88 citations · 191 across the 6 of their papers we have counts for
5 papers · 1 filter
A Generic Fundus Image Enhancement Network Boosted by Frequency Self-supervised Representation Learning
Heng Li, Haofeng Liu, Huazhu Fu +5
Fundus photography is prone to suffer from image quality degradation that impacts clinical examination performed by ophthalmologists or intelligent systems. Though enhancement algo…
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…
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…
Structure-consistent Restoration Network for Cataract Fundus Image Enhancement
Heng Li, Haofeng Liu, Huazhu Fu +5
Fundus photography is a routine examination in clinics to diagnose and monitor ocular diseases. However, for cataract patients, the fundus image always suffers quality degradation…
An Annotation-free Restoration Network for Cataractous Fundus Images
Heng Li, Haofeng Liu, Yan Hu +4
Cataracts are the leading cause of vision loss worldwide. Restoration algorithms are developed to improve the readability of cataract fundus images in order to increase the certain…