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公开(公告)号：US12051504B2
公开(公告)日：2024-07-30
申请号：US15734907
申请日：2019-06-04
Applicant: DEEP BIO INC.
Inventor： Sanghun Lee , Joonyoung Cho , Sun Woo Kim
Abstract: A two-phase disease diagnosis system includes a processor and a storage device storing a neural network, and using a slide including a biometric image and the neural network. The system includes a patch neural network that receives, through an input layer, a given patch segmented in a given size from the slide and outputs patch level diagnosis results indicating whether a disease is present in the patch and a slide diagnosis engine that marks a patch determined to be cancer based on the patch level diagnosis results for each of multiple patches included in the slide and outputs slide level diagnosis results indicating whether a disease is present in the slide based on the marked results. The patch neural network receives, through the input layer, four-channel information including original color information three-channels and a gray channel for the patch.
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公开(公告)号：US20210304405A1
公开(公告)日：2021-09-30
申请号：US17266090
申请日：2019-08-07
Applicant: DEEP BIO INC.
Inventor： Joon Young CHO , Sun Woo KIM
Abstract: A system for disease diagnosis includes a patch neural network for generating a patch-level diagnostic result of whether or not a disease is present in each of predetermined patches formed by dividing a slide into a predetermined size; a heat map generation module for generating a patch-level heat map image corresponding to the biometric image obtained from the slide on the basis of the patch diagnostic results of the respective multiple patches included in the slide; a tissue mask generation module for generating a tissue mask image corresponding to the biometric image obtained from the slide on the basis of a hue-saturation-value (HSV) model corresponding to the slide; and a visualization module for generating a disease diagnostic visualization image corresponding to the biometric image obtained from the slide on the basis of the patch-level heat map image and the tissue mask image.
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公开(公告)号：US20250095149A1
公开(公告)日：2025-03-20
申请号：US18964686
申请日：2024-12-02
Applicant: DEEP BIO INC.
Inventor： Tae Yeong KWAK , Jae Heon LEE , Hye Yoon CHANG , Sun Woo KIM
Abstract: A patch level severity determination method, a slide level severity determination method, and a computing system for performing same are disclosed. According to one aspect of the present invention, provided is a method performed in a computing system including a deep-learning model pre-trained to provide determination results for partial images when each partial image obtained by dividing a pathology slide image is inputted, the method comprising the steps of: for each of a plurality of partial images obtained by dividing a pathology slide image, determining an effective grade for the partial image on the basis of a determination result for the partial image outputted by the deep-learning model that has received the partial image; and determining a slide level severity rating for the entire pathology slide image on the basis of the effective grade for each of the plurality of partial images that constitute the pathology slide image.
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公开(公告)号：US12009099B2
公开(公告)日：2024-06-11
申请号：US16972231
申请日：2019-06-04
Applicant: DEEP BIO INC.
Inventor： Sanghun Lee , JoonYoung Cho , Sun Woo Kim
IPC: G16H50/20
CPC classification number: G16H50/20
Abstract: A disease diagnosis system includes a processor and a storage device storing a neural network. The processor trains the neural network in the storage device to output a determination value corresponding to a probability having at least one of a plurality of states using a given loss function and learning data labeled so that a given unitary unit included in a biometric image is to have at least one of the plurality of states. The neural network includes a specific layer to output a plurality of feature values corresponding to a probability that the unitary unit is to be determined as each of the plurality of states. The loss function incorporates both first and second feature values corresponding to first and second states into a dual labeling unitary unit with the first state having a higher probability and a second state having lower probability.
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Patent Agency Ranking
公开(公告)号：US20230289957A1
公开(公告)日：2023-09-14
申请号：US18017392
申请日：2020-07-23
Applicant: DEEP BIO INC.
Inventor： Joon Young CHO , Sun Woo KIM
CPC classification number: G06T7/0012 , G16H50/20 , G06T2207/20081 , G06T2207/20084
Abstract: Disclosed is a disease diagnosis method using a neural network trained by using a multi-phase biometric image. The method includes generating, by a diagnosis system using a neural network, a diagnosis neural network for predicting a diagnosis result regarding a predetermined disease by using a biometric image. The method further includes obtaining, by the diagnosis system, a plurality of training biometric images. The method further includes training, by the diagnosis system, the diagnosis neural network by using the plurality of training biometric images.
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36.发明公开公开(公告)号：US20230244930A1
公开(公告)日：2023-08-03
申请号：US18008407
申请日：2021-06-03
Applicant: DEEP BIO INC.
Inventor： Sun Woo KIM , Tae Yeong KWAK , Ye Chan MUN
IPC: G06N3/08
CPC classification number: G06N3/08
Abstract: The present disclosure relates to a neural network training method and a computing system for performing the same, and more specifically, the neural network training method, which may enhance performance of a neural network even with little training data and the computing system for performing the same by using an auto-encoder and a multiple instance training method and extracting many data instances from one data bag as instances for training.
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公开(公告)号：US20220277812A1
公开(公告)日：2022-09-01
申请号：US17626795
申请日：2020-07-10
Applicant: DEEP BIO INC. , GENCURIX INC.
Inventor： Jee Eun KIM , Byeongil KANG , Chang Dae LEE , Min Ah CHO
Abstract: A method for automatically calculating a threshold for classifying clusters from a reference data set and processing data by using same, and a system for performing same is included herein. A data processing method using auto-thresholding includes the steps of receiving, by a data processing system, as an input, a plurality of individual numerical values included in a reference data set having two or more clusters; on the basis of each of the numerical values included in the reference data set received as an input, calculating, by the data processing system, a threshold for classifying a cluster of the reference data set; and classifying, by the data processing system, into different clusters by using the threshold, each of at least one data set to be analyzed, having a plurality of individual numerical values.
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38.发明申请公开(公告)号：US20210398674A1
公开(公告)日：2021-12-23
申请号：US17297463
申请日：2019-11-27
Applicant: DEEP BIO INC.
Inventor： Sun Woo KIM
Abstract: A method for providing a diagnostic system using semi-supervised learning, and a system therefor. The method for providing a diagnostic system using semi-supervised learning includes: a step in which a diagnostic system trained through a neural network on the basis of supervised learning receives predetermined input data and outputs a diagnostic result for the input data; a step in which the diagnostic system generates automatic annotation training data including the input data annotated as the diagnostic result; and a step in which the diagnostic system performs a retraining process by using the generated automatic annotation training data.
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公开(公告)号：US20190385306A1
公开(公告)日：2019-12-19
申请号：US16468173
申请日：2017-12-06
Applicant: DEEP BIO, INC.
Inventor： Sun Woo KIM
Abstract: A disease diagnosis system including a processor and a storage device for storing a neural network and using a biometric image and the neural network, the disease diagnosis system including a micro-neural network for receiving a first tile included in the biometric image through a first input layer, and including a plurality of first layers and an output layer, and a macro-neural network for receiving a macro-tile including the first tile and at least one or more second tiles adjacent to the first tile through a second input layer, and including a plurality of second layers and the output layer, in which the output layer includes at least one state channel indicating a state of a disease of a biological tissue corresponding to the first tile.
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