Using Monte Carlo dropout and bootstrap aggregation for uncertainty estimation in radiation therapy dose prediction with deep learning neural networks.
Dan NguyenAzar Sadeghnejad-BarkousaraieGyanendra BoharaAnjali BalagopalRafe McBethMu-Han LinSteve B. JiangPublished in: CoRR (2020)
Keyphrases
- monte carlo
- radiation therapy
- deep learning
- neural network
- confidence intervals
- prostate cancer
- treatment planning
- ct images
- image guided
- deformable registration
- markov chain
- unsupervised learning
- machine learning
- normal tissue
- pattern recognition
- computer aided
- treatment plan
- particle filter
- mental models
- decision making
- medical imaging
- weakly supervised
- maximum likelihood
- decision support system
- medical images
- image registration
- multiscale
- cancer patients
- image segmentation