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Welcome to the age of AI-assisted imaging

Underpinning our Collaborative imaging approach is a commitment to creating smart solutions, powered by Altivity, that deliver uncompromised quality and value across the entire care pathway.
Using only the smartest innovations, including machine learning and deep learning technologies, our goal is to help clinicians improve patient outcomes across the board.

Here’s what artificial intelligence can do for you

50%*

reduction in

departmental costs.

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30-40%*

improvement in

treatment outcomes.

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Up to 82.4%**

dose reduction with

Advanced intelligent Clear-IQ Engine (AiCE)

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Advanced machine and deep learning innovation

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.

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AI research

Evolving AI for everyone

We oversee a range of AI research projects that explore the impact of machine learning and deep learning on modern healthcare.

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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

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“AI has the power to dramatically impact patient care.”

Dr. Peter D. Chang

University of California, Irvine USA

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“This year, we saw how AI can actually improve the images.”

Dr. Russell Bull

Royal Bournemouth Hospital, UK

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“It humanizes healthcare and connects us with our patients.”

Dr. Rasu Shrestha

Atrium Health, USA

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  • 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).