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公开(公告)号:US20240050053A1
公开(公告)日:2024-02-15
申请号:US18280192
申请日:2021-11-29
Applicant: Bayer Aktiengesellschaft
Inventor: Matthias LENGA , Marvin PURTORAB
Abstract: The present invention relates to the technical field of producing artificial contrast-enhanced radiological images by way of machine learning methods.
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公开(公告)号:US20240404255A1
公开(公告)日:2024-12-05
申请号:US18678323
申请日:2024-05-30
Applicant: BAYER AKTIENGESELLSCHAFT
Inventor: Matthias LENGA , Ivo Matteo BALTRUSCHAT , Parvaneh JANBAKHSHI , Felix Karl KREIS
IPC: G06V10/774 , A61K49/10 , G06V10/82
Abstract: The present disclosure is concerned with the technical field of generation of artificial contrast-enhanced radiological images.
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公开(公告)号:US20240404061A1
公开(公告)日:2024-12-05
申请号:US18732938
申请日:2024-06-04
Applicant: BAYER AKTIENGESELLSCHAFT
Inventor: Matthias LENGA , Ivo Matteo BALTRUSCHAT
Abstract: The present disclosure relates to the technical field of generation of synthetic medical images. The subjects of the present disclosure are a method, a computer system and a computer-readable storage medium comprising a computer program for detecting artifacts in synthetic medical images.
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公开(公告)号:US20240212811A1
公开(公告)日:2024-06-27
申请号:US18288963
申请日:2022-04-20
Applicant: Bayer Aktiengesellschaft
Inventor: Steffen VOGLER , Johannes HOEHNE , Matthias LENGA
IPC: G16H15/00 , G06V10/774 , G06V10/776 , G06V10/80 , G16H10/60
CPC classification number: G16H15/00 , G06V10/774 , G06V10/776 , G06V10/803 , G16H10/60 , G06V2201/03
Abstract: A method for training a machine learning model that is able to establish links between data of different modalities by creating a joint representation. In particular, application of the method to medical data including electronic medical records and medical images and/or other medical data. The trained machine learning model can among others fulfil tasks such as autocompletion of incomplete data, detection of uncertain and/or spurious data, generation of probable data and other tasks.
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公开(公告)号:US20250045926A1
公开(公告)日:2025-02-06
申请号:US18776651
申请日:2024-07-18
Applicant: BAYER AKTIENGESELLSCHAFT
Inventor: Matthias LENGA , Ivo Matteo BALTRUSCHAT
IPC: G06T7/00 , A61B5/055 , A61B6/03 , A61K49/10 , G06T11/00 , G06V10/774 , G06V10/776
Abstract: The present disclosure relates to the technical field of generation of synthetic images, in particular synthetic medical images. The subjects of the present disclosure are a method, a computer system and a computer-readable storage medium comprising a computer program for detecting artifacts in synthetic images, in particular synthetic medical images.
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公开(公告)号:US20240242350A1
公开(公告)日:2024-07-18
申请号:US18565422
申请日:2022-05-25
Applicant: Bayer Aktiengesellschaft
Inventor: Matthias LENGA
IPC: G06T7/00
CPC classification number: G06T7/0012 , G06T2207/10072 , G06T2207/20081 , G06T2207/20084
Abstract: The present invention relates to the technical field of producing artificial contrast-enhanced radiological images by way of machine learning methods.
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公开(公告)号:US20240153163A1
公开(公告)日:2024-05-09
申请号:US18281275
申请日:2021-11-29
Applicant: Bayer Aktiengesellschaft
Inventor: Matthias LENGA , Marvin PURTORAB
CPC classification number: G06T11/006 , G06T7/0016 , G06T2207/10088 , G06T2207/20056 , G06T2207/20081 , G06T2207/20084 , G06T2207/30061 , G06T2207/30096 , G06T2210/41 , G06T2211/441
Abstract: The present invention relates to the technical field of producing artificial contrast-enhanced radiological images by way of machine learning methods.
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公开(公告)号:US20240070440A1
公开(公告)日:2024-02-29
申请号:US18280160
申请日:2022-02-23
Applicant: Bayer Aktiengesellschaft
Inventor: Johannes HOEHNE , Steffen VOGLER , Matthias LENGA
IPC: G06N3/0455
CPC classification number: G06N3/0455
Abstract: Systems, methods, and computer programs disclosed herein relate to training a machine learning model to generate multimodal representations of objects, and to the use of said representations for predictive purposes.
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公开(公告)号:US20240403625A1
公开(公告)日:2024-12-05
申请号:US18294532
申请日:2022-07-22
Applicant: Bayer Aktiengesellschaft
Inventor: Steffen VOGLER , Johannes HOEHNE , Matthias LENGA
Abstract: The following disclosure relates to the field of data analysis, in particular medical data analysis, or more particularly relates to systems, apparatuses, and methods for processing in particular medical data stored in different modalities, so-called multi-modal data. In some embodiments, the disclosure relates to similarity retrieval for input data, in particular medical input data.
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公开(公告)号:US20240289637A1
公开(公告)日:2024-08-29
申请号:US18573793
申请日:2022-06-17
Applicant: Bayer Aktiengesellschaft
Inventor: Matthias LENGA , Johannes HÖHNE , Steffen VOGLER
IPC: G06N3/098
CPC classification number: G06N3/098
Abstract: The present invention relates to the technical field of federated learning. Subject matter of the present invention is a method for (re-)training a federated learning system, a computer system for carrying out the method, and a non-transitory computer-readable storage medium comprising processor-executable instructions with which to perform an operation for (re-)training a federated learning system.
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