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111.
公开(公告)号:US20240136068A1
公开(公告)日:2024-04-25
申请号:US18273316
申请日:2022-03-29
Applicant: Lunit Inc.
Inventor: Hyeonsoo LEE , Kihwan KIM , Hyeonseob NAM
Abstract: A prediction device operated by at least one processor includes: a risk factor inference model implemented with an artificial intelligence model trained to infer risk factors for a disease from input images, configured to receive medical images and output at least one inferred risk factor; and a medical prediction model configured to receive patient information including the at least one inferred risk factor as input and output a medical prediction including a disease risk.
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公开(公告)号:US11935236B2
公开(公告)日:2024-03-19
申请号:US18093162
申请日:2023-01-04
Applicant: LUNIT INC.
Inventor: Jung Hee Jang , Do Hyun Lee , Woo Suk Lee , Rae Yeong Lee
CPC classification number: G06T7/0012 , G06T3/40 , G06T15/00 , G06T2207/10072 , G06T2207/30096 , G06T2210/41
Abstract: Provided are a method and an apparatus for interlocking a lesion location between a 2D medical image and 3D tomosynthesis images including a plurality of 3D image slices.
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公开(公告)号:US11875893B2
公开(公告)日:2024-01-16
申请号:US18102465
申请日:2023-01-27
Applicant: LUNIT INC.
Inventor: Jeong Seok Kang , Jae Hong Aum , Dong Geun Yoo , Tai Won Chung
Abstract: A computing apparatus includes: at least one memory; and at least one processor, wherein the processor generates quantitative information regarding at least one cell included in a region of interest of a pathological slide image by analyzing the pathological slide image, generates qualitative information regarding at least one tissue included in the pathological slide image by analyzing the pathological slide image, and controls a display apparatus to output at least one of the quantitative information and the qualitative information on the pathological slide image according to a manipulation of a user.
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公开(公告)号:US20230420072A1
公开(公告)日:2023-12-28
申请号:US18463962
申请日:2023-09-08
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 predicting a response to an immune checkpoint inhibitor. The method includes receiving a first pathology slide image, detecting one or more target items in the first pathology slide image, determining at least one of an immune phenotype of at least some regions in the first pathology slide image or information associated with the immune phenotype based on the detection result for the one or more target items, and generating a prediction result as to whether or not a patient associated with the first pathology slide image responds to the immune checkpoint inhibitor, based on the immune phenotype of the at least some regions in the first pathology slide image or the information associated with the immune phenotype.
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115.
公开(公告)号:US20230419492A1
公开(公告)日:2023-12-28
申请号:US18463912
申请日:2023-09-08
Applicant: LUNIT INC.
Inventor: Donggeun YOO , Chanyoung OCK , Kyunghyun PAENG
CPC classification number: G06T7/0012 , G16B20/00 , G06N3/02
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:US11854194B2
公开(公告)日:2023-12-26
申请号:US17375876
申请日:2021-07-14
Applicant: Lunit Inc.
Inventor: Minje Jang
IPC: G06F18/214 , G06V10/82 , G06T7/00 , G06V10/426 , G06V20/69 , G06F18/25 , G06V10/764 , G06V10/774 , G06V10/80
CPC classification number: G06T7/0012 , G06F18/214 , G06F18/25 , G06V10/426 , G06V10/764 , G06V10/774 , G06V10/80 , G06V10/82 , G06V20/69 , G06T2207/20072 , G06T2207/20081 , G06T2207/20084 , G06T2207/30024 , G06V2201/03
Abstract: An image analysis method and an image analysis system are disclosed. The method may include extracting training raw graphic data including at least one first node corresponding to a plurality of histological features of a training tissue slide image, and at least one first edge defined by a relationship between the histological features and generating training graphic data by sampling the first node of the training raw graphic data. The method may also include determining a parameter of a readout function by training a graph neural network (GNN) using the training graphic data and training output data corresponding to the training graphic data, and extracting inference graphic data including at least one second node corresponding to a plurality of histological features of an inference tissue slide image, and at least one second edge decided by a relationship between the histological features of the inference tissue slide image.
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公开(公告)号:US20230410958A1
公开(公告)日:2023-12-21
申请号:US18334836
申请日:2023-06-14
Applicant: Lunit Inc.
Inventor: Kyung Hyun PAENG , Seung Yun Oh , Ji Min Moon , Se Jin Kim
Abstract: A computing apparatus includes at least one memory storing at least one program, and at least one processor configured to, by executing the at least one program, acquire at least one of first information regarding a primary clinical trial previously performed on a certain drug and second information indicating an association between the drug and each of candidate biomarkers, set a criterion related to responsitivity to the drug based on the acquired information, and generate information related to a secondary clinical trial based on the set criterion.
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公开(公告)号:US20230386028A1
公开(公告)日:2023-11-30
申请号:US18321132
申请日:2023-05-22
Applicant: Lunit Inc.
Inventor: Ga Hee PARK , Kyung Hyun PAENG , Chan Young OCK , Sang Hoon SONG , Suk Jun KIM
CPC classification number: G06T7/0012 , G06V20/698 , G16H30/40 , G16H15/00 , G06T2207/30096 , G06T2207/30204 , G06T2207/30168 , G06V2201/03 , G06T2207/30024
Abstract: A computing device includes at least one memory, and at least one processor configured to analyze at least one object expressed in a pathological slide image, evaluate quality of the pathological slide image based on a result of the analyzing, and perform at least one additional operation according to a result of the evaluating.
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公开(公告)号:US11710552B2
公开(公告)日:2023-07-25
申请号:US16953693
申请日:2020-11-20
Applicant: LUNIT INC.
Inventor: Chunseong Park
CPC classification number: G16H30/40 , G06N3/08 , G06T7/0012 , G06T7/11 , G06T2207/10056 , G06T2207/20081 , G06T2207/20084 , G06T2207/30024
Abstract: A method for refining label information, which is performed by at least one computing device is disclosed. The method includes acquiring a pathology slide image including a plurality of patches, inferring a plurality of label information items for the plurality of patches included in the acquired pathology slide image using a machine learning model, applying the inferred plurality of label information items to the pathology slide image, and providing the pathology slide image applied with the inferred plurality of label information items to an annotator terminal.
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公开(公告)号:US20230206433A1
公开(公告)日:2023-06-29
申请号:US18056773
申请日:2022-11-18
Applicant: LUNIT INC.
Inventor: Ga Hee PARK , Chan Young OCK , Kyung Hyun PAENG
CPC classification number: G06T7/0012 , G06V20/698 , G06V2201/03 , G06T2207/30024 , G06T2207/30096 , G06T2207/30242 , G06T2207/10056
Abstract: Provided is a computing apparatus including: at least one memory; and at least one processor, wherein the at least one processor is configured to: perform a first classification on a plurality of tissues expressed in a pathological slide image by analyzing the pathological slide image, perform a second classification on a plurality of cells expressed in a pathological slide image by analyzing the pathological slide image, and calculate tumor purity including information on noise included in the pathological slide image by combining a first classification result and a second classification result.
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