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. 

5 recent developments in thoracic imaging and what they may portend for radiology at large

Recent years have seen the venerable chest X-ray built upon with new technologies, screening programs and educational techniques. As a result, today’s thoracic imaging may be a humble herald of things to come across radiology.  

January 19, 2023
Example of artificial intelligence generated measurements to quantify the size of a lung cancer nodule during a followup CT scan to see if the lesion is regressing with treatment. This type of automation can aid radiologists by doing the tedious, time consuming work. Photo by Dave Fornell

8 trends in radiology technology to watch in 2023

Here is a list of some key trends in radiology technology from our editors based on our coverage of the radiology market.

January 18, 2023

Deep learning slashes real-world MRI scan times

Accelerated MRI with AI image reconstruction nearly halved orthopedic scan times while maintaining or even improving image quality in a newly published prospective study. 

January 18, 2023
Jakob Weiss, MD, a radiologist affiliated with the Cardiovascular Imaging Research Center at Massachusetts General Hospital and the AI in Medicine program at the Brigham and Women’s Hospital in Boston, helped develop an deep learning AI algorithm that can assess a patient's biological age and risk assess patients for various diseases. #RSNA #AI #ImagingAI

VIDEO: AI predicts heart disease risk using single chest X-ray

Jakob Weiss, MD, was the lead author on a study that used AI to determine a patient's cardiovascular risks based on a standard chest X-ray.

January 12, 2023
Safety information for patients taking Aduhelm has been updated by the FDA to include the addition of two MRI scans during the first year of treatment. #alzheimers #alzheimerstreatment

Biological ‘brain age’ could help pave the way for more personalized medicine

AI-powered analysis can now assess cognitive decline by noting gaps in chronological versus biological “brain age.”

January 9, 2023

Emerging imaging technologies boosted by COVID research

As the field of radiology research adapted to withstand the pandemic’s challenges, it morphed in some decidedly beneficial ways.

January 9, 2023
York University researchers demonstrate how AI can help predict brain metastasis outcomes

AI bests humans at predicting outcomes for brain radiotherapy patients

The new technology could help develop more tailored treatment plans. 

December 22, 2022
An overview of artificial intelligence (AI) in radiology with Keith Dreyer with the ACR. Images shows a COVID-19 lung CT scan reconstruction from Siemens Healthineers. #AI #radAI #ACR

AI triages pneumothorax patients with differentiated diagnoses

A commercially available AI package has proven adept at distinguishing between two closely similar but unequally urgent conditions on chest X-rays.

December 20, 2022

Around the web

"This was an unneeded burden, which was solely adding to the administrative hassles of medicine," said American Society of Nuclear Cardiology President Larry Phillips.

SCAI and four other major healthcare organizations signed a joint letter in support of intravascular ultrasound. 

The newly approved AI models are designed to improve the detection of pulmonary embolisms and strokes in patients who undergo CT scans.

Trimed Popup
Trimed Popup