The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Purpose To determine if the performance of a knowledge based RapidPlan (RP) planning model could be improved with an iterative learning process, i.e. if plans generated by an RP model could be used as new input to re-train the model and achieve better performance. Methods Clinical VMAT plans from 83 patients presenting with head and neck cancer were selected to train an RP model, CL-1. With this...
Background To evaluate a knowledge based planning model for RapidPlan (RP) generated for advanced head and neck cancer (HNC) patient treatments, as well its ability to possibly improve the clinical plan quality. The stability of the model was assessed also for a different beam geometry, different dose fractionation and different management of bilateral structures (parotids). Methods Dosimetric and...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.