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Gated Blood-Pool Imaging

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Fully Automatic Quantitative Measurement of Equilibrium Radionuclide Angiocardiography Using a Convolutional Neural Network.

Clinical nuclear medicine 38967505
PURPOSE: The aim of this study was to generate deep learning-based regions of interest (ROIs) from equilibrium radionuclide angiography datasets for left ventricular ejection fraction (LVEF) measurement.
Aged Angiocardiography Automation Deep Learning Female Gated Blood-Pool Imaging Humans Image Processing, Computer-Assisted Male Middle Aged Neural Networks, Computer Stroke Volume
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