Deep learning for predicting circular retinal nerve fiber layer thickness from fundus photographs and diagnosing glaucoma

This study aimed to propose a new deep learning (DL) approach to automatically predict the retinal nerve fiber layer thickness (RNFLT) around optic disc regions in fundus photography trained by optical coherence tomography (OCT) and diagnose glaucoma based on the predicted comprehensive information...

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Veröffentlicht in:	Heliyon 2024-07, Vol.10 (13), p.e33813, Article e33813
Hauptverfasser:	Xu, Yongli, Liu, Hanruo, Sun, Run, Wang, Huaizhou, Huo, Yanjiao, Wang, Ningli, Hu, Man
Format:	Artikel
Sprache:	eng
Schlagworte:	Deep learning Fundus photography Glaucoma Optical coherence tomography Retinal nerve fiber layer thickness
Online-Zugang:	Volltext
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