During his wide-ranging keynote yesterday at GTC, Nvidia CEO Jensen Huang outlined the company’s ambitious plan to build a medical imaging supercomputer – Clara – with a complete stack for medical image analysis and that could be deployed in datacenters or the cloud. Few details were disclosed but the demonstration, which showed AI-driven post processing of old black and white ultrasound images of a a fetus and the heart, was impressive.
“This technology is used everywhere, CT, MRI, PET scans. We can now reconstruct images better than ever before. We can visualize images in a way that release more insight with cinematic rendering. The entire software stack, the solvers and libraries, integrated into this is identical to what we’ve talked about,” said Huang.
“The unfortunate thing is there around 3 million medical instruments installed, but only 100k sold each year. It would take 30 years to update everything. To avoid this we have an initiative for Project Clara – a virtualized data center, remoted, multi-modality, multi-user. It’s a medical imaging supercomputer. It’s possible now for us to virtually update every system that’s out there.”
AI-driven analysis of medical images has certainly been revolutionizing the insight the medical community can extract from medical images. Making such processing available to the installed base of instruments could dramatically improve their usefulness. Most of the imaging equipment in hospital is already connected to a network.
Huang showed 15-year-old ultrasounds images that had been re-rendered in color and displaying features with far more realism and accuracy. There was also footage of heart function in which the anatomy and output were better identified and quantified. Nvidia is working with many partners, such as the Mayo Clinic and Samsung, in developing Clara said Huang.
Link to keynote: https://www.ustream.tv/recorded/110557582