DBU-Net: Dual-Branch U-Net for Retinal Fundus Image Super-Resolution Under Complex Degradation Conditions

Retinal fundus images are widely utilized in clinical screening and diagnosis of ocular diseases. However, in practical scenarios, the obtained fundus images are prone to be low-resolution (LR). LR fundus images increase the uncertainty in clinical observations, thereby heightening the risk of misdi...

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Autors principals:	Xianghui Chen, Shi Qiu, Yue Wang, Yu Zhang, Zhaoyan Liu, Xinhong Wang, Weiyuan Yao, Hongjia Cheng, Feihong Wang, Zhan Shu, Xuesong Li
Format:	Artigo
Idioma:	Inglês
Publicat:	IEEE 2025-01-01
Col·lecció:	IEEE Access
Matèries:	Retinal fundus image super-resolution deep learning U-Net attention multi-scale
Accés en línia:	https://ieeexplore.ieee.org/document/10813356/
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