Intel and GE deliver AI to medical imaging
December 11, 2018
Intel and GE Healthcare are teaming up to deliver artificial intelligence (AI) across multiple medical imaging formats to help prioritise and streamline patient care.
By leveraging the Intel distribution of the OpenVino toolkit running on Intel processor-based x-ray systems, GE Healthcare is accelerating deep learning with medical imaging at the point of care. Using this system, x-ray technologists, critical care teams and radiologists will be immediately notified to review critical findings that may accelerate patient diagnosis.
"With the OpenVino toolkit running on existing Intel processors, in early testing GE Healthcare achieved a 3.3 times improvement in deep learning optimisation, which enables early prioritisation and escalation of critical conditions to ensure faster treatment for our patients,” said Keith Bigelow, senior vice president at GE Healthcare. “Intel technologies will enable GE Healthcare to extend AI across multiple imaging modalities to transform radiologist workflows and patient care."
Medical imaging is the largest and fastest-growing data source in the healthcare industry. It accounts for 90 per cent of all healthcare data – and more than 97 per cent of it goes unanalysed or unused. Before now, processing this massive volume of medical imaging data could lead to longer turnaround times from image acquisition to diagnosis to care. Meanwhile, patients' health could decline while they wait for diagnosis. Especially when it comes to critical conditions, rapid analysis and escalation are essential to accelerate treatment.
By deploying deep learning on existing infrastructure, optimised with AI software, GE Healthcare has the potential to power more efficient and effective care, enhance decision-making, and drive greater value for patients and providers.
One key implementation of this technology is providing earlier detection of a collapsed lung, also known as pneumothorax – a potentially life-threatening event. Radiologists can now deploy predictive algorithms that scan for and detect pneumothorax within seconds at the point of care, allowing rapid response and reprioritisation of an x-ray for clinical diagnosis.
In early testing, when GE Healthcare employed the OpenVino toolkit on its pneumothorax models, pneumothorax detection on its Intel processor-based x-ray system accelerated by 3.3 times compared with models without OpenVino toolkit optimisations. Optimisations improved performance across models, with the pneumothorax model receiving the most benefit.