Prediction of Postoperative Visual Acuity in Rhegmatogenous Retinal Detachment Using OCT Images

Prediction of Postoperative Visual Acuity in Rhegmatogenous Retinal Detachment Using OCT Images

Deep Learning (DL) methods, such as Convolution Neural Networks (CNNs), have shown great potential in diagnosing complex diseases. Among these diseases, Rhegmatogenous Retinal Detachment (RRD) stands out as a critical condition necessitating precise diagnosis and postoperative Visual Acuity (VA) pre...

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Bibliographic Details
Main Authors: Sinda Hosni, Hajer Khachnaoui, Hsouna Mehdi Zgolli, Sonya Mabrouk, Desire Sidibe, Hedi Tabia, Nawres Khlifa
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Convolutional neural networks
deep learning
CAD system
rhegmatogenous retinal detachment
OCT imaging
Online Access:https://ieeexplore.ieee.org/document/10336764/

Internet

https://ieeexplore.ieee.org/document/10336764/

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