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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VR software may bring MRI segmentation into the future

A new virtual-reality (VR) software to correct segmentation errors on MRI scans was found to be faster, more accurate and enjoyable compared to a more commonly used system, reported authors of a recent Journal of Digital Imaging study.

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Flexible x-ray detector could lead to tailor-made imaging machines

A flexible x-ray detector developed by researchers at the University of Surrey's Advanced Technology Institute in the U.K. could lead to the development of other real-time imaging machines that would decrease screening errors and harm to patients.

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WHO, ITU to expand use of AI globally

The International Telecommunication Union (ITU) and World Health Organization (WHO) are converging for the global expansion of the use of artificial intelligence (AI) “to advance health for all worldwide.”

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What are Twitter users saying about AI in radiology? 3 key takeaways

Artificial intelligence (AI) is an immensely popular topic in radiology, sparking countless discussions and debates about whether it will give radiologists a new tool for providing high-quality patient care or end up replacing them altogether.

Twitter users are optimistic about AI's integration into radiology

According to the world of Twitter, the implementation of artificial intelligence (AI) in radiology renders an overwhelmingly positive response and is joined with arguments against AI potentially replacing radiologists, wrote authors Julia Goldberg, and Andrew Rosenkrantz, MD, in a piece published July 23 in Current Problems in Diagnostic Radiology.

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X-ray fiber diffraction may ID structural tissue changes in heart, brain

A specialized x-ray diffraction lab at the Illinois Institute of Technology (IIT) in Chicago is using fiber diffraction, allowing scientists to study structural tissue changes in the human heart, brain and even dinosaur fossils. The technique may help physicians track injury-related tissue damage and identify risk areas, according to an American Crystallographic Association release from July 22.

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Q&A: New Zealand father, son scientists discuss development of 3D color x-ray scanner

Health Imaging recently spoke with father-and-son scientists Anthony Butler, PhD, and Phil Butler, PhD, about the MARS spectral x-ray scanner, a new 3D color x-ray machine that has gained international attention since it successfully imaged its first human subject last week.

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Q&A: Sham Sokka on how radiologists can leverage AI to minimize patient no-shows

Sham Sokka, PhD, has spent the bulk of his career in radiology, where he’s worked for 15 years with a range of clients to shape and customize imaging modalities, workflows and software.