Tooth disease classification method based on federated learning (fl)

Abstract

The present disclosure provides a tooth disease classification method based on federated learning (FL), including the following steps: S: acquiring oral information of a user; S: transmitting an oral dental image to a local server for preprocessing; S: performing, by the single local server, model training according to a preprocessed oral dental image set and a model of a cloud master server; S: transmitting trained model parameters to the cloud master server through digital encryption; and S: performing, by each of local servers, fusion and classification according to digitally decrypted model parameters from the cloud master server. The method provided by the present disclosure has accurate classification, does not need to centrally process data, and keeps the oral information strictly secret without privacy disclosure; and meanwhile, the method encrypts the model parameters to further ensure the security.