Recent Advances in AI for Abdominal Radiology
Abdominal radiology has traditionally lagged behind other radiology subspecialties for AI research. That situation has changed dramatically over the last few years with the introduction of more public datasets for training and better performing AI pipelines. In this presentation, I will show the latest abdominal radiology AI research from my lab. I will present projects on such diseases as diabetes, cancer and liver disease and explain our latest work on integrating radiology reports and images to annotate large datasets.
Objectives
Discuss the role of AI in body composition analysis
Explain how AI can assess diabetes on body CT
Identify use cases for large language models in abdominal radiology
Speaker
Ronald M. Summers, MD, PhD
Senior Investigator
Clinical Image Processing Service
Imaging Biomarkers and Computer-Aided Diagnosis Laboratory
U.S. National Institutes of Health
