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.


  • Understand the basic principles behind leading generative AI algorithms
  • Learn about current and emerging applications of generative AI in medical imaging
  • Recognize benefits and limitations of using generative models for medical imaging data
  • Get inspired about how generative AI could be incorporated into your own research

Watch the Webinar for Free

CE Credit

SIIM has approved this activity for 1.0 hours of SIIM IIP Credits towards certification and re-certification by the American Board of Imaging Informatics (ABII).

To receive credit, registrants must view the entire webinar and then complete the post-webinar survey. Webinar credits will only be awarded one time per webinar view, regardless of if the learner watches the content live or on-demand.

Note: In order to receive credits for any events/learning you attend you must select your eligible credit types found in the CE & Certification section of your MySIIM Account profile.

To access the webinar, once you are registered navigate to My Learning in your My SIIM Account profile.    

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Aug 16, 2023

Credit Amount


Credit Type


Non-Member Cost


Member Cost


Delivery Type

  • On-Demand

Audience Type

  • Clinician
  • Developer
  • Imaging IT
  • Student Member in Training (SMIT)

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

Pouria Rouzrokh, MD, MPH, MHPE

Research Associate

Mayo Clinic, Moderator


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