NVIDIA has made a name for itself in the AI field with its Tesla family of deep learning GPU accelerators, and has signed up scores of partners with its AI-fueled DRIVE PX family. Its DRIVE PX products empower self-driving vehicles from some of the world's top auto manufacturers. Using these same AI fundamentals, NVIDIA hopes to revolutionize the medical world and help save lives in the process.
Using NVIDIA's AI platform, GE will adopt GPU-accelerated deep learning solutions to better provide real-time medical assessments of patients and help doctors make better-informed clinical decisions about patient care.
“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,” added NVIDIA CEO Jensen Huang.
“Healthcare is changing at remarkable speed, and the technologies that will transform the industry should reflect that pace,” said GE Healthcare CEO Kieran Murphy. “By partnering with NVIDIA, GE Healthcare will be able to deliver devices of the future – intelligent machines capable of empowering providers to improve the speed and accuracy of diagnoses for patients around the world.”
The pair also announced the Revolution Frontier CT family, which processes images twice as fast as its predecessor thanks to NVIDIA's AI computing advances. Over the past decade, advances in CT image reconstruction has reduced X-ray dosages by over 80 percent, while the new Revolution Frontier CT family uses supercomputer muscle to further aid in complex image reconstruction.
Another product announced was the Vivid E95 4D Ultrasound System, which uses NVIDIA GPUs to aid in the acceleration of reconstruction and visualization of blood flow, and enhances the reproduction of 2D and 4D imaging.
Finally, GE's Healthcare Applied Intelligence analytics platform will be infused with NVIDIA GPUs and the CUDA parallel computing platform to power a new generation of healthcare applications that take advantage of deep learning algorithms.