The purpose of this project is to collect a large ocular images dataset to be used to develop Artificial Intelligence (AI) systems to server an early detection for any ocular diseases. The aim is to decrease blindness rates and promoting better vision quality. The developed systems will contribute in early disease detection and maximizing the accuracy of diagnosis and treatment decisions and reduces the burdens on medical professionals. Two different Optical Coherence Tomography (OCT) machines at the retina and glaucoma clinics in King Abdulaziz Medical City in Riyadh, Saudi Arabia were used to collect the images and the associated clinical information. A total of 58114 retinal images for 4863 patients, 2394 are male and 2469 are female, for the age between 4 to 99 years old captured between the period of 2007- 2021. whereas 40722 images were extracted from Heidelberg Engineering OCT and 17392 images extracted from Topcon OCT. The images will be visually and manually labeled and annotated respectively by multiple specialized ophthalmologists. The developed AI systems will serves the population and health care system in early detection of preventable blinding diseases. Moreover, these systems will reduce the high cost of the late ocular diseases detections. The updated information regarding the data will be available through the link: https://kaimrc.med.sa/?page_id=11767072
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