Fluence map prediction and treatment plan generation for automatic radiation treatment planning

US12128250B2 · kind B2 · utility

Assignees

• Duke University · US
• The University Of North Carolina At Charlotte · US

Inventors

• Qingrong Jackie Wu · Chapel Hill, US
• Yaorong Ge · Winston-Salem, US
• Fang-Fang Yin · Durham, US
• Qiuwen Wu · Durham, US
• Chunhao Wang · Durham, US
• Yang Sheng · Durham, US
• Xinyi Li · Beijing, CN
• Wentao Wang · Tallahassee, US

Key dates

• Filing date: Feb 1, 2022
• Grant date: Oct 29, 2024
• Expiry date: Dec 15, 2042

Classification

• Technology area (CPC A): Human Necessities
• CPC primary: A61N5/1039
• WIPO field: Medical technology
• WIPO sector: Instruments

Abstract

A radiation treatment planning system can include a machine learning system that receives patient data, including an image scan (e.g., CT scan) and contour(s), a physician prescription, including planning target and dose, and device (radiation beam) data and outputs predicted fluence maps. The machine learning system includes at least two stages, where a stage of the at least two stages includes converting image scans from the patient data to projection images. A treatment planning system can receive the predicted fluence maps and generates treatment plans without performing inverse optimization.