A method for classifying diabetic retina images based on deep learning includes: obtaining a fundus image; importing the same fundus image into a microhemangioma lesion recognition model, a hemorrhage lesion recognition model and an exudation lesion recognition model for recognition; extracting lesion feature information from the recognition results, and then using a trained support vector machine classifier to classify the extracted lesion feature information to obtain a classification result. The microhemangioma lesion recognition model is obtained by extracting a candidate microhemangioma lesion region in the fundus image and inputting it into a CNN model for training; the hemorrhage lesion recognition model and the exudation lesion recognition model are obtained by labeling a region in the fundus image as a hemorrhage lesion region and an exudation lesion region, and then inputting the result into an FCN model for training. A system for the same is also disclosed.
展开▼
