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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Is AI biting off more than it can chew in radiology?

One expert believes AI "simply isn't ready" to handle the ever-growing workload many imaging professionals are encountering, sharing his thoughts Feb. 4 in Forbes.

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AI rivals radiologists at classifying common hip arthritis—with a few caveats

More than 230 million people are impacted by osteoarthritis across the globe, and that figure is only increasing in the United States as the population grows older.

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CT reveals improved lung function following weight-loss surgery

"For the first time, this study has demonstrated changes in the CT morphology of large and small airways that improve when individuals lose weight," researchers wrote in Radiology.

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Advanced imaging, genomic analysis may change the way we treat cancer patients

"This study is a bridge between genetic sequencing, single-cell analysis and high-resolution medical imaging," researchers said of their study published in PLOS One.

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What MRI and 100 years of horror movies can teach us about our brains

Finnish researchers had volunteers watch two of the century's scariest horror films inside an MRI machine while recording their brain activity, sharing their findings this month in NeuroImage.

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Sex, money and food: fMRI reveals how the brain processes rewards

These three items activate similar brain locations, according to the study published this month in Brain and Imaging Behavior, but do so in very different ways.

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AI reads images in milliseconds—bringing low-cost malaria detection to resource-strapped areas

The deep learning model can identify parasites that cause the disease in blood sample images as accurately as human experts, but in a fraction of the time, researchers wrote in the Journal of Digital Imaging.

 

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Experts urge radiology to be more cognizant of image resolution’s impact on AI

Two researchers found that using certain pixel dimensions helped tailor algorithms to detect specific abnormalities, and pushed radiology to keep this in mind when using such approaches.

Around the web

Positron, a New York-based nuclear imaging company, will now provide Upbeat Cardiology Solutions with advanced PET/CT systems and services. 

The nuclear imaging isotope shortage of molybdenum-99 may be over now that the sidelined reactor is restarting. ASNC's president says PET and new SPECT technologies helped cardiac imaging labs better weather the storm.

CMS has more than doubled the CCTA payment rate from $175 to $357.13. The move, expected to have a significant impact on the utilization of cardiac CT, received immediate praise from imaging specialists.