Patent ID: 11972854
Assignee: OUR UNITED CORPORATION
Field: nan (nan)
Classification: CPC nan | IPC G

Claim 7:
8. A data processing method applied to a radiotherapy system, comprising:
acquiring, by a calibration database which is accessed to a clinical database through a preset database interface, in real time or periodically a plurality of the sample data generated in a clinical therapy process;
performing, by a training module which is connected to the calibration database through a preset interface, deep learning on any one of the plurality of sample data stored in a calibration database to obtain a therapy algorithm model, and sending the therapy algorithm model to a data processing module;
processing, by the data processing module, the detection data received in the clinical therapy process according to the therapy algorithm model to generate preliminary therapy data;
wherein each sample data comprises a set of detection data and a set of therapy data corresponding to the set of the detection data and applied to the clinical therapy process and the therapy data is verified in the clinical therapy process;
the clinical therapy process comprises a therapy plan generation stage, a pre-therapy positioning stage and an in-therapy monitoring stage;
in the therapy plan generation stage, the detection data comprises medical image data, the therapy data comprises a therapy plan, and the training module is configured to perform deep learning on the detection data and the therapy data generated in the therapy plan generation stage to obtain a therapy plan formulation model;
in the pre-therapy positioning stage, the detection data comprises medical image data acquired before the clinical therapy process and in the clinical therapy process, the therapy data comprises a positioning offset of a patient, and the training module is configured to perform deep learning on the detection data and the therapy data generated in the pre-therapy positioning stage to obtain a pre-therapy positioning model;
in the in-therapy monitoring stage, the detection data comprises a patient displacement, a tumor monitoring image, a remaining radiation dosage, the therapy data comprises a tumor displacement before and after therapy, a dosage error, and the training module is configured to perform deep learning on the detection data and the therapy data generated in the in-therapy monitoring stage to obtain a monitoring model;
the calibration database classifies and stores the detection data and the therapy data generated in the therapy plan generation stage, the pre-therapy positioning stage and the in- therapy monitoring stage;
receiving a feedback level of a specified sample data, wherein the feedback level is positively related to a therapeutic effect of therapy data in the specified sample data;
adjusting a weight value of the specified sample data according to the feedback level of the specified sample data, the adjusted weight value of the specified sample data being positively related to the feedback level of the specified sample data;
performing deep learning on sample data with the adjusted weight value; and
wherein:
the data processing module comprises an image registration sub-module, a delineation sub-module, a therapy plan formulation sub-module, a positioning sub-module and a monitoring sub-module;
the training module performs deep learning on a plurality of medical image data and registration images generated at an image registration stage to obtain a registration model; and the image registration sub-module processes medical image data acquired in the clinical therapy process according to the registration model and outputs a preliminary registration image;
the training module performs deep learning on the plurality of registration images and delineation result images generated at a delineation stage to obtain a delineation model; and the delineation sub-module processes registration images acquired in the clinical therapy process according to the delineation model and outputs a preliminary delineation result image;
the positioning sub-module processes the medical image data acquired at the image registration stage and the medical image data acquired at the pre-therapy positioning stage during the clinical therapy process according to the pre-therapy positioning model and outputs a preliminary positioning offset and
the monitoring sub-module processes the monitoring data acquired at the in-therapy monitoring stage of the clinical therapy process according to the monitoring model and outputs preliminary adjustment data.