38 citations · 58 across the 11 of their papers we have counts for
7 papers · 1 filter
Frequency-mixed Single-source Domain Generalization for Medical Image Segmentation
Heng Li, Haojin Li, Wei Zhao +4
The annotation scarcity of medical image segmentation poses challenges in collecting sufficient training data for deep learning models. Specifically, models trained on limited data…
Elongated Physiological Structure Segmentation via Spatial and Scale Uncertainty-aware Network
Yinglin Zhang, Ruiling Xi, Huazhu Fu +4
Robust and accurate segmentation for elongated physiological structures is challenging, especially in the ambiguous region, such as the corneal endothelium microscope image with un…
Eye tracking guided deep multiple instance learning with dual cross-attention for fundus disease detection
Hongyang Jiang, Jingqi Huang, Chen Tang +3
Deep neural networks (DNNs) have promoted the development of computer aided diagnosis (CAD) systems for fundus diseases, helping ophthalmologists reduce missed diagnosis and misdia…
Hard Exudate Segmentation Supplemented by Super-Resolution with Multi-scale Attention Fusion Module
Jiayi Zhang, Xiaoshan Chen, Zhongxi Qiu +3
Hard exudates (HE) is the most specific biomarker for retina edema. Precise HE segmentation is vital for disease diagnosis and treatment, but automatic segmentation is challenged b…
Degradation-invariant Enhancement of Fundus Images via Pyramid Constraint Network
Haofeng Liu, Heng Li, Huazhu Fu +4
As an economical and efficient fundus imaging modality, retinal fundus images have been widely adopted in clinical fundus examination. Unfortunately, fundus images often suffer fro…
SuperVessel: Segmenting High-resolution Vessel from Low-resolution Retinal Image
Yan Hu, Zhongxi Qiu, Dan Zeng +3
Vascular segmentation extracts blood vessels from images and serves as the basis for diagnosing various diseases, like ophthalmic diseases. Ophthalmologists often require high-reso…