Patent ID: 11880972
Assignee: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 19:
20. A method for tissue nodule detection, performed by a computer device, the method comprising:
obtaining a to-be-detected image; and
inputting the to-be-detected image into a tissue nodule detection model to obtain nodule location information, the tissue nodule detection model being obtained according to a tissue nodule detection model training apparatus,
wherein the tissue nodule detection model is trained by:
obtain 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 with no annotation, and the image annotation being used for indicating location information of a tissue nodule in the source domain image, wherein the source domain data is collected by a first type of device that is different from a second type of device that collects the target domain data, and wherein an image to be detected by the tissue nodule detection model is collected by the second type of device, wherein the first type of device and the second type of device are based on a same radiology technology and are different in at least one of following aspects: a brand name; a model; a sampling distance; a noise level; or a nodule diameter distribution;
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.