Abstract: In this study a deep-learning based model for segmentation of thirteen features, common in atrophic and neovascular age-related macular degeneration is presented and evaluated.The model is compared against four independent observers and performs on par with them for most features, both in terms of overlap and extent of the segmented area.The model can be used to automatically evaluate large quantities of data or for integration in clinical practice.