December 14, 2017 — At the 2017 Radiological Society of North America (RSNA) Annual Meeting, GE Healthcare and NVIDIA announced a series of imaging equipment advances powered by NVIDIA’s artificial intelligence (AI) computing platform. The announcements included the new Revolution Frontier computed tomography (CT) system, advancements to the Vivid E95 4-D 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 U.S. Food and Drug Administration (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, benefiting patients with compromised renal function and reducing non-interpretable scans with Gemstone Spectral Imaging Metal Artefact Reduction (GSI MAR).
NVIDIA 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.
GE Healthcare and NVIDIA also announced the following at RSNA:
- The Vivid E95 4D Ultrasound System, on display at RSNA, uses NVIDIA GPUs to provide fast, accurate visualization and quantification while streamlining workflows across the cSound imaging platform. NVIDIA GPUs accelerate reconstruction and visualization of blood flow and improve 2-D and 4-D imaging for echo lab and interventional deployments;
- Modules of the new Applied Intelligence analytics platform will use NVIDIA GPUs, the NVIDIA CUDA parallel computing platform and the NVIDIA GPU Cloud container registry to accelerate the creation, deployment and consumption of deep learning algorithms in new healthcare analytic applications that will be seamlessly integrated into clinical and operational workflows and equipment.
For more information: www.gehealthcare.com
