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GE and NVIDIA Join Forces to Accelerate AI Adoption in Healthcare
Published: Nov 27,2017GE Healthcare and NVIDIA today announced they will deepen their 10-year partnership to bring the most sophisticated artificial intelligence (AI) to GE Healthcare’s 500,000 imaging devices globally and accelerate the speed at which healthcare data can be processed.
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The scope of the partnership, detailed today at the 103rd annual meeting of the Radiological Society of North America (RSNA), includes the announcement of the new NVIDIA-powered Revolution Frontier CT, advancements to the Vivid E95 4D Ultrasound and development of GE Healthcare’s Applied Intelligence analytics platform.
The new CT system in the Revolution Family is two times faster in imaging processing than its predecessor, due to its use of NVIDIA’s AI computing platform. The Revolution Frontier is FDA cleared and expected to deliver better clinical outcomes in liver lesion detection and kidney lesion characterization because of its speed – potentially reducing the need for unnecessary follow-ups, benefitting patients with compromised renal function and reducing non-interpretable scans with Gemstone Spectral Imaging Metal Artefact Reduction (GSI MAR).
“Our partnership with GE Healthcare brings together great expertise in medical instruments and AI to create a new generation of intelligent instruments that can dramatically improve patient care,” said Jensen Huang, founder and CEO of NVIDIA.
NVIDIA, which has helped pioneer the spread of AI across a growing range of fields, including self-driving cars, robotics and video analytics, is working with GE Healthcare to spread its application in healthcare. GPU-accelerated deep learning solutions can be used to design more sophisticated neural networks for healthcare and medical applications—from real-time medical condition assessment to point-of-care interventions to predictive analytics for clinical decision-making. For patients, the partnership aims to drive lower radiation doses, faster exam times and higher quality medical imaging.
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