The future of AI and medical imaging, from Nvidia to Harvard

Check out the on-demand sessions from the Low-Code/No-Code Summit to learn how to successfully innovate and gain efficiencies by improving and scaling citizen developers. Watch now.

It's been six years since Geoffrey Hinton said, "We need to stop training radiologists now," insisting that "it's quite obvious that within five years, deep learning will better than radiologists". Instead, the future of medical imaging, it seems, remains firmly in the hands of radiologists - who have embraced artificial intelligence (AI) as a collaborative tool to boost medical imaging, one of the most essential areas of health care that is used throughout the patient. journey.

What is evolving, however, are significant open source efforts to integrate AI models related to medical imaging into large-scale clinical environments, as well as to ensure that medical imaging data that train these AI models are robust, diverse, and available for anything.

Integration of AI models into clinical workflows

To address the first objective, Nvidia announced today at the annual meeting of the Radiology Society of North America (RSNA) that MONAI, an open-source medical imaging AI framework accelerated by Nvidia, makes it easy to integrate AI models into clinical workflows with MONAI Application Packages (MAPs), delivered through MONAI Deploy.

Nvidia and King's College London launched MONAI in April 2020 to simplify AI medical imaging workflows. This makes it possible to transform raw imaging data into interactive digital twins to improve analysis or diagnosis, or guide surgical instruments. The development and adoption of the platform now has over 600,000 downloads, half of them in the last six months.

Event

Smart Security Summit

Learn about the essential role of AI and ML in cybersecurity and industry-specific case studies on December 8. Sign up for your free pass today.

Register now

Leaders in medical imaging, including UCSF, Cincinnati Children's Hospital and startup Qure AI, are adopting MONAI Deploy to turn research advances into clinical impact, Nvidia said in a press release. hurry. Additionally, all major cloud providers, including Amazon, Google, Microsoft, and Oracle, support MAPs, allowing researchers and enterprises using MONAI Deploy to run AI applications on their platform, either using containers, or with the integration of native applications.

“MONAI has really established itself in the research and development community as the PyTorch of healthcare,” said David Niewolny, director of healthcare business development at Nvidia, during a press briefing before the announcements. "It's purpose-built for radiology, but now extends into pathology and digital surgery, and really tackles the entire lifecycle of AI, bridging the gap between that research community and the deployment."

For example, Cincinnati Children's Hospital is creating a MAP for an AI model that automates total heart volume segmentation from CT images, helping pediatric heart transplant patients in a project funded by the National Institutes of Health. "It speeds up decision-making time for pediatric transplant patients," he said. "He really has the potential to save the lives of a number of children."

Extend AI and medical imaging to a wider audience

The integration of MONAI by all cloud hyperscalers allows this research to expand beyond a hospital to a much wider audience, Niewolny added. For example, the MAP con...