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11.发明申请公开(公告)号：US20210224268A1
公开(公告)日：2021-07-22
申请号：US17053332
申请日：2019-05-08
Applicant: DEEP BIO, INC.
Inventor： Sun Woo KIM
IPC: G06F16/2458
Abstract: A method for searching for an endpoint of a specific data cluster and a data processing system therefor, including the steps of: a) receiving, by a search system, an input of a numerical value for each of a plurality of individual data included in a data set; b) dividing a numerical range, to which the numerical value may belong, into a plurality of bins each bin having a predetermined bin width, by using the respective numerical values received by the search system, and generating histogram data having, as a bin value, the number of individual data corresponding to each of the divided bins; and c) searching for a target bin present at an endpoint of a specific cluster on the basis of the histogram data generated by the search system.
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公开(公告)号：US12148151B2
公开(公告)日：2024-11-19
申请号：US17271214
申请日：2019-08-07
Applicant: DEEP BIO INC.
Inventor： Joon Young Cho , Sun Woo Kim
Abstract: A system for diagnosing a disease, implemented in a system and which uses a slide of a biological image, and a neural network, includes a patch level segmentation neural network which, for each patch in which the slide is divided into a predetermined size, receives the patch through an input layer and specifies an area in which a disease exists in the patch, wherein the patch level segmentation neural network is provided with a disease diagnosis system including a patch level classification neural network which receives the patch through an input layer and outputs a patch level classification result regarding whether the disease exists in the patch, and a patch level segmentation architecture which receives a feature map generated in each of plural feature extraction layers among hidden layers included in the patch level classification neural network and specifies an area in which a disease exists in the patch.
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公开(公告)号：US12045977B2
公开(公告)日：2024-07-23
申请号：US17266103
申请日：2019-08-07
Applicant: DEEP BIO INC.
Inventor： Sang Hun Lee , Sun Woo Kim
CPC classification number: G06T7/0012 , G06N3/10 , G06T7/90 , G16H30/20 , G16H30/40 , G16H50/20 , G16H50/70 , G06T2207/10024 , G06T2207/20021 , G06T2207/20081 , G06T2207/20084 , G06T2207/30024
Abstract: A disease diagnosis system implemented in a system including a processor and which uses the neural network and a slide on which biological tissue is provided and from which a biological image is obtained, the system including: a pre-processing module for generating first to Kth image information corresponding to each of a plurality of patches obtained by dividing the slide into a predetermined size, wherein ith image information, 1
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公开(公告)号：US20240144476A1
公开(公告)日：2024-05-02
申请号：US18282213
申请日：2022-03-14
Applicant: DEEP BIO INC.
Inventor： In Young PARK , Tae Yeong KWAK , Sun Woo KIM
CPC classification number: G06T7/0012 , G16H30/40 , G06T2207/20084 , G06T2207/30096
Abstract: A bladder lesion diagnosis method using a learned neural network, and a system thereof. The bladder lesion diagnosis method using a neural network includes the steps of: receiving a unit pathological image by a bladder lesion diagnosis system; inputting, by the bladder lesion diagnosis system, the unit pathological image into a first neural network to obtain the diagnosis result of a first bladder lesion among a plurality of bladder lesions in the unit pathological image; and inputting, by the bladder lesion diagnosis system, the unit pathological image into a second neural network to obtain the diagnosis result of a second bladder lesion, other than the first bladder lesion, among the plurality of bladder lesions in the unit pathological image.
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公开(公告)号：US20240087133A1
公开(公告)日：2024-03-14
申请号：US18273033
申请日：2022-01-19
Applicant: DEEP BIO INC.
Inventor： Joon Young CHO , Tae Yeong TWAK , Sun Woo KIM
CPC classification number: G06T7/12 , G06T7/11 , G06T7/13 , G06T7/136 , G06T7/194 , G06T7/73 , G06T7/90 , G06T2207/10056 , G06T2207/30024
Abstract: Disclosed are a method for refining a tissue image by removing, from a slide image of a tissue specimen, a tissue specimen region determined to be another tissue specimen, and a computer system performing same. According to one aspect of the present invention, provided is a method for refining a tissue specimen image, comprising the steps of: extracting a plurality of contours corresponding to a plurality of tissue regions included in a tissue specimen image; calculating the center point coordinates of each of the extracted plurality of contours; determining a main tissue contour from among the plurality of contours, on the basis of the center point coordinates of the tissue specimen image and the center point coordinates of each of the plurality of contours; and removing a region corresponding to at least a part of the contours other than the main tissue contour among the plurality of contours.
