Patents by Inventor Sara LORIO

Sara LORIO 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).

  • Implicit registration for improving synthesized full-contrast image prediction tool
    Patent number: 12646148
    Abstract: A method of training a prediction tool to generate at least one synthetic full-contrast image from zero-contrast and low-contrast images of a subject may involve receiving a training set a set of images of a set of subjects, the images of each subject comprising a full-contrast image, a low-contrast image, a first zero-contrast image acquired prior to the acquisition of the full-contrast image, and a second zero-contrast image acquired prior to the acquisition of the low-contrast image. An artificial neural network may be trained with the training set by applying the first and second zero-contrast images from the set of images and the low-contrast images from the set of images as input to the artificial neural network and using a cost function to compare the output of the artificial neural network with the full-contrast images from the set of images to train parameters of the artificial neural network using backpropagation.
    Type: Grant
    Filed: April 13, 2022
    Date of Patent: June 2, 2026
    Assignee: BAYER AKTIENGESELLSCHAFT
    Inventors: Veronica Corona, Marvin Purtorab, Sara Lorio, Thiago Ramos Dos Santos
  • PROSTATE CANCER LOCAL STAGING
    Publication number: 20260051049
    Abstract: Systems, methods, and computer programs disclosed herein relate to prostate cancer local staging based on multi-parametric magnetic resonance imaging images using a trained machine learning model.
    Type: Application
    Filed: August 8, 2023
    Publication date: February 19, 2026
    Inventors: Sara LORIO, Katharina URBAN
  • ACTOR-CRITIC APPROACH FOR GENERATING SYNTHETIC IMAGES
    Publication number: 20240303973
    Abstract: The present invention provides a technique for model improvement in supervised learning with potential applications to a variety of imaging tasks, such as segmentation, registration, detection. In particular, it has shown potential in medical imaging enhancement.
    Type: Application
    Filed: February 16, 2022
    Publication date: September 12, 2024
    Applicant: Bayer Aktiengesellschaft
    Inventors: Thiago RAMOS DOS SANTOS, Veronica CORONA, Marvin PURTORAB, Sara LORIO
  • IMPLICIT REGISTRATION FOR IMPROVING SYNTHESIZED FULL-CONTRAST IMAGE PREDICTION TOOL
    Publication number: 20240193738
    Abstract: A method of training a prediction tool to generate at least one synthetic full-contrast image from zero-contrast and low-contrast images of a subject may involve receiving a training set a set of images of a set of subjects, the images of each subject comprising a full-contrast image, a low-contrast image, a first zero-contrast image acquired prior to the acquisition of the full-contrast image, and a second zero-contrast image acquired prior to the acquisition of the low-contrast image. An artificial neural network may be trained with the training set by applying the first and second zero-contrast images from the set of images and the low-contrast images from the set of images as input to the artificial neural network and using a cost function to compare the output of the artificial neural network with the full-contrast images from the set of images to train parameters of the artificial neural network using backpropagation.
    Type: Application
    Filed: April 13, 2022
    Publication date: June 13, 2024
    Applicant: Bayer Aktiengesellschaft
    Inventors: Veronica CORONA, Marvin PURTORAB, Sara LORIO, Thiago RAMOS DOS SANTOS