A federated learning-based CT image detection method and a related device, applicable in eHealth. The method comprises: first devices train a first model on the basis of first data to acquire a trained first model and first model parameters (S201); the first devices transmit the first model parameters to a second device; the first devices receive a first average and a second average transmitted by the second device (S205); the first devices update the first model parameters on the basis of the first average and of the second average according a preset rule, then retrain the first model on the basis of a first type of CT images to acquire a trained second model and second model parameters (S206); and the first devices mark an abnormal area of an input CT image on the basis of the second model. The method provides, by means of a federated learning modeling method, the possibility for different platforms to collaborate, and employs a novel compression algorithm, thus effectively increasing the efficiency of communication.
FEDERATED LEARNING-BASED CT IMAGE DETECTION METHOD AND RELATED DEVICE