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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AI-generated synthetic brain MRI provides diverse, reliable training data

Researchers have created a deep-learning model that can generate synthetic brain MRIs to help train neural networks, according to research published in ArXiv. The technique may provide reliable, shareable training data.

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AI program may spot signs of disease 3 years before symptoms emerge

An artificial intelligence (AI) system developed by Shinjini Kundu, PhD, a physician and medical researcher at the University of Pittsburgh Medical Center, could find patterns of developing diseases as much as three years earlier than imaging experts.

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Open-source microscopy add-on may improve 2D, 3D brain imaging

Researchers from Tel Aviv University in Israel created a new microscopy method that utilizes an add-on for laser scanning microscopes to improve the quality of 2D and 3D brain imaging, according to research published Sept. 13 in Optica.

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Canadian researchers’ novel ultrasound machine costs $100 and can be controlled by a smartphone

Engineers from the University of British Columbia (UBC) in Canada who developed a new ultrasound transducer say it could lower the cost of ultrasound machines to just $100. The probe is portable, wearable and can be powered by a smartphone.

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AI differentiates between spondylitis MRIs as well as skilled radiologists

Research published online Sept. 3 in Scientific Reports concluded that an artificial intelligence (AI) algorithm can differentiate between tuberculous (TB) spondylitis and pyogenic spondylitis on MRI exams with the same level of expertise as skilled musculoskeletal radiologists.

Advanced imaging reveals concussed athletes may be returning too soon

Brain MRI scans of concussed university hockey players showed the protective tissue insulating brain cell fibers became jarred loose two weeks after injury—despite being cleared to return, research published in the Frontiers in Neurology revealed.

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‘Hive mind’ AI connects groups of radiologists, outperforms specialists or AI alone

A small group of experienced radiologists, connected by machine learning algorithms that enable them to work together as a “hive mind,” can achieve higher diagnostic accuracy than individual radiologists or machine learning algorithms alone, according to new research presented on Sept. 10 at the Society for Medical Imaging Informatics in Medicine (SIIM)’s Machine Intelligence in Medical Imaging conference.

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Radiologists connect via AI ‘hives’ to enhance pneumonia diagnosis

A new technique that connects a small group of radiologists together using artificial intelligence (AI) algorithms performed better than individual doctors or algorithms alone in detecting pneumonia on x-rays.

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