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Machine learning

Treatment planning technology is evolving to meet the needs of our growing world population. We’ve developed machine learning tools capable of automating organ segmentation and treatment plan generation activities, improving efficiency and consistency in the treatment planning process. Almost 10 million people die from cancer annually and treatment planning with machine learning* is our latest contribution to the fight.

*Subject to regulatory clearance in some markets.

Key features

  • Generate personalized treatment plans in minutes
  • Create organ contours in less than one minute with deep neural network models
  • Benefit from validated models based on data from leading cancer clinics
  • Spend less time on repetitive tasks
  • Get more time for patient consultations and complex cases
 

WHITE PAPER: MACHINE LEARNING AUTOMATED TREATMENT PLANNING

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WHITE PAPER: MACHINE LEARNING DEEP-LEARNING

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“We know that the RayStation algorithm generates high quality treatment plans that are deemed clinically acceptable by world experts with the majority of cases we have formally studied, showing automated plans are preferred or deemed equivalent to clinical plans.”

Tom Purdie
Medical Physicist, Princess Margaret Cancer Centre, Canada

See the study "Clinical integration of machine learning for curative-intent radiation treatment of patients with prostate cancer" here

INTERVIEW WITH FREDRIK LÖFMAN AT ASTRO 2019

Physics World met up with us and Fredrik Löfman, who is heading up our Machine learning department. Here is what he had to say.