Conference on Artificial Intelligence in Medical Imaging

Advancing Opportunistic Detection of Osteoporosis Through AI-Driven CT Segmentation 

• Amy MiHyun Jang, University of Pennsylvania, Perelman School of Medicine 
• Jeffrey T. Duda, PhD; Arijitt Borthakur, PhD, MBA; James C. Gee, PhD; Christopher C. Carson, PhD; Anurag Verma, PhD; Daniel J. Rader, MD; Charles E. Kahn, MD, MS, FSIIM; Walter R. Witschey, PhD; Hersh Sagreiya, MD 

 

An Explanatory Deep Learning Model for the Prediction of Biologically Relevant Gene Expression in Non-small Cell Lung Tumors and their Microenvironment 

• Vibha Rajesh Rao, Dartmouth Health 
• Adrienne A. Workman; Liang Lu; Xiaoying Liu, MD; Shrey S. Sukhadia, PhD 

 

Applying a Pediatric Liver Fibrosis Classification Tool to Adult Trichrome-Stained Liver Biopsies: A Validation Study 

• Zachary Taylor, Cincinnati Children's Hospital 
• Anas Bernieh; Sarangarajan Ranganathan, MD, MBBS; Christopher Woods; Madhieh Shabanian, MS; Jennifer Picarsic, MD; Elanchezhian Somasundaram, PhD; Jonathan Dillman, MD, MSc 

 

Deep Learning for Automated Aortic Valve Calcium Scoring on Non-Gated Chest CT 

• Chanon Chantaduly, BA, University of California, Irvine 
• Shawn Sun, MD; Justin Grant, MD; Long-Co Nguyen, MD; Parker Rushworth, MD; Raffi Hagopian, MD; Jennifer Xu, MD; Peter D. Chang, MD 

 

Discordance Analysis Between Automated Cardiothoracic Ratio Measurements and NLP-Extracted Cardiomegaly Labels 

• Frank Li, PhD, Emory University 
• Abdulhameed Dere, MBBS; Abdulquddus Ajibade, MBBS; Theo Dapamede, MD, PhD; Mohammadreza Chavoshi, MD; Janice M. Newsome, MD; Hari Trivedi, MD; Judy W. Gichoya, MD, MS, FSIIM 

 

Predicting Major Adverse Cardiovascular Events Using Multimodal Models 

• Frank Li, PhD, Emory University 
• Kéana Aitcheson, MBBS; Theo Dapamede, MD, PhD; Hari Trivedi, MD; Judy Gichoya, MD, MS, FSIIM