A Convolutional Neural Network approach for classifying leukocoria

We use Convolutional Neural Networks to detect leukocoria, or white-eye reflections, in recreational photography. Leukocoria is the most prominent symptom of retinoblastoma, a solid-tumor cancer of the eye that occurs most often in young children. We trained several networks for the task, using training images downloaded from Flickr. We achieved low error rates (<;3%) for classification of eye images into three classes: normal, leukocoric, and pseudo-leukocoric. We also provide a method for tuning the outputs of a trained network to match desired true-positive/false-positive rates.