UC San Francisco (UCSF) is getting a new artificial intelligence center — The Center for Intelligent Imaging, or ci2.

The center — a team effort with Santa Clara, California-based NVIDIA — will aim to create both the infrastructure and tools that are needed to bring AI to the imaging workflow and clinical care.

“Artificial intelligence represents the next frontier for diagnostic medicine,” said Dr. Christopher Hess, chair of the UCSF Department of Radiology and Biomedical Imaging.

“The Center for Intelligent Imaging will serve as a hub for the multidisciplinary development of AI in imaging to meet unmet clinical needs and provide a platform to measure impact and outcomes of this technology,” Hess added.

One major reason for the AI push is that there is more data than ever to process. “Close to half a million imaging studies are performed at UCSF annually. The medical center has amassed at least a petabyte of imaging data over the years — ranging from small X-ray images to much larger PET/MRI studies,” according to a report about the new center on the NVIDIA website.

Handling such enormous amounts of data requires equally gigantic amounts of computing power.

To address the computing demands, the center is adopting the NVIDIA DGX-2, which Hess believes will let researchers cut AI-software training time from months to day, hours – even minutes. It will also let them make use of different data modalities to create more complex — and powerful — learning models.

“We’re interested in integrating data from not only imaging, but also from medical records, genetics and other information sources in the healthcare system,” Hess explained.

The university has been a medical imaging and technology player since its 1975 collaboration with industry that led to the first worldwide installation of an MR system, according to UCSF.

Today's goal is to make a similar technologic leap forward with AI.

“AI is one of the greatest tools of this century,” said Abdul Hamid Halabi, director of healthcare at NVIDIA. “ci2 is bringing together an innovative ecosystem of startups, vendors, UCSF’s thought leadership in radiology, and NVIDIA’s Clara platform on the world’s fastest GPUs, to create imaging AI solutions for improving patient care.”

The center will be run by UCSF Radiology vice chair Sharmila Majumdar, who stressed that in today's image-heavy world AI is a must. “The volume of medical imaging has been rapidly increasing and radiologists are struggling to keep up with the sheer number of images,” she pointed out, adding that, “ci2 aims to impact the entire value chain of imaging, from the time the patient comes for a scan to the final delivery of individualized, quantitative, prognostic and care-defining information.”

As AI and big data have made increasing inroads into healthcare, major U.S. and European radiology organizations have begun to address potential ethical issues associated with access to patient data and AI-based diagnosis.

Earlier this month a number of radiology organizations addressed the issues in a multi-society statement, which focused on data, algorithms and practice, and appeared in the Journal of the American College of Radiology, Radiology, Insights into Imaging and the Canadian Association of Radiologists Journal.

“Radiologists remain ultimately responsible for patient care and will need to acquire new skills to do their best for patients in the new AI ecosystem,” said Dr. J. Raymond Geis, ACR Data Science Institute senior scientist and one of the paper’s leading contributors in an American Academy or Radiology statement at the time.

The societies collaborating on the statement included the ACR, European Society of Radiology (ESR), Radiological Society of North America (RSNA), Society for Imaging Informatics in Medicine (SIIM), European Society of Medical Imaging Informatics (EuSoMII), Canadian Association of Radiologists (CAR) and American Association of Physicists in Medicine (AAPM).