Patents by Inventor Michael Schwier

Michael Schwier 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).

  • Regression-based approach for measurement of rotator cuff tears in shoulder MRI images
    Patent number: 12555230
    Abstract: Systems and methods for calculating a distance between a first point and a second point of an anatomical landmark are provided. An input medical image of an anatomical landmark of a patient is received. One or more probability maps predicting a first point and a second point of the anatomical landmark in the input medical image are generated using a machine learning based model. Locations of the first point and the second point in the input medical image are determined based on the one or more probability maps. A distance between the first point and the second point is calculated based on the locations. The locations of the first point and the second point in the input medical image and/or the calculated distance between the first point and the second point are output.
    Type: Grant
    Filed: March 28, 2023
    Date of Patent: February 17, 2026
    Assignee: Siemens Healthineers AG
    Inventors: Jianing Wang, Michael Schwier, Bernhard Geiger, Sasa Grbic
  • Determining characteristics of muscle structures using artificial neural network
    Patent number: 12354730
    Abstract: Techniques of determining a quantification of at least one characteristic of a muscle structure comprising at least one muscle and at least one tendon are disclosed. The quantification of the at least one characteristic of the rotator cuff may be determined by using at least one artificial neural network and based on one or more medical images depicting the muscle structure of a patient.
    Type: Grant
    Filed: May 9, 2022
    Date of Patent: July 8, 2025
    Assignees: Siemens Healthineers AG, New York University
    Inventors: Michael Schwier, Bernhard Geiger, Sasa Grbic, Esther Raithel, Dana Lin, Guillaume Chabin
  • REGRESSION-BASED APPROACH FOR MEASUREMENT OF ROTATOR CUFF TEARS IN SHOULDER MRI IMAGES
    Publication number: 20240331138
    Abstract: Systems and methods for calculating a distance between a first point and a second point of an anatomical landmark are provided. An input medical image of an anatomical landmark of a patient is received. One or more probability maps predicting a first point and a second point of the anatomical landmark in the input medical image are generated using a machine learning based model. Locations of the first point and the second point in the input medical image are determined based on the one or more probability maps. A distance between the first point and the second point is calculated based on the locations. The locations of the first point and the second point in the input medical image and/or the calculated distance between the first point and the second point are output.
    Type: Application
    Filed: March 28, 2023
    Publication date: October 3, 2024
    Inventors: Jianing Wang, Michael Schwier, Bernhard Geiger, Sasa Grbic
  • Intuitive display for rotator cuff tear diagnostics
    Patent number: 12076158
    Abstract: Systems and methods for an intuitive display of one or more anatomical objects are provided. One or more 3D medical images of one or more anatomical objects of a patient are received. Correspondences between the one or more 3D medical images and points on a 2D map representing the one or more anatomical objects are determined. The 2D map is updated with patient information extracted from the one or more 3D medical images. The updated 2D map with the determined correspondences is output.
    Type: Grant
    Filed: February 5, 2021
    Date of Patent: September 3, 2024
    Assignees: Siemens Healthineers AG, New York University
    Inventors: Bernhard Geiger, Michael Schwier, Sasa Grbic, Esther Raithel, Dana Lin, Guillaume Chabin
  • DETERMINING CHARACTERISTICS OF MUSCLE STRUCTURES USING ARTIFICIAL NEURAL NETWORK
    Publication number: 20220392614
    Abstract: Techniques of determining a quantification of at least one characteristic of a muscle structure comprising at least one muscle and at least one tendon are disclosed. The quantification of the at least one characteristic of the rotator cuff may be determined by using at least one artificial neural network and based on one or more medical images depicting the muscle structure of a patient.
    Type: Application
    Filed: May 9, 2022
    Publication date: December 8, 2022
    Inventors: Michael Schwier, Bernhard Geiger, Sasa Grbic, Esther Raithel, Dana Lin, Guillaume Chabin
  • INTUITIVE DISPLAY FOR ROTATOR CUFF TEAR DIAGNOSTICS
    Publication number: 20220249014
    Abstract: Systems and methods for an intuitive display of one or more anatomical objects are provided. One or more 3D medical images of one or more anatomical objects of a patient are received. Correspondences between the one or more 3D medical images and points on a 2D map representing the one or more anatomical objects are determined. The 2D map is updated with patient information extracted from the one or more 3D medical images. The updated 2D map with the determined correspondences is output.
    Type: Application
    Filed: February 5, 2021
    Publication date: August 11, 2022
    Inventors: Bernhard Geiger, Michael Schwier, Sasa Grbic, Esther Raithel, Dana Lin, Guillaume Chabin