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Patent Agency Ranking
公开(公告)号：US20240055104A1
公开(公告)日：2024-02-15
申请号：US18271231
申请日：2021-03-29
Applicant: DEEP BIO INC.
Inventor： Min Ah CHO , Joon Young CHO , Tae Yeong KWAK , Sun Woo KIM
Abstract: A method for analyzing an output of a neural network that analyzes an output result of a neural network trained so as to output a disease expression probability for each biological image pixel includes, depending on whether an output result value of the neural network for each pixel is equal to or greater than a reference value, an output analysis system determines the optimal output result value which is a reference value for detecting whether a disease is expressed in the corresponding pixel; determining an optimal cut-off value for determining whether a detected lesion site is effective with respect to a detected lesion in a biological image; and, when the output analysis system receives an output result corresponding to a diagnostic biometric image to be diagnosed, performing an output analysis on the output result by using the optimal reference value and the optimal cut-off value.
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公开(公告)号：US20220301712A1
公开(公告)日：2022-09-22
申请号：US17626806
申请日：2020-07-10
Applicant: DEEP BIO INC.
Inventor： Sun Woo KIM , Joon Young CHO , Sang Hun LEE
Abstract: A disease diagnosis system uses a slide of a biological image and the neural network, the disease diagnosis system including a patch-level segmentation neural network that receives, for each predetermined patch in which the slide is divided into a predetermined size, the patch as an input layer so as to specify the area in which the disease in the patch exists, wherein the patch-level segmentation neural network comprises: a patch-level classification neural network, which receives the patch as an input layer so as to output a patch-level classification result about whether the disease exists in the patch; and a patch-level segmentation architecture, which receives a feature map generated in each of two or more feature map extraction layers from among hidden layers included in the patch-level classification neural network, so as to specify the area in which the disease in the patch exists.
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公开(公告)号：US20210327059A1
公开(公告)日：2021-10-21
申请号：US17266098
申请日：2019-08-07
Applicant: DEEP BIO INC.
Inventor： Sang Hun LEE , Sun Woo KIM
Abstract: A system and a method that output in both a machine-readable and a human-readable format, a result obtained by performing a diagnosis of a disease through an image of living tissue. A diagnosis result generation system includes a marking information generation module for generating marking information indicating a result obtained by diagnosing whether a disease is present in biological tissue provided on a slide of which a biological image is obtained therefrom, wherein the marking information includes disease state information for each pixel of the biometric image obtained from the slide; a contour extraction module for extracting at least one contour from the marking information; and a machine-readable/human-readable generation module for generating a machine-readable/human-readable document including outline information of each of the at least one extracted contour.
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公开(公告)号：US12169926B2
公开(公告)日：2024-12-17
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：US20240331364A1
公开(公告)日：2024-10-03
申请号：US18741765
申请日：2024-06-12
Applicant: DEEP BIO INC.
Inventor： Tae Yeong KWAK , Hye Yoon CHANG , Joon Young CHO , Sun Woo KIM
IPC: G06V10/774 , G06N3/084 , G06T7/00 , G06V10/82
CPC classification number: G06V10/774 , G06N3/084 , G06T7/0012 , G06V10/82 , G06T2207/10024 , G06T2207/10056 , G06T2207/20081 , G06T2207/20084 , G06T2207/30024 , G06T2207/30096 , G06V2201/03
Abstract: A method for extracting only a portion stained with a specific dye from a pathology slide stained with a mixed dye in which various types of dyes are mixed, training an artificial neural network, and determining a pathology image stained by using various staining techniques; and a computing system performing same. A neural network learning system generates and learns a learning data set including M pieces of individual learning data (where M is a natural number greater than or equal to 2).
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