GE HealthCare
(Nasdaq: GEHC)
is expanding its AI partnership with Nvidia to include autonomous X-ray and ultrasound applications.
The Chicago-based medtech giant said the partnership, announced yesterday at GTC 2025 in San Jose, California, is meant to address the radiology staff shortages burdening health systems amid an aging population.
The news was part of a host of medtech AI announcements this week as Nvidia holds its GTC 2025 event in San Jose, California. (We have a full roundup of medtech AI news out of Nvidia’s “Super Bowl of AI.”)
GE HealthCare will leverage Nvidia’s new Isaac for Healthcare platform. The Isaac for Healthcare platform is built on Nvidia’s three computers utilized to build physical AI, including Nvidia Omniverse for robotic simulation workflows. Using the Nvidia Cosmos platform for synthetic data generation, physics-based sensor simulation, imitation, and reinforcement learning, GE HealthCare will train, test, and tune autonomous ultrasound and X-ray devices in a virtual environment before actual deployment.
“GE HealthCare has a deep history of firsts in medical imaging, and we continue to build upon our legacy of innovation as a healthcare solutions provider,” Roland Rott, president and CEO of Imaging at GE HealthCare, said in a news release.
“We are excited about our expanded relationship with Nvidia and the potential of autonomous X-ray and ultrasound as we are focused on unlocking smarter, more automated solutions that enhance efficiency, standardize imaging, and help ease the burden of increased volumes and double-digit staff shortages on healthcare professionals.”
The initial focus of the partnership will involve developing an autonomous X-ray system, potentially utilizing the Nvidia Isaac for Healthcare and Jetson platforms. The Isaac for Healthcare platform and synthetic data generation will simulate various scenarios. The goal is to automate repetitive tasks a technologist performs in the patient exam room, enabling care teams to focus more on direct patient care and complex cases. There is also the potential to develop machine-to-patient interactions to lead the patient through the scan journey autonomously.
The work on autonomous ultrasound systems will focus on reducing the work burden for sonographers and radiologists. For sonographers, autonomous ultrasound systems could streamline workflow and reduce demanding physical strain resulting from repetitive motions. In addition, AI has the potential to take on more of the daily workload though advancements in image understanding and robotic navigation.
GE HealthCare and Nvidia already have a history of partnership. For example, GE HealthCare used Nvidia technology to develop its healthcare-specific research foundation model SonoSAMTrack, trained on approximately 200,000 image-mask pairs.
“Artificial intelligence and physical AI offer an incredible opportunity to expand global access to GE HealthCare’s advanced imaging systems,” said Kimberly Powell, VP of healthcare at Nvidia. “Working together to train and test autonomous solutions, we will accelerate the future of medical imaging capabilities, starting with the two most widely used modalities: X-ray and ultrasound.”
