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Did you know?

Efficiency, speed, and accuracy are just the beginning.

When it comes to state-of-the-art functionalities and efficient workflows, RayStation®* is undoubtably a market leader. Clinics worldwide are utilizing RayStation for its unmatched adaptive therapy capabilities, advanced multi-criteria optimization tools, and wide range of particle therapy support features - for starters. But you may not know that our "total package" TPS possesses enormous untapped potential.

Did you know that deep learning segmentation in RayStation is now included in structure templates?

*Subject to regulatory clearance in some markets.

Fallback planning greatly reduces treatment delays in contingency situations 

Built upon the dose mimicking algorithm created by RaySearch, the fallback planning module allows users to automatically create contingency plans for any machines or modalities found within the department. Fallback plans are generated after plan approval, based on previously created protocols. If a machine is out of operation for any reason, fallback plans can be accessed and pushed via DicomRT to the R&V system. For safety assurance, fallback plan review and approval before use of the plan is needed.

  • Create a fallback plan that is saved until needed, such as in the event of machine outage.
  • Powerful tools in plan evaluation allow the user to combine treatments performed on different machines.
  • Can convert between different modalities and treatment techniques, e.g. can be used to convert proton or tomotherapy plans to VMAT, IMRT or 3D-CRT.
  • Atlas based auto segmentation, protocols, and fallback combined save 70% of planning efforts when a machine failure occurs

White paper: Fallback Planning

Click here to download and view

Structure template support allows for more concise treatment planning and enhanced focus on the most important ROI’s.

Simplify the way deep learning segmentation is applied in RayStation, and enhance automation of the patient modeling process. RayStation allows you to combine deep learning segmentation with model based segmentation and atlas based segmentation in a single template to further customize your clinical workflow, and optimize treatment personalization for your patients.
One system, endless possibilities.