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Abdominal Radiology (New York)|April 28, 2025
Methodology for a fully automated pipeline of AI-based body composition tools for abdominal CTJohn W Garrett, Perry J Pickhardt, Ronald M Summers
Abdominal Radiology (New York)|May 14, 2024
Adjusting for the effect of IV contrast on automated CT body composition measures during the portal venous phaseAlexander R Moeller, John W Garrett, Ronald M Summers, et al.
European Radiology|July 12, 2024
AI-based abdominal CT measurements of orthotopic and ectopic fat predict mortality and cardiometabolic disease risk in adultsMatthew H Lee, Ryan Zea, John W Garrett, et al.
Abdominal Radiology (New York)|January 27, 2024
AI-generated CT body composition biomarkers associated with increased mortality risk in socioeconomically disadvantaged individualsMatthew H Lee, Ryan Zea, John W Garrett, et al.
European Radiology|June 4, 2024
Post-contrast CT liver attenuation alone is superior to the liver-spleen difference for identifying moderate hepatic steatosisPerry J Pickhardt, Glen M Blake, Alex Moeller, et al.
Abdominal Radiology (New York)|August 27, 2023
Artificial intelligence tool detection of intravenous contrast enhancement using spleen attenuationB Dustin Pooler, Cullen J Fleming, John W Garrett, et al.
Abdominal Radiology (New York)|March 5, 2026
Longitudinal evaluation of intra-patient changes in computed tomography-based body composition measuresB Dustin Pooler, John W Garrett, Matthew H Lee, et al.
AJR. American Journal of Roentgenology|April 25, 2023
Technical Adequacy of Fully Automated Artificial Intelligence Body Composition Tools: Assessment in a Heterogeneous Sample of External CT ExaminationsB Dustin Pooler, John W Garrett, Andrew M Southard, et al.
Radiology|April 28, 2026
CT-based Opportunistic Screening for Adding Clinical Value: How I Do ItPerry J Pickhardt, Mathew H Lee, Joshua D Warner, et al.
Abdominal Radiology (New York)|November 12, 2022
Fully automated CT-based adiposity assessment: comparison of the L1 and L3 vertebral levels for opportunistic predictionDaniel Liu, John W Garrett, Matt H Lee, et al.
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