Tissue nodule detection and tissue nodule detection model training method, apparatus, device, and system

Abstract

This application relates to a tissue nodule detection and tissue nodule detection model training method, apparatus, device, storage medium and system. The method for training a tissue nodule detection model includes: obtaining source domain data and target domain data, the source domain data comprising a source domain image and an image annotation, the target domain data comprising a target image, and the image annotation being used for indicating location information of a tissue nodule in the source domain image; performing feature extraction on the source domain image using a neural network model to obtain a source domain sampling feature, performing feature extraction on the target image using the neural network model to obtain a target sampling feature, and determining a model result according to the source domain sampling feature using the neural network model; determining a distance parameter between the source domain data and the target domain data according to the source domain sampling feature and the target sampling feature, the distance parameter being a parameter describing a magnitude of a data difference between the source domain data and the target domain data; determining, according to the model result and the image annotation, a loss function value corresponding to the source domain image; and training the neural network model to obtain a tissue nodule detection model by iteratively reducing a combination of the loss function value and the distance parameter. In this way, the detection accuracy can be improved.