Purpose To assess whether a generative adversarial network (GAN) could synthesize realistic optical coherence tomography (OCT) images that satisfactorily serve as the educational images for retinal specialists, and the training datasets for the classification of various retinal disorders using deep learning (DL). Methods The GANs architecture was adopted to synthesize high-resolution OCT images trained on a publicly available OCT dataset, including urgent referrals (37,206 OCT images from eyes with choroidal neovascularization, and 11,349 OCT images from eyes with diabetic macular edema) and nonurgent referrals (8617 OCT images from eyes with drusen, and 51,140 OCT images from normal eyes). Four hundred real and synthetic OCT images were evaluated by two retinal specialists (with over 10 years of clinical retinal experience) to assess image quality. We further trained two DL models on either real or synthetic datasets and compared the performance of urgent versus nonurgent referrals diagnosis tested on a local (1000 images from the public dataset) and clinical validation dataset (278 images from Shanghai Shibei Hospital). Results The image quality of real versus synthetic OCT images was similar as assessed by two retinal specialists. The accuracy of discrimination of real versus synthetic OCT images was 59.50% for retinal specialist 1 and 53.67% for retinal specialist 2. For the local dataset, the DL model trained on real (DL_Model_R) and synthetic OCT images (DL_Model_S) had an area under the curve (AUC) of 0.99, and 0.98, respectively. For the clinical dataset, the AUC was 0.94 for DL_Model_R and 0.90 for DL_Model_S. Conclusions The GAN synthetic OCT images can be used by clinicians for educational purposes and for developing DL algorithms. Translational Relevance The medical image synthesis based on GANs is promising in humans and machines to fulfill clinical tasks.

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. Purpose:  To evaluate reading ability and stereoscopic vision with combined implantation of refractive and diffractive multifocal intraocular lenses (IOLs). Methods:  Thirty‐one cataract patients (62 eyes) were assigned to receive either a ReZoom NXG1 IOL in the dominant eye and a Tecnis ZM900 IOL in the fellow eye (MIOL group), or Sensar AR40e IOLs bilaterally (SIOL group). The uncorrected visual acuity (UCVA) at 500 cm, best spectacle‐corrected visual acuity (BSCVA) at 500 cm, reading acuity, reading speed, near stereoacuity and questionnaire were assessed 3 months postoperatively. Results:  Three months postoperatively, monocular and binocular UCVA and BSCVA at 500 cm showed no significant differences in both groups. The uncorrected reading acuity and reading speed in the MIOL group were significantly better than those in the SIOL group and were similar to that with correction in the SIOL group. The uncorrected mean near stereoacuity in the MIOL group was significantly better than that in the SIOL group (69 ± 50 seconds of arc in the MIOL group versus 180 ± 160 seconds of arc in the SIOL group). Patients in the MIOL group had a high level of satisfaction and more than 80% of them had an increased independence from spectacles for brief reading. Conclusion:  The combined implantation of refractive and diffractive multifocal IOLs was effective in improving reading ability and near stereoacuity with a good visual quality.