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This webinar aims to provide attendees with an overview of the potential applications and considerations surrounding the use of generative AI techniques in medical imaging. Without presuming extensive technical expertise, the session will introduce prominent generative models such as GANs and diffusion models and how they may be utilized to enhance medical images.
Discussion will focus on realistic use cases such as reconstruction, segmentation, and synthesis, while also exploring challenges including validation, transparency, and responsible development. Expert speakers will outline best practices for rigorous testing and appropriate oversight if leveraging these algorithms in a clinical setting.
The webinar will supply professionals with an informed perspective on how generative AI may positively impact patient care in radiology and medical imaging, if thoughtfully implemented. Participants can expect to leave with an appreciation of the technology's promise and perils.
Objectives:
1. Understand the basic principles behind leading generative AI algorithms
Learn about current and emerging applications of generative AI in medical imaging
2. Recognize benefits and limitations of using generative models for medical imaging data
3. Get inspired about how generative AI could be incorporated into your own research
Speakers:
Akshay Chaudhari, PhD, Assistant Professor of Radiology, Stanford University
Judy Gichoya, MD, MS, Assistant Professor of Radiology, Emory University
Bardia Khosravi, MD, MPH, MHPE, Research Fellow, Mayo Clinic
Moderator:
Pouria Rouzrokh, MD, MPH, MHPE, Research Associate, Mayo Clinic
Watch for IIP Credit on SIIM.org.