Deep learning for arterial analysis and assessment
The present disclosure relates to training one or more neural networks for vascular vessel assessment using synthetic image data for which ground-truth data is known. In certain implementations, the synthetic image data may be based in part, or derived from, clinical image data for which ground-truth data is not known or available. Neural networks trained in this manner may be used to perform one or more of vessel segmentation, decalcification, Hounsfield unit scoring, and/or estimation of a hemodynamic parameter.
General Electric Company
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Xia Prem Jed Douglas Xin James Vradenburg Peter Michael
Li Venugopal Pack Wang Miller Edic