Invention Grant
- Patent Title: Deep learning based dosed prediction for treatment planning and quality assurance in radiation therapy
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Application No.: US16558681Application Date: 2019-09-03
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Publication No.: US11615873B2Publication Date: 2023-03-28
- Inventor: Dan Nguyen , Steve Jiang
- Applicant: The Board of Regents of The University of Texas System
- Applicant Address: US TX Austin
- Assignee: The Board of Regents of The University of Texas System
- Current Assignee: The Board of Regents of The University of Texas System
- Current Assignee Address: US TX Austin
- Agency: DLA Piper LLP (US)
- Main IPC: G16H20/10
- IPC: G16H20/10 ; G06N5/04 ; G06N3/08 ; G06N3/04

Abstract:
A method and system for generating a treatment plan are disclosed herein. A computing system receives a plurality of dose volume histograms for a plurality of patients and a plurality of volumetric dose distributions corresponding to the plurality of dose volume histograms. The computing system generates a volumetric dose prediction model using a neural network by learning, by the neural network, a relationship between a plurality of dose volume histograms for the plurality of patients and the corresponding plurality of volumetric dose distributions. The computing system receives a candidate dose volume histogram for a target patient. The computing system infers, via the volumetric dose prediction module, a volumetric dose prediction distribution matching the candidate dose volume histogram. The computing system generates a recommendation based on the inferred volumetric dose prediction distribution.
Public/Granted literature
- US20200075148A1 DEEP LEARNING BASED DOSED PREDICTION FOR TREATMENT PLANNING AND QUALITY ASSURANCE IN RADIATION THERAPY Public/Granted day:2020-03-05
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