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公开(公告)号：US11545266B2
公开(公告)日：2023-01-03
申请号：US16588080
申请日：2019-09-30
申请人： GE Precision Healthcare LLC , Partners HealthCare System, Inc. , The General Hospital Corporation , The Brigham and Women's Hospital, Inc.
发明人： John Francis Kalafut , Bernardo Bizzo , Stefano Pedemonte , Christopher Bridge , Neil Tenenholtz , Ramon Gilberto Gonzalez
摘要： Systems and techniques for generating and/or employing a medical imaging stroke model are presented. In one example, a system employs a convolutional neural network to generate output data regarding a brain anatomical region based on diffusion-weighted imaging (DWI) data associated with the brain anatomical region and apparent diffusion coefficient (ADC) data associated with the brain anatomical region. The system also detects presence or absence of a medical stroke condition associated with the brain anatomical region based on the output data.
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公开(公告)号：US11331056B2
公开(公告)日：2022-05-17
申请号：US16588013
申请日：2019-09-30
申请人： GE Precision Healthcare LLC , Partners HealthCare System, Inc. , The General Hospital Corporation , The Brigham and Women's Hospital, Inc.
摘要： Systems and techniques for generating and/or employing a computed tomography (CT) medical imaging stroke model are presented. In one example, a system employs a convolutional neural network to generate learned medical imaging stroke data regarding a brain anatomical region based on CT data associated with the brain anatomical region and diffusion-weighted imaging (DWI) data associated with one or more segmentation masks for the brain anatomical region. The system also detects presence or absence of a medical stroke condition in a CT image based on the learned medical imaging stroke data.
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公开(公告)号：US11367179B2
公开(公告)日：2022-06-21
申请号：US16588129
申请日：2019-09-30
申请人： GE Precision Healthcare LLC , Partners Healthcare System, Inc. , The General Hospital Corporation , The Brigham and Women's Hospital, Inc.
发明人： Jason Polzin , Bernardo Bizzo , Bradley Wright , John Kirsch , Pamela Schaefer
摘要： Systems and techniques for determining degree of motion using machine learning to improve medical image quality are presented. In one example, a system generates, based on a convolutional neural network, motion probability data indicative of a probability distribution of a degree of motion for medical imaging data generated by a medical imaging device. The system also determines motion score data for the medical imaging data based on the motion probability data.
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公开(公告)号：US20210097679A1
公开(公告)日：2021-04-01
申请号：US16588129
申请日：2019-09-30
申请人： GE Precision Healthcare LLC , Partners HealthCare System, Inc. , The General Hospital Corporation , The Brigham and Women's Hospital, Inc.
发明人： Jason Polzin , Bernardo Bizzo , Bradley Wright , John Kirsch , Pamela Schaefer
摘要： Systems and techniques for determining degree of motion using machine learning to improve medical image quality are presented. In one example, a system generates, based on a convolutional neural network, motion probability data indicative of a probability distribution of a degree of motion for medical imaging data generated by a medical imaging device. The system also determines motion score data for the medical imaging data based on the motion probability data.
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公开(公告)号：US20210093278A1
公开(公告)日：2021-04-01
申请号：US16587828
申请日：2019-09-30
申请人： GE Precision Healthcare LLC , Partners HealthCare System, Inc. , The General Hospital Corporation , The Brigham and Women's Hospital, Inc.
发明人： John Francis Kalafut , Bernardo Bizzo , Behrooz Hashemian , Christopher Bridge , Neil Tenenholtz , Stuart Robert Pomerantz
摘要： Systems and techniques for generating and/or employing a computed tomography (CT) medical imaging intracranial hemorrhage model are presented. In one example, a system employs a convolutional neural network to generate classification output data regarding a brain anatomical region based on computed tomography (CT) data associated with the brain anatomical region. The system also detects presence or absence of a medical intracranial hemorrhage condition in the CT data based on the classification output data. Furthermore, the system determines a subtype of the medical intracranial hemorrhage condition based on the classification output data. The system also generates display data associated with the subtype of the medical intracranial hemorrhage condition in a human-interpretable format.
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公开(公告)号：US20210093258A1
公开(公告)日：2021-04-01
申请号：US16588013
申请日：2019-09-30
申请人： GE Precision Healthcare LLC , Partners HealthCare System, Inc. , The General Hospital Corporation , The Brigham and Women's Hospital, Inc.
摘要： Systems and techniques for generating and/or employing a computed tomography (CT) medical imaging stroke model are presented. In one example, a system employs a convolutional neural network to generate learned medical imaging stroke data regarding a brain anatomical region based on CT data associated with the brain anatomical region and diffusion-weighted imaging (DWI) data associated with one or more segmentation masks for the brain anatomical region. The system also detects presence or absence of a medical stroke condition in a CT image based on the learned medical imaging stroke data.
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公开(公告)号：US20210098127A1
公开(公告)日：2021-04-01
申请号：US16588080
申请日：2019-09-30
申请人： GE Precision Healthcare LLC , Partners HealthCare System, Inc. , The General Hospital Corporation , The Brigham and Women?s Hospital, Inc.
发明人： John Francis Kalafut , Bernardo Bizzo , Stefano Pedemonte , Christopher Bridge , Neil Tenenholtz , Ramon Gilberto Gonzalez
摘要： Systems and techniques for generating and/or employing a medical imaging stroke model are presented. In one example, a system employs a convolutional neural network to generate output data regarding a brain anatomical region based on diffusion-weighted imaging (DWI) data associated with the brain anatomical region and apparent diffusion coefficient (ADC) data associated with the brain anatomical region. The system also detects presence or absence of a medical stroke condition associated with the brain anatomical region based on the output data.
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