Session Item

In this presentation the practical clinical implementation of deep learning (DL) based segmentation and planning for breast cancer treatment planning will be discussed. It will include all steps that one would need to take to use DL in clinical practice: pre-clinical training, evaluation and testing when building your own model or testing of a commercial model.  Setting standards for comparisons with your own clinical data, both quantitatively and qualitatively, which includes e.g., DVH criteria, possible time gains, fraction of plans or segmentations that still need to be adjusted etc. Documentation for commissioning and the Medical Device Regulations, education and monitoring during clinical use. The changing roles of radiation oncologists, RTT and medical physicists will also be discussed.