The utility model provides a fundus image lesion screening system which is characterized in that the fundus image lesion screening system comprises a storage module which is deployed in a cloud server; the acquisition module is used for acquiring more than two fundus images from different eyes of the same person and uploading the fundus images to the storage module; the input module is used for inputting examinee information corresponding to the fundus image, associating the examinee information with the fundus image and uploading the examinee information to the storage module; and the screening module is used for extracting the fundus image and the information of the examinee from the storage module, and automatically interpreting whether the associated fundus image has lesions or not byutilizing a deep learning method based on an artificial neural network so as to generate a screening result. According to the utility model, a deep learning method based on an artificial neural network can be used for assisting a doctor in judging lesion identification of the fundus image, so that the screening efficiency of fundus image lesions can be effectively improved.
Screening system for fundus image lesions