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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：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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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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Patent Agency Ranking
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：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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8.发明公开公开(公告)号：US20240156416A1
公开(公告)日：2024-05-16
申请号：US18282202
申请日：2022-03-14
Applicant: DEEP BIO INC.
Inventor： Sun Woo KIM
CPC classification number: A61B5/7275 , A61B5/1079 , G06T7/0012 , G06T7/11 , G06T7/60 , G16H50/20 , G06T2207/20084 , G06T2207/30024 , G06T2207/30081
Abstract: A prognosis prediction method using a result of disease diagnosis through a neural network and a system therefor. The prognosis prediction method includes: receiving a biometric image as an input; generating an expression region diagnosis result in which an expression region in the biometric image, in which a disease has been expressed, is determined with respect to the input biometric image; and determining first information corresponding to the size of the entire tissue in the biometric image and second information corresponding to the size of the expression region in the biometric image, on the basis of the diagnosis result, and generating prognosis prediction information based on a result of the determination.
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9.发明公开公开(公告)号：US20240037855A1
公开(公告)日：2024-02-01
申请号：US18276039
申请日：2022-02-08
Applicant: DEEP BIO INC.
Inventor： Sun Woo KIM
CPC classification number: G06T19/00 , G16H30/40 , G16H50/20 , G06T2210/44 , G06T2219/004 , A61B10/0241
Abstract: A method for generating a three-dimensional prostate pathological image, and a system therefor are disclosed. The method for generating a three-dimensional prostate pathological image includes the steps of: by a system for generating a three-dimensional prostate pathological image, specifying a three-dimensional prostate image; by the system for generating a three-dimensional prostate pathological image, obtaining, through a diagnosis system, a digital diagnosis result for each of at least one specimen corresponding to predetermined template coordinates obtained through a transperineal template prostate biopsy (TTPB); and by the system for generating a three-dimensional prostate pathological image, displaying, on the three-dimensional prostate image, an onset site of prostate cancer existing in the at least one specimen on the basis of the template coordinates for each specimen and the digital diagnosis result.
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10.发明公开公开(公告)号：US20230306624A1
公开(公告)日：2023-09-28
申请号：US18010701
申请日：2021-06-16
Applicant: DEEP BIO INC.
Inventor： Ui Geo MUN , Min Ah CHO , Tae Yeong KWAK , Sun Woo KIM
CPC classification number: G06T7/60 , G06T7/0012 , G06T7/11 , G06V10/28 , G06V10/426 , G16H30/40 , G06T2207/20072 , G06T2207/30024 , G06T2207/30096
Abstract: Disclosed are a method for measuring the length of a living tissue included in a slide image, and a computing system for performing same. According to one aspect of the present invention, the method comprising the steps of: segmenting the slide image into a plurality of patches having a predetermined size; generating a graph corresponding to the slide image; for each edge included in the graph, setting a weight of the edge; for each connected component of the graph including two or more nodes, detecting shortest paths between all node pairs included in the connected components and determining a longest shortest path having the longest length from among the detected shortest paths between all the node pairs; and calculating the length of the living tissue included in the slide image, on the basis of the longest shortest path of each connected component constituting the graph.
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