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Using Monte Carlo dropout and bootstrap aggregation for uncertainty estimation in radiation therapy dose prediction with deep learning neural networks
Recently, artificial intelligence technologies and algorithms have becom...
11/01/2020 ∙ by Dan Nguyen, et al. ∙
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Using Deep Learning to Predict Beam-Tunable Pareto Optimal Dose Distribution for Intensity Modulated Radiation Therapy
We propose to develop deep learning models that can predict Pareto optim...
06/19/2020 ∙ by Gyanendra Bohara, et al. ∙
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A reinforcement learning application of guided Monte Carlo Tree Search algorithm for beam orientation selection in radiation therapy
Due to the large combinatorial problem, current beam orientation optimiz...
04/14/2020 ∙ by Azar Sadeghnejad Barkousaraie, et al. ∙
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Incorporating human and learned domain knowledge into training deep neural networks: A differentiable dose volume histogram and adversarial inspired framework for generating Pa
We propose a novel domain specific loss, which is a differentiable loss ...
08/16/2019 ∙ by Dan Nguyen, et al. ∙
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