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. 

Compute

AI sees what radiologists cannot, predicts disease-free survival in lung cancer patients

With further testing and validation, Hyungjin Kim, with Seoul’s National University College of Medicine and colleagues believe radiologists may one day use the tool to individualize treatment and achieve better outcomes.

May 14, 2020
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Machine learning-powered imaging platform pinpoints subtle differences in blood clots

"Using this new tool may uncover the characteristics of different types of clots that were previously unrecognized by humans," researchers wrote in the journal eLife.

May 12, 2020
Covid

Abdominal imaging reveals bowel injuries in COVID-19 patients

Abnormalities were most commonly seen in sicker patients with the virus who were also admitted to the intensive care unit, according to recent research.

May 12, 2020

Readily available radiotracer offers new option in prostate cancer imaging

Nuclear medicine experts found that 18F-PSMA-1007 performed just as well as 68Ga-PSMA for staging individuals with intermediate- or high-risk forms of the disease.

May 11, 2020
Brain

Blood-brain barrier vs. focused ultrasound with MRI guidance

Researchers at the University of Virginia are exploring ways to break through the blood-brain barrier using MRI-guided focused ultrasound.

May 6, 2020

RSNA, neuroradiologists assemble largest-ever set of brain hemorrhage CT images through AI challenge

The society recently announced this “unprecedented collaboration,” which was made possible by the help of 60 physician volunteers and a fellow imaging interest group. 

April 30, 2020
MRI

Will medical imaging follow the (investor) money to in-office, AI-aided MRI?

The moment may be ripe for MRI scanners that could fit into clinicians’ offices and leverage AI for optimally efficient workflows, interpretations and treatment plans.

April 29, 2020

Algorithm classifies sleep apnea—or recognizes its absence—from 3D headshots

A predictive algorithm has distinguished patients free of obstructive sleep apnea from those with three levels of the condition—mild, moderate and severe—with 91% accuracy. And it did so using only 3D photos of the subjects’ faces.

April 23, 2020

Around the web

Automated AI-generated measurements combined with annotated CT images can improve treatment planning and help referring physicians and patients better understand their disease, explained Sarah Jane Rinehart, MD, director of cardiac imaging with Charleston Area Medical Center.

Two advanced algorithms—one for CAC scores and another for segmenting cardiac chamber volumes—outperformed radiologists when assessing low-dose chest CT scans. 

"Gen AI can help tackle repetitive tasks and provide insights into massive datasets, saving valuable time," Thomas Kurian, CEO of Google Cloud, said Tuesday. 

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