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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3 key ways machine learning could transform interventional radiology

Machine learning could be a real game-changer for interventional radiology (IR) in the years ahead, according to a new analysis published in the American Journal of Roentgenology.

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AI helps radiologists detect brain aneurysms

“Search for an aneurysm is one of the most labor-intensive and critical tasks radiologists undertake,” said co-senior author Kristen Yeom, MD, associate professor of radiology at Stanford University.

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AI approach reduces CT radiation, produces high-quality images

A new deep learning approach lowered radiation exposure from CT imaging while producing higher quality scans compared to traditional iterative reconstruction techniques, according to research published in Nature Machine Intelligence.

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Aidoc’s AI solution for cervical spine fractures gains FDA clearance

Tel Aviv, Israel-based Aidoc has received FDA approval for its new AI solution that helps specialists triage cervical spine fractures.

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Augmented datasets can improve accuracy of neural networks

Deep convolutional neural networks (DCNNs) can better classify chest x-rays when trained on augmented datasets, according to a new study published in Clinical Radiology.

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Ultrafast CT can produce clearer images in the ED

Utilizing the ultrafast scan mode for CT imaging in the emergency department (ED) can significantly reduce motion artifacts, reported a team of Japan-based researchers in a study published by the American Journal of Roentgenology.

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AI helps researchers ID brain aneurysms on CTA examinations

A new automated detection tool using deep learning can detect clinically significant brain aneurysms on CT angiography (CTA) examinations, according to a new study published in JAMA Network Open.

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How the FDA assesses AI-based imaging algorithms

The FDA is responsible for regulating AI solutions designed and developed to provide care for patients, a task that leads to certain unique challenges.

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