Background and Motivation:
Not all treatment centres will have access to upright imaging modalities, so there is a critical need for alternative approaches. Developing a versatile image guidance workflow, empowered by robust deformable image registration and associated algorithms for generating supine-to-upright image transformations, will be vital to ensure accurate treatment planning in centres with limited resources.
Goal:
A comprehensive multi-modality image-guided workflow, establishing treatment planning, robustness, and margin guidelines based on the gathered upright imaging data and numerical phantom
Tasks:
Project 16, ‘Multimodal Imaging for Upright Posture’, is carried out by Ronja Stern at the Paul Scherrer Institute (PSI) in Switzerland. She began her PhD in September 2025, under the supervision of Dr Ye Zhang, a tenured scientist at the Centre for Proton Therapy (CPT) at PSI.
Having obtained a Bachelor’s degree in Computer Science (University of Bern) and a Master’s degree in IT & Cognition (University of Copenhagen), Ronja’s goal is to develop AI-driven methods for upright proton therapy.
She is a disciplined, dedicated and curious researcher who is eager to learn and understand how things work, from the highest conceptual level to technical implementation.
Drawing on her background in computer science, she is developing AI-driven methods that combine multimodal imaging, motion modelling, and treatment adaptation.
The aim is to create more accurate and efficient patient-specific workflows, from image synthesis and registration to dose prediction. In doing so, she is bridging the gap between her theoretical knowledge and real-world clinical applications that could one day benefit patients.
She is eager to gain a deeper understanding of the field, establish a professional network across Europe, and collaborate with experts from various institutions.
In her free time, she enjoys playing sports such as badminton, skiing and cycling.
Additional:
