The Study on Predicting Respiratory Motion with Support Vector Regression

Objective: The target is usually tracked in real time at thoracic and abdominal radiotherapy due to the effect of respiratory motion, the prediction is necessary to compensate the system latency. Method: This paper proposed a prediction method based on support vector regression, it dynamically updates the training set and achieves the accurate online support vector regression. Result: The experiment selected seven respiratory motion data, using online model trained and predicted. The mean absolute error was 0.30mm. Conclusion: The online accurate support vector regression described respiratory motion accurately, and the results with high precision can be satisfied in practical application.