Description:
We are pleased to invite you to a series of webinars on artificial intelligence (AI) for medical physicists organized under IAEA Technical Cooperation Project RAS6109-Improving the Quality and Safety of Diagnostic and Interventional Radiology Services to Benefit Health Care by Enhancing the Status, Knowledge and Skills of Medical Physicists (RCA) and hosted by the Dosimetry and Medical Radiation Physics Section, Division of Human Health, IAEA.
As the integration of AI into medical imaging and radiation therapy continues to grow, ensuring its safe and effective implementation in clinical practice becomes increasingly critical. Given the essential role of medical physicists in the selection, deployment, and use of AI systems in clinical settings, this series of webinars aims to provide a comprehensive understanding of AI technologies. Its objective is to equip medical physicists with the knowledge necessary to support the introduction of imaging-based AI systems with the appropriate level of rigor and thoughtful consideration.
Tailored for medical physicists working in medical imaging and radiotherapy having interest in imaging-based AI systems, the sessions will feature expert-led presentations followed by a live discussion.
Learning Objectives:
By the end of this series, participants will be able to:
- Understand the basis of AI in medical imaging and explain key concepts, terminology, and types of AI technologies relevant to medical imaging and radiation therapy;
- Understand a need for safe and effective integration of AI systems aligned with clinical needs and regulatory requirements and appropriate quality assurance to verify the performance and reliability of AI systems over time;
- Promote ethical and responsible use of AI.
Presenters:
Maryellen L. Giger, Ph.D: is the A.N. Pritzker Distinguished Service Professor of Radiology, Committee on Medical Physics, and the College at the University of Chicago, USA. She is also the Vice-Chair of Radiology (Basic Science Research) and the immediate past Director of the CAMPEP-accredited Graduate Programs in Medical Physics/ Chair of the Committee on Medical Physics at the University. She is a former president of the American Association of Physicists in Medicine (AAPM) and a former president of the SPIE (the International Society of Optics and Photonics), and was the inaugural Editor-in-Chief of the SPIE Journal of Medical Imaging. She is contact PI on the NIBIB-funded Medical Imaging and Data Resource Center (MIDRC; midrc.org), which has ingested more than 500,000 medical imaging studies, with currently more than 190,000 imaging studies publicly available for use by AI investigators. For over 30 years, she has conducted research on computer-aided diagnosis, including computer vision, machine learning, and deep learning, in the areas of breast cancer, lung cancer, prostate cancer, brain injury, lupus, and bone diseases, and COVID-19. She has more than 300 peer-reviewed publications and has more than 30 patents, and has mentored over 120 graduate students, residents, medical students, and undergraduate students.
Andre Dekker, Ph.D: is a full professor of Clinical Data Science and board certified Medical Physicist at Maastro Clinic, Maastricht, The Netherlands. His previous positions include Manager of Research and Education, head of IT and head of Medical Physics. He has served on advisory boards of organizations, including the European Society for Radiotherapy & Oncology, MD Anderson, Luxemburg National Research Fund and Peter Munk Cardiac Centre. His main research areas are: building global FAIR data sharing infrastructures; using AI to learn health state prediction models from this data; and applying AI driven prediction models to improve health. His Clinical Data Science group spans multiple entities including Maastricht University, Maastricht University Medical Centre and Maastro Clinic. He has published over 300 peer-reviewed publications and patents and mentored more than 50 PhD students.
Alex Zwanenburg, Ph.D: is a researcher at the National Center for Tumor Diseases (NCT/UCC) Dresden, Germany, and OncoRay – National Center for Radiation Research in Oncology, Dresden Germany. His main research interest is the clinical translation of imaging-based AI tools. He founded the Image Biomarker Standardisation Initiative which has released two widely accepted reference standards for making radiomics software reproducible. He has published over 45 peer-reviewed articles (h-index 28), developed several open-source software packages, and mentored 14 PhD students. He teaches foundations of medical imaging and data science fundamentals.
Ashish Kumar Jha, Ph.D: is Assistant Professor and Scientific Officer at Tata Memorial Hospital, Parel, Mumbai, Maharashtra, India. He has two decades of experience in nuclear medicine as a clinical medical physicist, scientist, and educator. He has contributed as a task force member to several key organizations, including the Quality Council of India (QCI), the Bureau of Indian Standards (BIS), the National Commission of Allied and Healthcare Professions (NCAHP), the Atomic Energy Regulatory Board (AERB) India, the Ministry of Health and Family Welfare of the Government of India, and the National Cancer Grid (NCG). For several years, he has also served in various capacities within the Society of Nuclear Medicine in India (SNMI), the Nuclear Medicine Physicist Association in India (NMPAI), the Nuclear Cardiology Society of India (NCSI), and the Indian College of Nuclear Medicine (ICNM). His main research areas are radiomics, the implementation of artificial intelligence in oncology, medical instrumentation, and radiation dosimetry. He has published over 150 peer-reviewed articles/abstracts and mentored more than 100 postgraduate students.
Register Here
- Episode 1: 14th October 2025, 21:00 - 22:30 - Introduction to AI, historical background and terminology.
- Episode 2: 28th October 2025, 22:00 - 23:30 - Roles & Responsibilities of medical physicists in AI.
- Episode 3: 11th November 2025, 22:00 - 23:30 - Overview of basic and advanced statistical methods.
- Episode 4: 25th November 2025, 22:00 - 23:30 - Ethical and regulatory considerations relevant to the AI systems.
- Episode 5: 9th December 2025, 22:00 - 23:30 - Machine learning models, training and validation.
- Episode 6: 13th January 2026, 22:00 - 23:30 - Deep learning architecture.
- Episode 7: 27th January 2026, 22:00 - 23:30 - Data management.
- Episode 8: 10th February 2026, 22:00 - 23:30 - Clinical implementation of imaging-based AI systems.
- Episode 9: 24th February 2026, 22:00 - 23:30 - Overview of diagnostic radiology procedures utilising AI.
- Episode 10: 10th March 2026, 22:00 - 23:30 - Overview of imaging-based AI systems in radiotherapy.
- Episode 11: 24th March 2026, 22:00 - 23:30 - Radiomics for medical physicists.
- Episode 12: 7th April 2026, 20:00 - 21:30 - Medical Physicist role in clinical validation of AI technologies in imaging.
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