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AI functions in x-ray systems may save radiographers time

AuntMinnie

Intelligent virtual and AI-based collimation features appear to save radiographers time during x-ray image acquisitions – a key function for enabling more patient-focused workflows, according to a recent study. To that end, the researchers conducted an observational study at five clinical sites in Europe and the U.S.

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What's best practice for using AI for thoracic imaging?

AuntMinnie

The use of AI in thoracic imaging has begun to demonstrate "cumulative evidence of effectiveness," but more testing and research are needed to determine its feasibility for this application, according to a commentary published February 25 in Radiology. van Beek, MD, of the University of Edinburgh in the U.K. in an accompanying editorial.

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Generative AI model validated in chest x-ray study

AuntMinnie

In a reader study involving five radiologists interpreting 758 chest x-rays, use of the model (AIRead, Soombit.ai) reduced average reading times by 14 seconds per image and increased sensitivities for certain findings. Image and caption courtesy of RSNA. AP = anterior-posterior. seconds 20.4 seconds 12.5

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Moore’s Law for radiologists

AuntMinnie

Some of my radiological heroes would report a staggering 30,000 to 40,000 radiographs a year. The scanners could reconstruct images faster than we could report them. Some even [startled gasp] gave up reporting plain radiographs. A good day five to 10 years ago was reporting 40 cross-sectional imaging studies.

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Generative AI, radiologist shortages feature in 2024 Minnies

AuntMinnie

Middlebrooks, MD, Mayo Clinic, Jacksonville, FL Erik H. Middlebrooks, MD, of the Mayo Clinic in Jacksonville, FL. His lab team is currently focused on "implementing advanced techniques, such as parallel transmit, to achieve more consistent image quality and fully harness the power of 7T for every patient," Middlebrooks said.

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Can AI help chest DDR achieve clinical adoption?

AuntMinnie

Chest dynamic digital radiography (DDR) may have received a boost toward clinical use in patients with lung disorders, with researchers developing AI to perform time-consuming analysis involved in the technology, according to researchers in New York City. a) Raw example of a dynamic digital radiograph. (b)

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Deep learning combines breast imaging data to predict cancer prognosis

AuntMinnie

Deep-learning models could have potential as predictive tools for breast cancer prognosis, a study published January 17 in Clinical Breast Cancer has found. They collected imaging data to establish deep-learning models using ResNet50. This means the combined model could predict prognosis after surgery.

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