A CycleGAN deep learning technique for artifact reduction in fundus photography
Version 1Herein, we present a deep learning technique to remove artifacts automatically in fundus photograph. By using a CycleGAN model, we synthesize the retinal images with artifact reduction based on low-quality image, and validated this technique in the independent test dataset. This study included total 2,206 anonymized retinal images. We collected the fundus photographs without qualification, which include normal and pathologic retinal images. Images including both photograph with and without artif
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Herein, we present a deep learning technique to remove artifacts automatically in fundus photograph. By using a CycleGAN model, we synthesize the retinal images with artifact reduction based on low-quality image, and validated this technique in the independent test dataset. This study included total 2,206 anonymized retinal images. We collected the fundus photographs without qualification, which include normal and pathologic retinal images. Images including both photograph with and without artif