Artificial Intelligence

Artificial intelligence (AI) is becoming a crucial component of healthcare to help augment physicians and make them more efficient. In medical imaging, it is helping radiologists more efficiently manage PACS worklists, enable structured reporting, auto detect injuries and diseases, and to pull in relevant prior exams and patient data. In cardiology, AI is helping automate tasks and measurements on imaging and in reporting systems, guides novice echo users to improve imaging and accuracy, and can risk stratify patients. AI includes deep learning algorithms, machine learning, computer-aided detection (CAD) systems, and convolutional neural networks.

Commercially available AI increases breast cancer detection by nearly 20%
Results from the world’s largest prospective artificial intelligence study revealed the system could significantly benefit breast cancer screening programs.
Clinicians want AI to show its work
Providers are more likely to trust AI when they understand how it arrives at its conclusions.
ACR Assess-AI national data registry tracks performance of clinical algorithms
Christoph Wald, MD, vice chair of the ACR Board of Chancellors, explains how the new Assess-AI National Radiology Data Registry is designed to help monitor accuracy and other metrics for radiology artificial intelligence.
New cardiac prevention paradigm explored in TRANSFORM trial using AI and CCTA
Deepak Bhatt, MD, director of the Mount Sinai Fuster Heart Hospital and principal investigator of the TRANSFORM trial, explains an emerging technique for cardiac screening: combining coronary CT angiography with artificial intelligence for plaque analysis to create an approach similar to mammography.
PHOTO GALLERY: Medical imaging technology at RSNA 2024
Take a virtual tour around the Radiological Society of North America (RSNA) meeting to see the sights and new technologies displayed across the vast exhibit hall floors.

ACR’s Allen: Why structured use cases will drive adoption of AI in radiology

The American College of Radiology Data Science Institute (ACR DSI) recently released a series of standardized artificial intelligence (AI) use cases to help advance imaging in AI. Down the road, they could help create an “AI ecosystem” for radiology, wrote Bibb Allen, MD, chief medical officer of the ACR DSI, in a recent Journal of the American College of Radiology editorial.

October 30, 2018

3D MR fingerprinting technique shows promise in breast imaging

A team of researchers from Cleveland has developed a three-dimensional (3D) MR fingerprinting method for breast imaging which may better evaluate breast tumors, according to an Oct. 30 study published in Radiology.

October 30, 2018

Novel quantum dots may allow for 3D cell imaging

Researchers from the University of Illinois at Urbana-Champaign and the Mayo Clinic in Rochester, Minnesota, teamed up to create a new molecular probe which can measure and count RNA in cells and tissue as well as traditional dyes, according to a new study in Nature Communications.

October 30, 2018

Researchers succesfully open blood-brain barrier with focused ultrasound in Alzheimer’s patient

Researchers from the West Virginia University (WVU) Rockefeller Neuroscience Institute in Morgantown performed the world's first FDA-approved focused ultrasound procedure during a phase II trial to treat Alzheimer's Disease, according to a university press release.

October 29, 2018

ACR Data Science Institute releases use cases to advance AI imaging

The American College of Radiology Data Science Institute (ACR DSI) announced Oct. 26 the release of a series of standardized artificial intelligence (AI) use cases to advance imaging in AI.

October 26, 2018

FDA approves first Microsoft HoloLens augmented reality system for surgical use

The technology projects 2D, 3D and 4D images of patients interactively by overlaying them onto the patient's body, according to a Novarad press release published Oct. 24.

October 25, 2018

AI detects missed aneurysms in MR angiography with increased sensitivity

A team of Japanese researchers found a deep learning-based algorithm used to analyze time-of-flight (TOF) MR angiography images improved cerebral aneurysm detection with an average sensitivity of 92 percent compared to initial radiology reports, according to research published Oct. 23 in Radiology.

October 24, 2018

CT imaging of ancient remains creates 3D pictures of Egyptian mummy faces

Two Egyptian mummies pinned unidentifiable by archaeologists have recently been given three-dimensional (3D) faces with the help of CT imaging and computer animation thanks to researchers at Johns Hopkins University in Baltimore, according to a report published Oct. 23 by The Baltimore Sun.

October 23, 2018

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New cardiac prevention paradigm explored in TRANSFORM trial using AI and CCTA

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Cardiology practices pay $17.7M to settle fraud allegations brought on by whistleblowers

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