Patents by Inventor Francesco Cognolato

Francesco Cognolato 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).

  • Method and system for determining a magnetic susceptibility distribution
    Patent number: 11940519
    Abstract: A training method for training neural networks to determine a magnetic susceptibility distribution of a sample may include: storing a simulated magnetic susceptibility map of the sample, generating a modified magnetic susceptibility map by combining an influence of one or more external magnetic susceptibility sources with the simulated magnetic susceptibility map and storing the modified magnetic susceptibility maps. The method may include generating a first training image by applying a quantitative susceptibility mapping model the modified magnetic susceptibility map and storing the first training image, applying the first neural network to the first image and a second neural network to an output of the first neural network and changing network parameters of the first and the second neural network depending on a deviation of an output of the second artificial neural network from the simulated magnetic susceptibility map.
    Type: Grant
    Filed: April 21, 2022
    Date of Patent: March 26, 2024
    Assignee: Siemens Healthineers AG
    Inventors: Kieran O'Brien, Jin Jin, Steffen Bollmann, Markus Barth, Francesco Cognolato
  • Method and System for Determining a Magnetic Susceptibility Distribution
    Publication number: 20220342022
    Abstract: A training method for training neural networks to determine a magnetic susceptibility distribution of a sample may include: storing a simulated magnetic susceptibility map of the sample, generating a modified magnetic susceptibility map by combining an influence of one or more external magnetic susceptibility sources with the simulated magnetic susceptibility map and storing the modified magnetic susceptibility maps. The method may include generating a first training image by applying a quantitative susceptibility mapping model the modified magnetic susceptibility map and storing the first training image, applying the first neural network to the first image and a second neural network to an output of the first neural network and changing network parameters of the first and the second neural network depending on a deviation of an output of the second artificial neural network from the simulated magnetic susceptibility map.
    Type: Application
    Filed: April 21, 2022
    Publication date: October 27, 2022
    Applicants: Siemens Healthcare GmbH, The University of Queensland
    Inventors: Kieran O'Brien, Jin Jin, Steffen Bollmann, Markus Barth, Francesco Cognolato