SynthEye: Investigating the Impact of Synthetic Data on Artificial Intelligence-assisted Gene Diagnosis of Inherited Retinal Disease.

Yoga Advaith Veturi,William Woof,Teddy Lazebnik,Ismail Moghul,Peter Woodward-Court,Siegfried K Wagner,Thales Antonio Cabral de Guimarães,Malena Daich Varela,Bart Liefers,Praveen J Patel,Stephan Beck,Andrew R Webster,Omar Mahroo,Pearse A Keane,Michel Michaelides,Konstantinos Balaskas,Nikolas Pontikos

Ophthalmology Science（2023）

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摘要

Synthetic generation of realistic IRD FAF images is feasible. Synthetic data augmentation does not deliver improvements in classification performance. However, synthetic data alone deliver a similar performance as real data, and hence may be useful as a proxy to real data. Proprietary or commercial disclosure may be found after the references.

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关键词

AUROC, area under the receiver operating characteristic curve,BRISQUE, Blind/Referenceless Image Spatial Quality Evaluator,Class imbalance,Clinical Decision-Support Model,DL, deep learning,Deep Learning,FAF, fundas autofluorescence,FRR, Fake Recognition Rate,GAN, generative adversarial network,Generative Adversarial Networks,IRD, inherited retinal disease,Inherited Retinal Diseases,MEH, Moorfields Eye Hospital,R, baseline model,RB, rebalanced model,S, synthetic data trained model,Synthetic data,TRR, True Recognition Rate,UMAP, Universal Manifold Approximation and Projection

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