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. 

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Need a hand? ABB brings new laboratory robot to Texas Medical Center

ABB, an international technology company, has opened its first global healthcare research hub in Houston, Texas, to demonstrate some of its robotic solutions.

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UCSF pilots new center to accelerate AI in radiology

“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,” said Christopher Hess, MD, PhD, chair of the UCSF Department of Radiology and Biomedical Imaging.

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Brain imaging debunks traditional theory about dyslexia

New research utilizing functional MRI (fMRI) has cast doubts on a commonly believed theory about dyslexia, potentially paving the way for new approaches to the learning disorder.

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AI helps bust stroke, identify occlusions

Applied to head CT images, AI software can help speed diagnosis of ischemic stroke while also localizing large vessel occlusions when the latter are a culprit, according to a systematic review of studies published over a five-year period ending in February.

4D MRI virtual catheter automatically evaluates aortic flow

A newly created four-dimensional virtual catheter technique allows for reproducible, automated estimation of blood flow in patients with congenital bicuspid aortic valve (BAV), reported authors of an Oct. 8 study published in Radiology.

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AI system performs comparably to PI-RADS

A convolutional neural network (CNN) could potentially help with the detection and segmentation of suspicious findings on prostate MRI scans, according to new findings published in Radiology.

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MRI scans show drops in income may reduce brain volume

"Income volatility is at a record level since the early 1980s and there is growing evidence that it may have pervasive effects on health," said Adina Zeki Al Hazzouri, PhD, assistant professor of epidemiology at Columbia Mailman School of Public Health.

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How radiologists can avoid malpractice lawsuits when using AI

As the use of artificial intelligence continues to proliferate in healthcare, radiologists may be opening themselves up to a whole new set of liability concerns.