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- W4296196909 abstract "Abstract We propose a new method to automatically contour the left ventricle on 2D echocardiographic images. Unlike most existing segmentation methods, which are based on predicting segmentation masks, we focus at predicting the endocardial contour and the key landmark points within this contour (basal points and apex). This provides a representation that is closer to how experts perform manual annotations and hence produce results that are physiologically more plausible. Our proposed method uses a two-headed network based on the U-Net architecture. One head predicts the 7 contour points, and the other head predicts a distance map to the contour. This approach was compared to the U-Net and to a point based approach, achieving performance gains of up to 22% in terms of landmark localisation ( $${<}4.5$$ <mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML> <mml:mrow> <mml:mo><</mml:mo> <mml:mn>4.5</mml:mn> </mml:mrow> </mml:math> mm) and distance to the ground truth contour ( $${<}3.0$$ <mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML> <mml:mrow> <mml:mo><</mml:mo> <mml:mn>3.0</mml:mn> </mml:mrow> </mml:math> mm)." @default.
- W4296196909 created "2022-09-18" @default.
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- W4296196909 date "2022-01-01" @default.
- W4296196909 modified "2023-10-06" @default.
- W4296196909 title "Left Ventricle Contouring of Apical Three-Chamber Views on 2D Echocardiography" @default.
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- W4296196909 doi "https://doi.org/10.1007/978-3-031-16902-1_10" @default.
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