Quantification of cone loss after surgery for retinal detachment involving the macula using adaptive optics
Maher Saleh(Université de Franche-Comté), B. Delbosc(Centre Hospitalier Universitaire de Besançon), Mathieu Flores(Université de Franche-Comté), M BIDAUT GARNIER(Université de Franche-Comté), C. Schwartz(Université de Franche-Comté), Guillaume Debellemanière(Fondation Ophtalmologique Adolphe de Rothschild), Perle Tumahai(Université de Franche-Comté)
Cited by 49
Related Papers
The PEARL-DGS Formula: The Development of an Open-source Machine Learning–based Thick IOL Calculation Formula
|American Journal of Ophthalmology|2021|125
Impact of Surgical Learning Curve in Descemet Membrane Endothelial Keratoplasty on Visual Acuity Gain
|Cornea|2016|64
Corneal Topography Raw Data Classification Using a Convolutional Neural Network
|American Journal of Ophthalmology|2020|50
Determining the Theoretical Effective Lens Position of Thick Intraocular Lenses for Machine Learning–Based IOL Power Calculation and Simulation
|Translational Vision Science & Technology|2021|46
Reliability of cone counts using an adaptive optics retinal camera
|Clinical and Experimental Ophthalmology|2014|42