A multi-task deep-learning system for assessment of diabetic macular ischemia on optical coherence tomography angiography images.

Purpose null We aimed to develop and test a deep-learning (DL) system to perform image quality and diabetic macular ischemia (DMI) assessment on OCTA images. null Methods null This study included 7,194 OCTA images with diabetes mellitus for training and primary validation, and 960 images from three independent datasets for external testing. A trinary classification for image quality assessment and presence or absence of DMI for DMI assessment...