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This page provides a high-level overview of Rad-Plan.
For detailed technical, clinical, and product information, visit our main website.
AI-powered radiotherapy planning that standardizes quality, accelerates optimization, and improves organ-at-risk protection.
Radiotherapy planning today relies heavily on manual trial-and-error, with plan quality varying between planners, optimization being time-consuming, and achieving consistent OAR sparing remaining a challenge. As a result, planners spend significant time iterating without a reliable starting point, motivating the need for an intelligent system that translates patient geometry into clinically achievable optimization objectives.
Outcomes depend strongly on individual experience, leading to variability in plan quality.
Repeated manual tuning of objectives slows workflows and increases planning time.
Achievable dose fall-off is often unknown upfront, resulting in unrealistic constraints.
An intelligent planning assistant generating realistic, patient-specific optimization objectives.
Patient-specific objectives, reduce planner-to-planner variability and raise the baseline of the plan quality.
High-quality starting objectives minimize iterations and speed convergence.
Patient-specific dose distribution represented by optimal optimization parameters.
Planners fine-tune constraints instead of rebuilding plans from scratch.
This page provides a high-level overview of Rad-Plan.
For detailed technical, clinical, and product information, visit our main website.