A research team from Leipzig University, the Max Planck Institute and Heidelberg University, all in Germany, devised a new segmentation algorithm for stroke lesions that improves upon previous methods. They used machine-learning models to effect CT image segmentation in the early stages of acute stroke. The research team published their findings on the fully convolutional graph network in July in the Journal of Medical Imaging.
A research team from Leipzig University, the Max Planck Institute and Heidelberg University, all in Germany, devised a new segmentation algorithm for stroke lesions that improves upon previous methods. They used machine-learning models to effect CT image segmentation in the early stages of acute stroke. The research team published their findings on the fully convolutional graph network in July in the Journal of Medical Imaging.
LONDON – The U.K. National Institute for Health and Care Excellence (NICE) has published new advice on how and when artificial intelligence (AI) could be applied to the interpretation of mammograms and chest computer tomography images, in a move that is intended to set the ground rules for the uptake of these technologies. In population breast screening, NICE looked at how five AI systems could be used to pick out mammography images that need further assessment, supporting qualified radiologists in their interpretation.