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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. 

 

A Very Special Thank You to Bracco and ACR Data Science Institute for Their Support of the 2020 SAR TANK!

 


 

SAR Tank 2020 Winners


 

SAR Tank 2020 Winner - Expert’s Choice
Expedited and Improved Detection of Thromboembolism on CT - Roshan Modi

 

SAR Tank 2020 Winner - People’s Choice
Building an Artificial Intelligence (AI) Use Case for Determining the Location and Likelihood of Clinically Significant Prostate Cancer using mpMRI – Masoom Haider & Baris Turkbey

 

SAR Tank 2020 Runner Up
AI TI-RADS Classifier & Automated Recommendations for Thyroid Nodules - Ben Wildman-Tobriner

 

SAR Tank 2020 Honorable Mentions

 

Outstanding submissions given Honorable Mention were invited to submit a video presentation to experts around the world showing that their idea is worth working, not 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


 

 

SAR AI Masters Class

The SAR 2020 AI Masters Class material is located here: https://github.com/abdominalradiology


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