Abstract: A method and a system automatically generate a digital representation of an annulus structure of a valve from a segmented digital representation of a human internal heart. The basis for the segmented digital representation is multi-slice computed tomography image data. The method includes automatically determining, for at least a first effective time point, based on a segmentation, i.e. labels, of a provided input segmented digital representation, a candidate plane, and/or a candidate orientation vector together with a candidate center point, arranged with respect to the input segmented digital representation for the first effective time point, and candidate points for the annulus structure are determined automatically. From the candidate points acting as support points, a candidate spline interpolation is generated which is then adapted based on the input segmented digital representation.

Abstract: The invention provides a system and method for training artificial neural networks for solving multiple tasks simultaneously, wherein the artificial neural network comprises at least one capsule layer. The invention also provides a system and a method for solving multiple tasks simultaneously, wherein the artificial neural network comprises at least one capsule layer. The invention further provides additional connected aspects.

Abstract: The present invention provides a system and a computer-implemented method for generating at least one 4-dimensional medical image segmentation for at least one structure of a human heart. The method includes the steps of: providing a first n 4-dimensional medical image comprising the at least one structure of the human heart, the medical image being based on a computed tomography scan image; generating a segmentation of at least part of the provided first 4-dimensional medical image using at least one first trained artificial neural network, wherein the at least one first trained artificial neural network is configured as a convolutional processing network with U-net architecture; and generating at least one 4-dimensional medical image segmentation for the at least one structure of the human heart based at least on the segmentation generated by the at least one first trained artificial neural network.

Abstract: A method and a system automatically generate a digital representation of an annulus structure of a valve from a segmented digital representation of a human internal heart. The basis for the segmented digital representation is multi-slice computed tomography image data. The method includes automatically determining, for at least a first effective time point, based on a segmentation, i.e. labels, of a provided input segmented digital representation, a candidate plane, and/or a candidate orientation vector together with a candidate center point, arranged with respect to the input segmented digital representation for the first effective time point, and candidate points for the annulus structure are determined automatically. From the candidate points acting as support points, a candidate spline interpolation is generated which is then adapted based on the input segmented digital representation.