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Attention-aware 3D U-Net convolutional neural network for knowledge-based planning 3D dose distribution prediction of head-and-neck cancer.

Alexander F I OsmanNissren M Tamam
Published in: Journal of applied clinical medical physics (2022)
The attention-gated 3D U-Net model demonstrated a capability in predicting accurate 3D dose distributions for head-and-neck IMRT plans with consistent quality. The prediction performance of the proposed model was overall superior to a baseline standard U-Net model, and it was also competitive to the performance of the best state-of-the-art dose prediction method reported in the literature. The proposed model could be used to obtain dose distributions for decision-making before planning, quality assurance of planning, and guiding-automated planning for improved plan consistency, quality, and planning efficiency.
Keyphrases
  • convolutional neural network
  • deep learning
  • decision making
  • systematic review
  • healthcare
  • machine learning
  • high throughput
  • quality improvement
  • health insurance