Welcome to the age of AI-assisted imaging

Underpinning our Collaborative imaging approach is a commitment to creating smart solutions, powered by AI, that deliver uncompromised quality and value across the entire care pathway. Using only the smartest innovations, including deep learning technology, our goal is to help clinicians improve patient outcomes through the provision of:
Informed healthcare 
Our solutions have been designed to enhance your clinical confidence with high-quality images and applications that help you make informed treatment decisions in real-time.
Efficient workflows
We have created simple, streamlined AI-driven workflows that optimize resource deployment and ensure your teams have the insights they need to work smarter every day.
Tailored treatment
We’re channeling our focus into the provision of AI solutions that enable your patients to get the fast, accurate results they need for a more confident and personalized approach to care.

The Technology

Cutting-edge doesn’t cut it

We’re obsessed with the pursuit of smarter, faster, better imaging solutions that can transform the way you work.

Discover our technology

The Research

Evolving AI for everyone

We oversee a range of research projects to ensure you’re always working with the latest insights available.
Learn more about our research

Latest News

A new era of AI-assisted imaging has begun

“AI in Medical Imaging: Hype, Myth, Reality and Next Steps”

Listen to Eliot Siegel, MD, FSIIM, FACR, Professor and Vice Chair Research Informatics, University of Maryland School of Medicine, Chief of Radiology and Nuclear Medicine, Veterans Affairs Maryland Healthcare System

Watch Video

*From $600 M to $6 Billion, Artificial Intelligence Systems Poised for Dramatic Market Expansion in Healthcare
**A Model Observer study was performed comparing AiCE to FBP. Actual clinical results may differ depending on the clinical task, patient size, anatomical location and clinical practice.
** Based on the detectability index performance metric, a measure of signal to noise that takes into account the magnitude and texture of both the signal and the noise for a given LCD task.
** A model observer evaluation showed that equivalent low contrast delectability to FBP (range from 0.649 - 0.695) can be achieved with 79.6 to 82.4% less dose using AiCE at Standard setting for thin (0.5 mm) reconstruction slice thickness in simulated body phantom (MITA-FDA phantom with a body ellipse surrounding it).