50 citations · 90 across the 6 of their papers we have counts for
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eess.IV2025★ 1 cited
Fundus Image Quality Assessment and Enhancement: a Systematic Review
Heng Li, Haojin Li, Mingyang Ou +5
As an affordable and convenient eye scan, fundus photography holds the potential for preventing vision impairment, especially in resource-limited regions. However, fundus image deg…
eess.IV2023★ 39 cited
Enhancing and Adapting in the Clinic: Source-free Unsupervised Domain Adaptation for Medical Image Enhancement
Heng Li, Ziqin Lin, Zhongxi Qiu +4
Medical imaging provides many valuable clues involving anatomical structure and pathological characteristics. However, image degradation is a common issue in clinical practice, whi…
eess.IV2023★ 50 cited
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…