Tumor radiotherapy control system and storage medium
A radiotherapy and storage medium technology, applied in the field of medical devices, can solve problems such as high planning cost, large variance in planning quality, fatigue, anxiety, etc., and achieve the effect of reducing planning cost, improving consistency, and shortening time
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Embodiment 1
[0037] image 3 is a schematic structural block diagram of a tumor radiotherapy control system provided by an embodiment of the present invention, such as image 3 As shown, the system includes a dose prediction module, a judgment module and an optimization adjustment module.
[0038] 1. The dose prediction module
[0039] The dose prediction module is used to input the image image of the patient and the structure set containing the boost target area, the tumor target area and the organ at risk in the image image into the dose prediction model, so as to use the dose prediction model to predict the tumor and the dose index received by organs at risk are predicted and processed.
[0040] In addition, the dose prediction module is also used to use historical data to train the dose prediction model to obtain a trained dose prediction model, so as to use the trained dose prediction model to perform prediction processing; wherein the historical data includes : The image image of ...
Embodiment 2
[0064] In order to overcome the disadvantages of unquantifiable target range, variable quality, and time-consuming defects in the design of P-SABR plans, the embodiment of the present invention applies deep learning to the design of clinical radiotherapy plans, and uses artificial intelligence to assist in the design of target volumes. In the P-SABR plan that has been designed in the past, the delineated range of the P-SABR boost target area and the dose data established by this target area and the set dose are saved, and the target area and dose of the previous P-SABR plan are calculated. In-depth learning to obtain a dose prediction model that can be used for radiotherapy dose prediction, and then use the computer's powerful calculation and self-learning capabilities to find the optimal target range that meets the dose limit, so as to automatically generate an optimized target target area and make the tumor The equivalent biological dose is greatly increased without increasin...
Embodiment 3
[0090] An embodiment of the present invention provides a storage medium, the storage medium stores one or more programs for tumor radiotherapy control, and the one or more programs can be executed by one or more processors to achieve the following: Figure 7 The following specific steps are shown:
[0091] Step S701: Input the patient's imaging image and the structure set containing the boost target volume, tumor target volume and organ-at-risk region in the imaging image into the dose prediction model, so as to use the dose prediction model to estimate the impact of the tumor and the organ-at-risk. The dose index for prediction processing.
[0092] Wherein, the imaging images include but not limited to CT imaging images and nuclear magnetic resonance images.
[0093] Wherein, the structure set including the boost target volume, tumor target volume and organ-at-risk regions in the image image is obtained after delineating the boost target volume, tumor target volume and organ...
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