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. 

fMRI reveals video game addiction in men increases impulsivity

Using fMRI, researchers found that brain regions associated with impulsivity were altered in men who are addicted to video games, according to new findings presented Nov. 28 at RSNA 2018.

Novel imaging method measures iron minerals in the living brain

A novel imaging technology—magnetoencephalography (MEG)—allows scientists to measure levels of iron-based minerals in the brain, which may provide insight into neurodegenerative disorders such as Alzheimer’s disease, reported researchers from Massachusetts General Hospital (MGH) in Boston.

New Intel-Based Artificial Intelligence Imaging Solution to Accelerate Critical Patient Diagnoses

Sponsored by GE HealthCare

Intel and GE Healthcare* are teaming up to deliver artificial intelligence (AI) solutions across multiple medical imaging formats to help prioritize and streamline patient care.

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RSNA 2018: How AI can help, but also hack into medical imaging

"Neural networks, such as cycle-consistent generative adversarial network (CycleGAN), are not only able to learn what breast cancer looks like, we have now shown that they can insert these learned characteristics into mammograms of healthy patients or remove cancerous lesions from the image and replace them with normal looking tissue,” said Anton S. Becker, MD, at RSNA 2018 in Chicago.

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RSNA 2018: The value of automated recommendations in AI radiology reporting

As time goes on, artificial intelligence (AI) is becoming more widely accepted as a necessary component of clinical workflow in medical imaging. According to Tarik K. Alkasab, MD, PhD, a radiologist at Massachusetts General Hospital in Boston, AI has the potential to make radiology reporting much more consistent and ultimately help radiologists make smarter decisions.

NYU releases open-source MRI dataset as part of Facebook collaboration

NYU School of Medicine’s Department of Radiology announced it will release more than 1.5 million anonymous MR images from its fastMRI collaboration with Facebook AI Research (FAIR), a partnership focused on using AI to speed up MRIs.

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Playing youth football may alter brain development

One season of football may cause alterations in the brain development of younger players, according to research presented Monday, Nov. 26, at RSNA 2018 in Chicago.

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Stanford researchers find AI may reduce gadolinium dose in MRI scans

Using artificial intelligence (AI), researchers from Stanford University in California have reduced the amount of gadolinium left behind in a patient’s body after an MRI exam, according to research presented at RSNA 2018 in Chicago