Learning Segmentation-Assisted diagnosis model via Transformer
Junde Wu, Huihui Fang, Fangxin Shang +5
Clinically, the accurate annotation of lesions/tissues can significantly facilitate the disease diagnosis. For example, the segmentation of optic disc/cup (OD/OC) on fundus image w…
Learning self-calibrated optic disc and cup segmentation from multi-rater annotations
Junde Wu, Huihui Fang, Fangxin Shang +5
The segmentation of optic disc(OD) and optic cup(OC) from fundus images is an important fundamental task for glaucoma diagnosis. In the clinical practice, it is often necessary to…
One Hyper-Initializer for All Network Architectures in Medical Image Analysis
Fangxin Shang, Yehui Yang, Dalu Yang +3
Pre-training is essential to deep learning model performance, especially in medical image analysis tasks where limited training data are available. However, existing pre-training m…
Contrastive Centroid Supervision Alleviates Domain Shift in Medical Image Classification
Wenshuo Zhou, Dalu Yang, Binghong Wu +6
Deep learning based medical imaging classification models usually suffer from the domain shift problem, where the classification performance drops when training data and real-world…
Opinions Vary? Diagnosis First!
Junde Wu, Huihui Fang, Dalu Yang +5
With the advancement of deep learning techniques, an increasing number of methods have been proposed for optic disc and cup (OD/OC) segmentation from the fundus images. Clinically,…