REAL-TIME ANATOMIC POSITION MONITORING IN RADIOTHERAPY USING MACHINE LEARNING REGRESSION

Systems and methods are disclosed for monitoring anatomic position of a human subject for a radiotherapy treatment session, based on use of a regression model trained to estimate movement of a region of interest based on 2D image data input. Example operations for movement estimation include: obtain...

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Bibliographic Details
Main Authors Novosad, Philip P, Beriault, Silvain
Format Patent
LanguageEnglish
Published 03.11.2022
Subjects
CALCULATING
COMPUTING
COUNTING
ELECTROTHERAPY
HUMAN NECESSITIES
HYGIENE
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
MAGNETOTHERAPY
MEDICAL OR VETERINARY SCIENCE
PHYSICS
RADIATION THERAPY
ULTRASOUND THERAPY
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Summary:Systems and methods are disclosed for monitoring anatomic position of a human subject for a radiotherapy treatment session, based on use of a regression model trained to estimate movement of a region of interest based on 2D image data input. Example operations for movement estimation include: obtaining 3D image data for a subject, which provides a reference volume and at least one defined region of interest; obtaining 2D image data corresponding to the subject, captured in real time (during the radiotherapy treatment session); extracting features from the 2D image data; analyzing the extracted features with a machine learning regression model, trained to estimate a spatial transformation in the three dimensions of the reference volume; and outputting and using a relative motion estimation of the at least one region of interest, produced from the machine learning regression model, the relative motion estimation being estimated from the extracted features.
Bibliography:Application Number: US202117302252