公开(公告)号：US20210295509A1

公开(公告)日：2021-09-23

申请号：US17266103

申请日：2019-08-07

Applicant: DEEP BIO INC.

Inventor： Sang Hun LEE ,  Sun Woo KIM

IPC: G06T7/00 ,  G06N3/10 ,  G16H50/20 ,  G16H30/20 ,  G16H30/40 ,  G16H50/70 ,  G06T7/90

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

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.

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

IPC: G06T7/00 ,  G06T7/11 ,  G16H30/40 ,  G16H50/30 ,  G16H70/60

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.

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

IPC: G06T7/00 ,  G16H50/20

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.

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.

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

IPC: G16H50/20 ,  G16H40/20 ,  G16H50/30 ,  G06N3/08 ,  A61B5/00

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.

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

IPC: G06T7/00 ,  G06N3/04 ,  G16H50/20 ,  G06F17/15 ,  G06F17/18

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.