公开(公告)号：US20240185577A1

公开(公告)日：2024-06-06

申请号：US18285361

申请日：2022-03-24

Applicant: Bayer Aktiengesellschaft

Inventor： Matthias LENGA ,  Marvin PURTORAB ,  Thiago RAMOS DOS SANTOS ,  Jens HOOGE ,  Veronica CORONA

IPC: G06V10/774 ,  G06V10/22 ,  G06V10/32 ,  G06V10/82

CPC classification number: G06V10/774 ,  G06V10/22 ,  G06V10/32 ,  G06V10/82 ,  G06V2201/031

Abstract: The present invention relates to the technical field of machine learning. Subject matter of the present invention is a novel approach for training a neural network and the use of this approach for the processing of (medical) images.

公开(公告)号：US20240050054A1

公开(公告)日：2024-02-15

申请号：US18280193

申请日：2021-11-29

Applicant: Bayer Aktiengesellschaft

Inventor： Matthias LENGA ,  Marvin PURTORAB

IPC: A61B6/00 ,  A61B6/03 ,  A61B8/08

CPC classification number: A61B6/481 ,  A61B6/032 ,  A61B8/481

Abstract: A method for providing a prediction of a representation of an examination region that was generated using a medical image technique involving a contrast agent may include receiving a first representation in frequency space of an examination region of an examination object, receiving a second representation in the frequency space of the examination region of the examination object, providing the first representation and the second representation as an input to a predictive machine learning model that is configured to provide, as an output, a prediction of a representation in the frequency space of the examination region with an amount of the contrast agent administered during a medical imaging technique, receiving the output of the predictive machine learning model based on the input, and converting the output of the predictive machine learning model to a representation in real space of the examination region of the examination object.