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We recently published a deep learning study on the potential ofencoder-decoder networks for the segmentation of the 2D CAMUS ultrasounddataset. We propose in this abstract an extension of the evaluation criteria toanatomical assessment, as traditional geometric and clinical metrics in cardiacsegmentation do not take into account the anatomical correctness of thepredicted shapes. The completed study sheds a new light on the ranking ofmodels.

Deep Learning Segmentation in 2D echocardiography using the CAMUS dataset : Automatic Assessment of the Anatomical Shape Validity