80 citations · 142 across the 12 of their papers we have counts for
12 papers
ReSynthDetect: A Fundus Anomaly Detection Network with Reconstruction and Synthetic Features
Jingqi Niu, Qinji Yu, Shiwen Dong +3
Detecting anomalies in fundus images through unsupervised methods is a challenging task due to the similarity between normal and abnormal tissues, as well as their indistinct bound…
Source-Free Domain Adaptation for Medical Image Segmentation via Prototype-Anchored Feature Alignment and Contrastive Learning
Qinji Yu, Nan Xi, Junsong Yuan +3
Unsupervised domain adaptation (UDA) has increasingly gained interests for its capacity to transfer the knowledge learned from a labeled source domain to an unlabeled target domain…
Region and Spatial Aware Anomaly Detection for Fundus Images
Jingqi Niu, Shiwen Dong, Qinji Yu +2
Recently anomaly detection has drawn much attention in diagnosing ocular diseases. Most existing anomaly detection research in fundus images has relatively large anomaly scores in…
DualStreamFoveaNet: A Dual Stream Fusion Architecture with Anatomical Awareness for Robust Fovea Localization
Sifan Song, Jinfeng Wang, Zilong Wang +4
Accurate fovea localization is essential for analyzing retinal diseases to prevent irreversible vision loss. While current deep learning-based methods outperform traditional ones,…
Coarse Retinal Lesion Annotations Refinement via Prototypical Learning
Qinji Yu, Kang Dang, Ziyu Zhou +2
Deep-learning-based approaches for retinal lesion segmentation often require an abundant amount of precise pixel-wise annotated data. However, coarse annotations such as circles or…
Weakly Supervised Online Action Detection for Infant General Movements
Tongyi Luo, Jia Xiao, Chuncao Zhang +5
To make the earlier medical intervention of infants' cerebral palsy (CP), early diagnosis of brain damage is critical. Although general movements assessment(GMA) has shown promisin…