Patents by Inventor Julian Praceus

Julian Praceus has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 11836924
    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.
    Type: Grant
    Filed: September 25, 2019
    Date of Patent: December 5, 2023
    Assignee: LARALAB GmbH
    Inventors: Julian Praceus, Aleksei Vasilev
  • Publication number: 20220028085
    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.
    Type: Application
    Filed: December 2, 2019
    Publication date: January 27, 2022
    Inventors: Aleksei Vasilev, Julian Praceus
  • Publication number: 20220012887
    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.
    Type: Application
    Filed: September 25, 2019
    Publication date: January 13, 2022
    Inventors: Julian Praceus, Aleksei Vasilev