1. Geographic Atrophy Segmentation in SD-OCT Images Using Synthesized Fundus Autofluorescence Imaging

    Geographic Atrophy Segmentation in SD-OCT Images Using Synthesized Fundus Autofluorescence Imaging

    Background and Objective Accurate assessment of geographic atrophy (GA) is critical for diagnosis and therapy of non-exudative age-related macular degeneration (AMD). Herein, we propose a novel GA segmentation framework for spectral-domain optical coherence tomography (SD-OCT) images that employs synthesized fundus autofluorescence (FAF) images. Methods An en-face OCT image is created via the restricted sub-volume projection of three-dimensional OCT data. A GA region-aware conditional generative adversarial network is employed to generate a plausible FAF image from the en-face OCT image. The network balances the consistency between the entire synthesize FAF image and the lesion. We use a fully convolutional deep network ...

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