Glasgow, United Kingdom

ESTRO 2024

Session

Sunday
May 05
08:45 - 10:00
Hall 3
QA of AI in the radiotherapy practice
Camilla Panduro Nielsen, Denmark;
Uulke van der Heide, The Netherlands
This symposium focusses on quality assurance of autosegmentation models and AI-based auto-planning for photon and proton therapy. How robust are they? Are they still adequate after a software update or a change in imaging device? During routine clinical application, do they behave as expected, and how can the clinical benefit be evaluated? What biases are introduced and does this change over time? The importance of estimating uncertainty of autosegmentations is discussed as well as the limitations of the Dice Similarity Coefficient. Finally, the question is considered if the dosimetric impact of contouring variations can be used to minimize manual corrections.
2120
Symposium
Physics
08:45 - 08:57
Auto-segmentation QA
Liesbeth Vandewinckele, Belgium
08:57 - 09:09
Quality check of auto-segmentation during clinical use
Tomas Janssen, The Netherlands
09:09 - 09:21
Diving deep into the uncertainty estimation methods for head and neck tumor auto-segmentation
Jintao Ren, Denmark
09:21 - 09:33
Autoplanning QA
Leigh Conroy, Canada
09:33 - 09:45
Dose predictions in all IMPT robustness scenarios with a single deep learning model
Hazem Nomair, The Netherlands
09:45 - 09:57
DIVE-ART: towards Dosimetrically Informed Volume Editions of automatically segmented volumes
Benjamin Roberfroid, Belgium