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Purpose: This work aims to identify areas with sub-retinal-pigment-epithelium (sub-RPE) accumulations on 2dimensional (2D) color-fundus-photographs (CFPs) in patients with age-related macular degeneration (AMD) using the definitions in spectral-domain-optical-coherence-tomography (SD-OCT) imaging. Detecting and quantifying areas of RPE elevations (most notably drusen) in CFPs will aid in objective evaluation of AMDseverity-scores as well as patient selection and monitoring in clinical trials. Methods: A retinal-layersegmentation algorithm for SD-OCTs was used to automatically identify areas with RPE elevations and build the ground-truth 2D binary maps for training. CFP was registered to the enface projection images of SD-OCT to overlay OCT-defined drusen areas on CFP images. A 2D-UNet segmentation network was trained using bilateral stereo CFP pairs in a Siamese architecture that share OCT-defined drusen areas as ground-truth. Results: Dataset consists of AMD patients with 127 train and 23 test eyes. Dice-similarity-coefficient for the predictions on CFPs was found to be 0.70±0.13 (mean±std), and overall accuracy was 0.73. 89% of test eyes exhibited drusen area prediction error <1mm 2 compared to reading-center measures. Conclusion: Our work demonstrates the potential of using 2D CFP images to predict areas of sub-RPE elevations as defined in 3D-SD-OCT imaging. Qualitative evaluation of the mismatch between the two imaging modalities shows regions with complementary features in a subset of the cases making it challenging to achieve optimal segmentation. However, the results show clinically useful performance in CFPs that can be used to quantify accumulations in the sub-RPE space which are the key pathologic biomarkers of AMD relevant to patient selection and trial outcome measure designs.

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