Imaging researchers at NYU Langone have used deep learning to turn noise against itself in order to improve low-field MRI. They’re after something much bigger than sharper images.
Tag: Artificial Intelligence
Computed tomography (CT) scans of the chest, abdomen, and spine, taken originally to detect problems such as kidney stones or growths on the lungs, can be repurposed through artificial intelligence (AI) to catch signs of bone loss, a new study shows.
Imaging scientists at NYU Langone have created an AI model that assesses MRI data during the exam to inform the remainder of the imaging session.
Lavanya Umapathy, postdoctoral fellow who develops representation learning models for medical imaging, talks about improving prostate-cancer screening and using artificial intelligence to approach “the person behind the images.”
Congratulations to Jungkyu Park on a successful defense of his doctoral dissertation in biomedical imaging and technology at NYU Grossman School of Medicine.
Eros Montin, research scientist who develops MRI simulation software and investigates radiomics, talks about building a virtual scanner, using orthogonal information, and what he thinks about while walking down the street.
The fastMRI dataset now includes curated breast MRI data to boost AI innovation in radial, dynamic contrast-enhanced, ultrafast MRI of the breast.
With the help of an AI tool, CT scans taken to look for tumors or bleeding or infections, also revealed calcium buildup in arteries, a sign of worsening cardiovascular disease.
Since 2014, the Center for Advanced Imaging Innovation and Research has been in the lead of technological shifts in magnetic resonance imaging. An award from the National Institutes of Health is extending the center’s mandate for a third five-year term.
Marcelo Zibetti, imaging scientist at NYU Langone Health, talks about efficiency in MRI, the value of differing vantage points, and learning by thinking across disciplines.