Elastic Deformation of Optical Coherence Tomography Images of Diabetic Macular Edema for Deep-Learning Models Training: How Far to Go?

Elastic Deformation of Optical Coherence Tomography Images of Diabetic Macular Edema for Deep-Learning Models Training: How Far to Go?

– Objective: To explore the clinical validity of elastic deformation of optical coherence tomography (OCT) images for data augmentation in the development of deep-learning model for detection of diabetic macular edema (DME). Methods: Prospective evaluation of OCT images of DME (n &#x0...

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Bibliographic Details
Main Authors: Daniel Bar-David, Laura Bar-David, Yinon Shapira, Rina Leibu, Dalia Dori, Aseel Gebara, Ronit Schneor, Anath Fischer, Shiri Soudry
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Journal of Translational Engineering in Health and Medicine
Subjects:
Data augmentation
OCT
deep learning
DME
elastic deformation
Online Access:https://ieeexplore.ieee.org/document/10192390/

Internet

https://ieeexplore.ieee.org/document/10192390/

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