Medical Imaging

Physicians utilize medical imaging to see inside the body to diagnose and treat patients. This includes computed tomography (CT), magnetic resonance imaging (MRI), X-ray, ultrasound, fluoroscopy, angiography, and the nuclear imaging modalities of PET and SPECT.

NVIDIA sees major shift in radiology to AI agents and new autonomous imaging systems
“Physical AI agents being able to actually deliver some of these services—all the way into robotic surgery—this is where we're going to see this next chapter of medicine be written,” said Kimberly Powell, vice president and general manager of healthcare at NVIDIA.
Scoring system outperforms standard radiology reports for predicting soft tissue tumor malignancy
The Soft-Tissue Tumor Reporting and Data System (ST-RADS) is an MRI framework that was designed to assess the risk of soft tissue tumors and help providers in managing the finding.
Mindfulness improves brain connectivity, MRI data show
Mindfulness-based stress reduction techniques combine meditation, bodily awareness exercises and yoga to temper stress and anxiety.
Stanford Medicine’s Department of Radiology inks partnership with Novartis
They’ll work to accelerate research and development around targets for radioligand imaging across a wide range of oncological applications.
New data on GBCA safety indicate risk of renal complications 'exceedingly low'
Nephrogenic systemic fibrosis is a serious, potentially fatal disease that progressively causes the skin and underlying tissues to harden.

Kimberly Powell, vice president, general manager of healthcare at NVIDIA, explains how artificial intelligence (AI) has rapidly expanded in radiology and how many of the companies showing AI products at the Radiological Society of North America (RSNA) 2025 meeting use the company's technology. She said a few key technology launches by GE Healthcare show a deeper integration of NVIDIA's AI technology, and shared what the next generation of "physical AI" will enable autonomous radiology exams.

NVIDIA sees major shift in radiology to AI agents and new autonomous imaging systems

“Physical AI agents being able to actually deliver some of these services—all the way into robotic surgery—this is where we're going to see this next chapter of medicine be written,” said Kimberly Powell, vice president and general manager of healthcare at NVIDIA.

ST-RADS scoring system for predicting risk of soft tissue tumor malignancy

Scoring system outperforms standard radiology reports for predicting soft tissue tumor malignancy

The Soft-Tissue Tumor Reporting and Data System (ST-RADS) is an MRI framework that was designed to assess the risk of soft tissue tumors and help providers in managing the finding.

Mindfulness improves brain connectivity, MRI data show

Mindfulness-based stress reduction techniques combine meditation, bodily awareness exercises and yoga to temper stress and anxiety.

Stanford Medicine’s Department of Radiology inks partnership with Novartis

They’ll work to accelerate research and development around targets for radioligand imaging across a wide range of oncological applications.

New data on GBCA safety indicate risk of renal complications 'exceedingly low'

Nephrogenic systemic fibrosis is a serious, potentially fatal disease that progressively causes the skin and underlying tissues to harden.

Leading nuclear medicine organizations collaborate to streamline PET accreditation

The groups have jointly endorsed a unified framework “to standardize and harmonize quantitative PET imaging worldwide.”

Artificial Intelligence AI in healthcare

MRI data suggest COVID likely affects the neurological health of everyone, even those who fully recover

Even if an individual has fully recovered from COVID-19 and is able to return to their normal routines, the structural and chemical makeup of their brain may not return to its pre-COVID state.

Eric Rubin, MD, vice president of clinical operations at Virtua Health, and the American College of Radiology's CPT advisor to the American Medical Association (AMA), explains the process for creating a Category I CPT code for payments and the difference with Category III temporary tracking codes.

Radiology dominates FDA-cleared AI, but reimbursement lags far behind

As of January 2026, there will only be two CPT category 1 payment codes for newer AI, despite there being hundreds of FDA-cleared medical imaging algorithms.