Plan implementation method and device based on predicted dose guidance and Gaussian process optimization

Abstract

The invention provides a plan implementation method and apparatus based on predicted dose guidance and Gaussian process optimization, and relates to the field of radiotherapy technology. The method comprises: calculating a predicted dose of a case by using a dose prediction model; calculating a plan score of the predicted dose according to the scoring rule as an optimal plan score; determining a plurality of sets of plan parameters based on the a priori database according to organ anatomy information; calculating corresponding plan scores of the plurality of sets of plan parameters, and constituting a Gaussian data set; and based on the Gaussian data set, calculating new plan parameters by using the Gaussian process, calculating the corresponding plan scores, adding the calculated scores to the Gauss data set, iteratively executing the step, and finally calculating the intensity-modulated optimization results under the plan parameters corresponding to the highest score in the Gauss data set. By the use of the predictive model to predict the dose distribution of the case to optimize the guidance, the quality of the plan is guaranteed, and by the use of the Gaussian process to calculate the posterior distribution based on the a priori data, the number of trial and error is reduced, thereby speeding up the optimization.

Description

technical field [0001] The invention relates to the technical field of radiotherapy, in particular to a method and device for implementing a plan based on predictive dose guidance and Gaussian process optimization. Background technique [0002] At present, intensity-modulated radiotherapy technology has been widely used clinically, but there are still many problems in the design method of treatment plan as its core. The current manual trial and error method seriously limits the work efficiency of the hospital and the cost of completing the plan, increasing burden on hospitals and patients. More importantly, the quality of the treatment plan obtained by such a planning method has great uncertainty, which largely depends on the experience of the plan designer and the time spent in designing the treatment plan. At the same time, according to the research reports of different treatment centers, it can be found that there are great differences in the quality of plans and the tim...

AI Technical Summary

Problems solved by technology

[0007] The purpose of the present invention is to provide a plan implementation method and device based on pre

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