Join the Machine Learning in Medical Imaging Consortium (MaLMIC) for an opportunity to network on machine learning

Amir Jabbarpour,
PhD, Medical Physics Department, Carleton University

Amir Jabbarpour, PhD, is a medical physicist and AI researcher specializing in quantitative medical imaging, nuclear medicine, and clinically deployable artificial intelligence solutions. He recently earned his PhD in Medical Physics from Carleton University, where his research focused on advancing AI applications in ventilation/perfusion imaging. His work spans radiotherapy, CT, MRI, and cardiac and pulmonary nuclear medicine, with expertise in machine learning, medical image analysis, and healthcare software development. At The Ottawa Hospital, he led the development of large-scale medical imaging datasets and end-to-end AI pipelines for V/Q scintigraphy, supporting workflow automation and physician decision making. He is currently conducting research at the University of Ottawa Heart Institute, focusing on quantitative Rubidium-82 cardiac PET imaging. His interdisciplinary background combines medical physics, artificial intelligence, and software engineering to translate research innovations into practical clinical tools.

Talk Description: Amir’s talk introduces VQ-SPRINT, a new AI tool that helps doctors diagnose pulmonary embolism more quickly and consistently. Normally, this type of diagnosis relies on a lung scan that has to be carefully analyzed by hand—a process that takes time and can vary from one reader to another. VQ-SPRINT automates this work: it uses AI to spot problem areas in the lungs, creates easy-to-read images from the scan, and maps out exactly where the issues are, all in under 30 seconds. It then generates a clear summary and diagnostic impression that doctors can use directly. As the first tool to fully automate this process, VQ-SPRINT could help speed up diagnosis, make results more consistent across hospitals, and serve as a helpful teaching tool for medical trainees.

Eric Moulton,
PhD, Director, Artificial Intelligence, Jubilant Radiopharma

Eric Moulton is Director of Artificial Intelligence within the research and development team at Jubilant Radiopharma, a radiopharmaceutical company based in Kirkland, Quebec, where he leads the development and clinical translation of AI technologies for nuclear medicine and molecular imaging. He is also an Affiliate Researcher at the University of Ottawa Heart Institute and an Adjunct Professor in the School of Electrical Engineering and Computer Science at the University of Ottawa. His research is at the intersection of artificial intelligence and nuclear medicine for developing new software tools and finding new indications for radiopharmaceuticals. Dr. Moulton received his PhD in Neuroscience and Medical Imaging from Sorbonne Université in Paris, France and has authored numerous scientific publications on AI-enabled medical imaging and clinical decision support.

Talk Description: Eric’s talk explores how AI can get more value out of Rubidium-82, a substance already used in PET scans to check blood flow to the heart and diagnose coronary artery disease. Eric Moulton, from Jubilant Radiopharma, shares how his team built an AI method that creates detailed 3D blood flow maps, improving detection of heart disease beyond current standard methods. These maps also show promise for predicting risk of serious heart events and assessing the heart’s right side, not just the left. AI is also being used to automatically check scan quality and sharpen images, making the process smoother for hospitals. Overall, the talk shows how smart AI use can unlock more value from an already-approved tool, without needing a new drug.