Implementing a simple, dynamic and controllable AI delineation tool in clinical settings

This paper describes some of the development, decisionmaking processes, and outcomes of implementing a locally hosted service for automatic segmentation, using in-house trained models complying with national and international guidelines, of medical scans in cancer radiation therapy. By integrating this service, we significantly reduce the time from scanning to treatment planning, as the system automates tasks traditionally performed manually, thereby reducing the need for manual editing. We detail the service's architectural structure, discussing critical decisions in its design and addressing the constraints posed by the hospital’s broader IT infrastructure. Our results highlight that automatic segmentation improves workload, and sheds light on practical considerations and challenges of embedding such technological solutions in a clinical setting.