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公开(公告)号:US20230237658A1
公开(公告)日:2023-07-27
申请号:US18193275
申请日:2023-03-30
Applicant: Lunit Inc.
Inventor: Chan-Young Ock , Dongguen Yoo , Kyunghyun Paeng
CPC classification number: G06T7/0012 , G06V20/695 , G06V10/945 , G16H30/20 , G06T2207/30096 , G06T2207/20092 , G06V2201/03
Abstract: The present disclosure relates to a method, performed by at least one processor of an information processing system, of analyzing a pathological image. The method includes receiving a pathological image, detecting an object associated with medical information, in the received pathological image by using a machine learning model, generating an analysis result on the received pathological image, based on a result of the detecting, and outputting medical information about at least one region included in the pathological image, based on the analysis result.
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公开(公告)号:US12266196B2
公开(公告)日:2025-04-01
申请号:US18491314
申请日:2023-10-20
Applicant: Lunit Inc.
Inventor: Biagio Brattoli , Chan-Young Ock , Wonkyung Jung , Soo Ick Cho , Kyunghyun Paeng , Dong Geun Yoo
Abstract: Provided is a method for analysing a pathology image, which is performed by at least one processor and includes acquiring a pathology image, inputting the acquired pathology image into a machine learning model and acquiring an analysis result for the pathology image from the machine learning model, and outputting the acquired analysis result, in which the machine learning model is a model trained by using a training data set generated based on a first pathology data set associated with a first domain and a second pathology data set associated with a second domain different from the first domain.
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公开(公告)号:US20250069420A1
公开(公告)日:2025-02-27
申请号:US18946457
申请日:2024-11-13
Applicant: Lunit Inc.
Inventor: Biagio BRATTOLI , Chan-Young Ock , Wonkyung Jung , Soo Ick Cho , Kyunghyun Paeng , Dong Geun Yoo
Abstract: Provided is a method for analysing a pathology image, which is performed by at least one processor and includes acquiring a pathology image, inputting the acquired pathology image into a machine learning model and acquiring an analysis result for the pathology image from the machine learning model, and outputting the acquired analysis result, in which the machine learning model is a model trained by using a training data set generated based on a first pathology data set associated with a first domain and a second pathology data set associated with a second domain different from the first domain.
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公开(公告)号:US20220036549A1
公开(公告)日:2022-02-03
申请号:US17502661
申请日:2021-10-15
Applicant: LUNIT Inc.
Inventor: Donggeun Yoo , Chanyoung Ock , Kyunghyun Paeng
Abstract: The present disclosure relates to a method, performed by at least one computing device, for providing information associated with immune phenotype for pathology slide image. The method may include obtaining information associated with immune phenotype for one or more regions of interest (ROIs) in a pathology slide image, generating, based on the information associated with the immune phenotype for one or more ROIs, an image indicative of the information associated with the immune phenotype, and outputting the image indicative of the information associated with immune phenotype.
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公开(公告)号:US12266447B2
公开(公告)日:2025-04-01
申请号:US17502304
申请日:2021-10-15
Applicant: LUNIT INC.
Inventor: Donggeun Yoo , Jeong Hoon Lee , Kyunghyun Paeng
Abstract: A method for generating a medical prediction related to a biomarker from medical data is provided, which includes obtaining medical data associated with a patient, determining a region of interest in the medical data, extracting one or more features associated with the medical data based on the region of interest, and generating a medical prediction for the patient based on the extracted one or more features.
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公开(公告)号:US12205288B2
公开(公告)日:2025-01-21
申请号:US18193275
申请日:2023-03-30
Applicant: Lunit Inc.
Inventor: Chan-Young Ock , Donggeun Yoo , Kyunghyun Paeng
Abstract: The present disclosure relates to a method, performed by at least one processor of an information processing system, of analyzing a pathological image. The method includes receiving a pathological image, detecting an object associated with medical information, in the received pathological image by using a machine learning model, generating an analysis result on the received pathological image, based on a result of the detecting, and outputting medical information about at least one region included in the pathological image, based on the analysis result.
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