1. DeshadowGAN: A Deep Learning Approach to Remove Shadows from Optical Coherence Tomography Images

    DeshadowGAN: A Deep Learning Approach to Remove Shadows from Optical Coherence Tomography Images

    Purpose: To remove retinal shadows from optical coherence tomography (OCT) images of the optic nerve head (ONH). Methods: 2328 OCT images acquired through the center of the ONH using a Spectralis OCT machine for both eyes of 13 subjects were used to train a generative adversarial network (GAN) using a custom loss function.Image quality was assessed qualitatively (for artifacts) and quantitatively using the intralayer contrast € a measure of shadow visibility ranging from 0 (shadow-free) to 1 (strong shadow) and compared to compensated images. Œis was computed in the Retinal Nerve Fiber Layer (RNFL), the Inner Plexiform Layer (IPL), the ...

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