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Article Synopsis
  • Left ventricular ejection fraction (LVEF) is crucial for assessing heart function, and accurate segmentation of echocardiograms is essential for this measurement.
  • Traditional methods relying on convolutional neural networks (CNN) have shown good results, but their limited receptive fields can hinder effective segmentation of the large left ventricle area.
  • Recent research introduces two innovative models using Vision Transformer frameworks which significantly improve segmentation accuracy, achieving over 92% Dice similarity scores, outperforming many existing CNN approaches.
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