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ETC on Artificial Intelligence (AI)

Thank you to all who participated in the SAR AI Challenge!


The AI Challenge received over 50 submissions encompassing 30 institutions and 4 countries.  Each submission was reviewed by members of the AI ETC for technical innovation and feasibility and the relevant DFP members for potential impact.  The reviewers were blinded and over 70 of them were involved in the scoring.  This challenge has generated tremendous discussion, education and excitement around AI for all abdominal imaging. 


The top 3 finalists have been preparing to present to the panel judges and LIVE audience at the SAR TANK challenge on Tuesday March 3rd at the annual meeting in Maui!


Our top 3 finalists set to present to the SAR tank are Dr. Roshan Modi, Dr. Baris Turkbey and Dr. Ben Wildman-Tobriner!


Outstanding submissions given Honorable Mention were invited to submit a video presentation to experts around the world showing that their idea is worth workingnot just because of the clinical needs but that the application of AI to this problem will be successful as well!


Please enjoy the SAR AI Video Library below!


AI Guidance for Appropriate Imaging Protocols

Dr. Frank Miller

Northwestern University

Use of artificial intelligence for body composition assessment and osteopenia screening in all abdominal CTs

Dr. Alexander Goehler

Beth Israel Deaconess Medical Center, Harvard Medical School

Automated 3D-volumetric measurement of cystic pancreatic lesions on abdominal MRI: improving accuracy and efficiency with artificial intelligence

Dr. Alexander Goehler

Beth Israel Deaconess Medical Center, Harvard Medical School


Prostate cancer detection, rad-path correlated categorization, and prioritization

Dr. Yibo Chen

Naval Medical Center Portsmouth (NMCP)

AI Augmentation of LI-RADS for Improved Classification of HCC and Liver Malignancies

Dr. Carl Sabottke

Louisiana State University, University Hospital and Clinics Lafayette

Shear Wave Elastography Optimization for Hepatic Fibrosis Detection and Quantification Using Advanced Machine Learning Image Processing


Dr. Theodore Pierce


Massachusetts General Hospital


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