Abstract
In this work we present a framework for robust deep learning-based VMAT forward dose calculations for the 1.5T MR-Linac. A convolutional neural network was trained on the dose of individual multi-leaf-collimator VMAT segments and was used to predict the dose per segment for a set of MR-Linac-deliverable VMAT test plans.
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