Other Workshop: The Role and Potential of AI and Quantum Computing in Radiotherapy
04-06-2026 12:00 pm Add to iCal
This workshop explores how AI and quantum computing are reshaping the landscape of radiotherapy, from treatment planning and imaging to personalised patient care and optimisation of clinical workflows.
Organiser: Region Stockholm and The University Alliance Stockholm Trio, a partnership between Karolinska Institutet, KTH Royal Institute of Technology and Stockholm University.
The event aims to bridge the gap between clinical practice and emerging computational technologies, offering an interdisciplinary forum for clinicians, physicists, engineers, and researchers to exchange ideas and foster collaborations.
Key Topics
- AI-driven image segmentation, dose prediction, and adaptive planning
- Radiomics and predictive modelling for personalised treatment response
- Deep learning architectures for medical imaging and treatment planning
- Data quality, bias, and ethics in AI-driven radiotherapy
- Quantum algorithms for optimisation problems in radiotherapy planning
- Quantum machine learning, emerging applications in oncology
Target Audience
Clinical oncologists, radiation oncologists, medical physicists, data scientists, AI and quantum-computing researchers, biomedical engineers, and PhD students working at the interface of medicine, physics, and computer science.
For questions about the scientific programme, registration, or practical arrangements, please contact:
- Iuliana Toma-Dasu iuliana.livia.dasu@ki.se
- Kristina Viktorsson kristina.viktorsson@ki.se, Mobile: +46 703 38 35 13
- Helena Zander Ögren helena.zander.ogren@ki.se
Programme
Day 1: AI in Radiotherapy Research and Practice
08:30–09:00
Registration
09:00–09:15
Welcome and introduction
On behalf of the organising committee: Iuliana Toma-Dasu and Kristina Viktorsson
09:15–10:00
Keynote Lecture
Quantum Machine Learning in Radiotherapy – the Path to Successful Implementation and Beyond
Speaker: Issam El Naqa, Moffitt Cancer Center, Department of Machine Learning, Tampa
10:00–11:30 | Session 1: Thematic Lectures
Radiomics and Predictive Modelling for Personalized Treatment Response
Chair: Marta Lazzeroni
- Beyond Radiomics: Spatial Patterns in MRI for Glioma Genotype Prediction
Speaker: Mehdi Astaraki, Stockholm University (Medical Radiation Physics) and Karolinska Institutet (Department of Oncology-Pathology)
10:20–10:40 – Coffee break
- Radiomics in the Age of Causal AI: Moving Beyond Prediction
Speaker: Shayan Mostafaei, Karolinska Institutet, Department of Medical Epidemiology and Biostatistics - Agentic AI in Radiotherapy: From AI Model Development to Radiobiological Evaluation
Speaker: Eleftherios Tzanis, University of Crete (School of Medicine, Department of Radiology, ATI Lab) and Karolinska Institutet (Department of Clinical Science, Intervention and Technology, Division of Radiology)
11:30–12:30 | Session 2: Case Studies
Implementation of AI Tools in Clinical Workflows
Chair: Rolf Lewensohn
- Implementing AI in Lung Cancer Imaging: From Screening to Clinical Decision-Making
Speaker: Vitali Grozman, Karolinska Institutet (Department of Molecular Medicine and Surgery) and Karolinska University Hospital (Thoracic Radiology) - Karolinska Experience on Organ-at-Risk Delineation in Head-and-Neck Cases Using a Commercial Auto-Contouring Software
Speaker: Laura Gallo, Karolinska University Hospital, Theme Cancer, Medical Unit Radiotherapy - Clinical Implementation of a Deep Learning Synthetic CT Solution for Radiotherapy Treatment of Glioblastoma
Speaker: Fernanda Villegas-Navarro, Karolinska Institutet (Department of Oncology-Pathology) and Karolinska University Hospital (Radiotherapy Physics and Engineering, Nuclear Medicine and Medical Physics) - Auto-Segmentation of CTV and OOIs in Breast Cancer Irradiation
Speaker: Pehr Lind, Karolinska Institutet (Department of Clinical Science and Education, Södersjukhuset) and Södersjukhuset (Department of Radiation Therapy)
12:30–14:00
Lunch
14:00–15:00 | Session 3: Thematic Lectures
Deep Learning Architectures for Medical Imaging and Treatment Planning
Chair: Chunliang Wang
- Deep Learning for Target Tumor Segmentation
Speaker: Mehdi Astaraki, Stockholm University and Karolinska Institutet - From Images to Tissue Mechanics: AI and MRI Transforming Brain Imaging
Speaker: Rodrigo Moreno, KTH Royal Institute of Technology, Biomedical Imaging - Deep Learning-Based Treatment Planning
Speaker: Attila Simko, Umeå University, Faculty of Medicine, Department of Diagnostics and Intervention
15:00–15:30
Coffee break
15:30–16:00
Panel Discussion
Moderator: Mehdi Astaraki
Data Quality, Bias, and Ethics in AI-Driven Radiotherapy
Moderated panel with Day 1 speakers
Day 2: Quantum Computing in Medical Physics
08:30–09:00
Arrival and coffee
Session 4
09:00–09:15
- Introduction - Quantum Computing Meets Medical Physics: Setting the Stage
Speaker: Iuliana Toma-Dasu, Stockholm University (Medical Radiation Physics) and Karolinska Institutet (Department of Oncology-Pathology)
09:15–10:00
Keynote Lecture
- Quantum Computing for Radiation Therapy Optimization
Speaker: Robabeh Rahimi, University of Maryland School of Medicine (Department of Radiation Oncology) and Maryland Proton Treatment Center
10:00–10:15
Coffee break
10:15–11:00 | Session 5: Thematic Lecture
Chair: Kristina Viktorsson
- Quantum Technology Alliance: From Fundamental Science to Future Applications (QUANTA)
Speaker: Anders Karlhede, Stockholm University, Department of Physics - Quantum Computing for Radiotherapy Planning: A Feasibility Study
Speaker: Jonas Gårding, Elekta, Global Director Partner Research
11:00–11:30
Roundtable Discussion
Bridging AI and Quantum Computing: Future Research Collaborations
Moderated discussion with invited speakers
Moderator: Iuliana Toma-Dasu
11:30–12:00
Closing remarks and networking
Organising Committee
12:00–13:00
Lunch