Imaging AI in Practice demonstration

The Imaging AI in Practice (IAIP) demonstration is presented at the RSNA annual meeting to showcase new technologies and communication standards needed to integrate AI into the diagnostic radiology workflow. It uses real-world clinical scenarios and interoperability standards to demonstrate new tools and practice enhancements enabled by AI. 


The demonstration follows a fictional patient through a real-world clinical scenario involving both emergent and long-term care. It includes many steps in the radiology workflow where AI can assist the radiologist and improve the efficiency and quality of care.

The diagrams linked here give a visual overview of the flow of information among systems in a radiology practice with AI tools integrated: 

Standards foundation

The RSNA IAIP demonstration shows how radiology systems can be integrated to efficiently include AI-based applications at key points in the workflow. This seamless integration relies on a set of interoperability standards, including: 

RSNA 2023 Participants

GE Healthcare
Hyperfine Operations, Inc.
Laurel Bridge
Nuance Communications
Pocket Health
Rad AI
Siemens Healthineers
Smart Reporting
Telerad Tech
Visage Imaging

Imaging AI in Practice video archive

View videos featuring previous IAIP demonstration participants performing real-world clinical scenarios to show how AI can be used to support improvements in patient care.

RSNA 2022

Introduction: Imaging AI Clinical and Data Workflow
Watch an overview of the clinical scenario and process steps for the Imaging AI in Practice demonstration at RSNA 2022.

RSNA 2020

Imaging AI in Practice Demonstration Introduction
Start here for an overview of the Imaging AI in Practice demonstration’s clinical scenario and process steps.

Work with AI
This video focuses on the interaction between radiologists and AI tools.

Evolve with AI
This video covers implementing and refining AI tools to optimize them for your local environment.

Save Time with AI
This video highlights the efficiencies gained by strategically implementing AI.