Purpose: Deep learning-based knowledge-based planning (KBP) methods have been introduced for radiotherapy dose distribution prediction to reduce the planning time and maintain consistent high-quality plans. This paper presents a novel KBP model using an attention-gating mechanism and a three-dimensional (3D) U-Net for intensity-modulated radiation therapy (IMRT) 3D dose distribution prediction in head and neck cancer.

The datasets can be found in the OpenKBP - 2020 AAPM Grand Challenge repository at https://competitions.codalab.org/competitions/23428.

Please cite this paper: Osman AFI, Tamam NM. Attention-aware 3D U-Net convolutional neural network for knowledge‐based planning 3D dose distribution prediction of head and neck cancer. Appl Clin Med Phys. 2022;e13630. https://aapm.onlinelibrary.wiley.com/doi/10.1002/acm2.13630