Classification of retinal damage by a neural network based system.

The objective of this research is to provide an ophthalmologist with a helpful system, capable of classifying a degree of patients' retinal hemorrhage. The system is composed of four modules: (a) data acquisition module, (b) image Database module, (c) image processing module, (d) image classification module. The system was trained with a modular neural network on a set of 25 images, and tested on a set of 160 images. A training performance of greater than 95% was achieved. The classifying part of the system showed 79% recognition accuracy. Since the testing images were taken from independent sources, we assume that the system should also provide an accurate classification of other image types.