公开(公告)号：US20230298753A1

公开(公告)日：2023-09-21

申请号：US18017397

申请日：2020-07-23

Applicant: DEEP BIO INC.

Inventor： Sang Hun LEE ,  Sun Woo KIM

IPC: G16H50/20 ,  G16H50/70 ,  G16H30/40 ,  G06T7/00

CPC classification number: G16H50/20 ,  G16H50/70 ,  G16H30/40 ,  G06T7/0014 ,  G06T2207/30024 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30081

Abstract: Disclosed in the present invention are a method for annotating a pathogenic site of a disease by means of semi-supervised learning. According to an aspect of the present invention, provided is the method comprising the steps in which: the diagnosis system using a neural network generates a patch-level classification neural network, which predicts a classification result relating to whether or not a predetermined disease is present in a patch, and a pixel-level classification neural network which predicts a classification result relating to the disease for each pixel constituting the patch; the diagnosis system obtains a plurality of slide images for learning, wherein each of the plurality of slide images for learning is labeled with a corresponding slide-level diagnosis result; and the diagnosis system gradually learns the patch-level classification neural network and pixel-level classification neural network by means of the plurality of slide images for learning.

公开(公告)号：US20210391076A1

公开(公告)日：2021-12-16

申请号：US17282775

申请日：2019-10-04

Applicant: DEEP BIO INC.

Inventor： Tae Yeong KWAK ,  Sang Hun LEE ,  Sun Woo KIM

IPC: G16H50/20 ,  G06T7/00 ,  G16H30/40 ,  G06N3/08 ,  G06N3/04

Abstract: A system for searching for a pathological image includes: an autoencoder having an encoder for receiving an original pathological image and extracting a feature of the original pathological image, and a decoder for receiving the feature of the original pathological image extracted by the encoder and generating a reconstructed pathological image corresponding to the original pathological image; a diagnostic neural network for receiving the reconstructed pathological image generated by the autoencoder that has received the original pathological image, and outputting a diagnosis result of a predetermined disease; and a training module for training the autoencoder and the diagnostic neural network by inputting a plurality of training pathological images, each labeled with a diagnosis result, into the autoencoder. The autoencoder is trained by reflecting the diagnosis result of the reconstructed pathological image output from the diagnostic neural network.

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：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

IPC: G16H50/20 ,  G16H30/20 ,  G16H30/40

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.

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

IPC: G06T7/00 ,  G06T7/90 ,  G06T7/136 ,  G06T7/13 ,  G06F40/143 ,  G16H15/00 ,  G06N3/08

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.