Rapid in vivo EPID image prediction using a combination of analytically calculated attenuation and AI predicted scatter.
Journal:
Medical physics
PMID:
39607282
Abstract
BACKGROUND: The electronic portal imaging device (EPID) can be used in vivo, to detect on-treatment errors by evaluating radiation exiting a patient. To detect deviations from the planning intent, image predictions need to be modeled based on the patient's anatomy and plan information. To date in vivo transit images have been predicted using Monte Carlo (MC) algorithms. A deep learning approach can make predictions faster than MC and only requires patient information for training.