Explore more about: Image processing

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An automated tool captures circulating tumor cells in children with central nervous system cancers. The tool could make it easier to identify tumors that don't respond to treatment.
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A new wearable brain scanner is the first of its kind to accurately record magnetic fields generated by brain activity while people are in motion.
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Traditional medical imaging works great for people with light skin but has trouble getting clear pictures from patients with darker skin. A Johns Hopkins University–led team found a way to deliver clear pictures of anyone's internal anatomy, no matter their skin tone.  Source: Johns Hopkins University
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One team helped develop the first photon-counting detector (PCD)-CT system, which is superior to current CT technology. Another team has also been using artificial intelligence to lower the dose of radiation given to a patient when they are undergoing a conventional CT brain scan.
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– The National Institutes of Health are helping to fund an evolution in medical imaging, and a University at Buffalo-led research team is leading the way. Jun Xia, PhD, associate professor in the Department of Biomedical Engineering, received a $1.6 million grant to improve medical imaging for people with chronic leg ulcers. The project is a collaboration with the surgery clinic of UBMD Physician’s Group and other UB researchers.
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A team of NIH microscopists and computer scientists used a type of artificial intelligence called a neural network to obtain clearer pictures of cells at work even with extremely low, cell-friendly light levels.
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A team of engineers has demonstrated how a new algorithm they developed was able to successfully predict whether or not a COVID-19 patient would need ICU intervention. This artificial intelligence-based approach could be a valuable tool in determining a proper course of treatment for individual patients.
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NIBIB-funded researchers at NYU Langone Health worked with Facebook AI researchers to develop a method to speed up MRI scans.
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NIBIB-funded researchers have developed a way to use artificial intelligence to speed up MRI imaging without sacrificing quality.
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QuantX backstops radiologists with AI-enabled software that analyzes MRIs to confirm or challenge their diagnosis.