Inspired by the success of CNNs in identifying retinal entities associated with ocular diseases such as diabetic retinopathy, this study implemented a CNN architecture for ocular toxoplasmosis image classification. For this project, three sources of images were merged to create a dataset of 2464 retinal images, of which 2079 are healthy and 385 are unhealthy.
grant 2022/11378-3, São Paulo Research Foundation (FAPESP)