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. Plan quality varies between planners, optimization is time-consuming, and achieving consistent OAR sparing remains a challenge.
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.
Rad-Plan is an intelligent planning assistant integrated into the radiotherapy workflow, generating realistic, patient-specific optimization objectives.
Geometry-driven objectives reduce variability and raise baseline plan quality.
High-quality starting objectives minimize iterations and speed convergence.
Patient-specific dose fall-off estimation improves sparing without compromising targets.
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.
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Contact ahmad@radplan.ai