WO2021010671A3 - 뉴럴 네트워크 및 비국소적 블록을 이용하여 세그멘테이션을 수행하는 질병 진단 시스템 및 방법 - Google Patents
뉴럴 네트워크 및 비국소적 블록을 이용하여 세그멘테이션을 수행하는 질병 진단 시스템 및 방법 Download PDFInfo
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- WO2021010671A3 WO2021010671A3 PCT/KR2020/009096 KR2020009096W WO2021010671A3 WO 2021010671 A3 WO2021010671 A3 WO 2021010671A3 KR 2020009096 W KR2020009096 W KR 2020009096W WO 2021010671 A3 WO2021010671 A3 WO 2021010671A3
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- 238000013528 artificial neural network Methods 0.000 title abstract 9
- 201000010099 disease Diseases 0.000 title abstract 7
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 title abstract 7
- 230000011218 segmentation Effects 0.000 title abstract 5
- 238000003745 diagnosis Methods 0.000 title abstract 4
- 238000000034 method Methods 0.000 title abstract 2
- 238000000605 extraction Methods 0.000 abstract 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
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- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/0033—Features or image-related aspects of imaging apparatus classified in A61B5/00, e.g. for MRI, optical tomography or impedance tomography apparatus; arrangements of imaging apparatus in a room
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- G06F18/00—Pattern recognition
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H30/00—ICT specially adapted for the handling or processing of medical images
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H30/00—ICT specially adapted for the handling or processing of medical images
- G16H30/40—ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
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- G—PHYSICS
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- G06T2207/30004—Biomedical image processing
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Abstract
뉴럴 네트워크를 통한 학습을 수행하여 학습된 뉴럴 네트워크 및 비국소적 블록을 이용하여 생체조직의 이미지에서 질병이 있는 영역을 세그멘테이션할 수 있는 질병 진단 시스템 및 그 방법이 개시된다. 본 발명의 일 측면에 따르면, 프로세서 및 뉴럴 네트워크를 저장하는 저장장치를 포함하는 시스템에 구현되며 생체이미지인 슬라이드와 상기 뉴럴 네트워크를 이용한 질병의 진단 시스템에 있어서, 상기 시스템은, 상기 슬라이드가 소정의 크기로 분할된 소정의 패치 각각에 대하여, 상기 패치를 입력 레이어로 입력 받아서 상기 패치 중 질병이 존재하는 영역을 특정하는 패치레벨 세그멘테이션 뉴럴 네트워크를 포함하되, 상기 패치레벨 세그멘테이션 뉴럴 네트워크는, 상기 패치를 입력 레이어로 입력 받아서 상기 패치에 상기 질병이 존재하는지 여부에 관한 패치레벨 분류 결과를 출력하는 패치레벨 클래시피케이션 뉴럴 네트워크 및 상기 패치레벨 클래시피케이션 뉴럴 네트워크에 포함된 히든 레이어 중 2 이상의 피쳐 맵 추출 레이어 각각에서 생성되는 피쳐 맵을 입력 받아서 상기 패치 중 질병이 존재하는 영역을 특정하는 패치레벨 세그멘테이션 아키텍쳐를 포함하는 질병 진단 시스템이 제공된다.
Priority Applications (4)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US17/626,806 US20220301712A1 (en) | 2019-07-13 | 2020-07-10 | Disease diagnosis system and method for performing segmentation by using neural network and unlocalized block |
EP20841047.2A EP3989237A4 (en) | 2019-07-13 | 2020-07-10 | DISEASE DIAGNOSIS SYSTEM AND METHOD FOR SEGMENTATION USING A NEURAL NETWORK AND UNLOCALIZED BLOCKS |
CN202080051105.3A CN114503153A (zh) | 2019-07-13 | 2020-07-10 | 利用神经网络及非局部块进行分割的疾病诊断系统及方法 |
JP2022500883A JP7299658B2 (ja) | 2019-07-13 | 2020-07-10 | ニューラルネットワーク及び非局所的ブロックを用いてセグメンテーションを行う疾病診断システム及び方法 |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
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KR10-2019-0084814 | 2019-07-13 | ||
KR1020190084814A KR102329546B1 (ko) | 2019-07-13 | 2019-07-13 | 뉴럴 네트워크 및 비국소적 블록을 이용하여 세그멘테이션을 수행하는 질병 진단 시스템 및 방법 |
Publications (3)
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WO2021010671A2 WO2021010671A2 (ko) | 2021-01-21 |
WO2021010671A3 true WO2021010671A3 (ko) | 2021-04-08 |
WO2021010671A9 WO2021010671A9 (ko) | 2021-05-27 |
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PCT/KR2020/009096 WO2021010671A2 (ko) | 2019-07-13 | 2020-07-10 | 뉴럴 네트워크 및 비국소적 블록을 이용하여 세그멘테이션을 수행하는 질병 진단 시스템 및 방법 |
Country Status (6)
Country | Link |
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US (1) | US20220301712A1 (ko) |
EP (1) | EP3989237A4 (ko) |
JP (1) | JP7299658B2 (ko) |
KR (1) | KR102329546B1 (ko) |
CN (1) | CN114503153A (ko) |
WO (1) | WO2021010671A2 (ko) |
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KR102592762B1 (ko) * | 2021-01-27 | 2023-10-24 | 대구대학교 산학협력단 | 합성곱 신경망 기반의 덴스넷을 통한 부정맥 분류 방법 |
US11868443B1 (en) * | 2021-05-12 | 2024-01-09 | Amazon Technologies, Inc. | System for training neural network using ordered classes |
US11948358B2 (en) * | 2021-11-16 | 2024-04-02 | Adobe Inc. | Self-supervised hierarchical event representation learning |
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KR20160034814A (ko) * | 2014-09-22 | 2016-03-30 | 삼성전자주식회사 | 뉴럴 네트워크를 수반한 클라이언트 장치 및 그것을 포함하는 시스템 |
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- 2020-07-10 JP JP2022500883A patent/JP7299658B2/ja active Active
- 2020-07-10 CN CN202080051105.3A patent/CN114503153A/zh active Pending
- 2020-07-10 WO PCT/KR2020/009096 patent/WO2021010671A2/ko unknown
- 2020-07-10 EP EP20841047.2A patent/EP3989237A4/en active Pending
- 2020-07-10 US US17/626,806 patent/US20220301712A1/en active Pending
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KR20160034814A (ko) * | 2014-09-22 | 2016-03-30 | 삼성전자주식회사 | 뉴럴 네트워크를 수반한 클라이언트 장치 및 그것을 포함하는 시스템 |
KR20180066983A (ko) * | 2016-12-11 | 2018-06-20 | 주식회사 딥바이오 | 뉴럴 네트워크를 이용한 질병의 진단 시스템 및 그 방법 |
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Publication number | Publication date |
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EP3989237A4 (en) | 2023-07-26 |
JP2022540152A (ja) | 2022-09-14 |
JP7299658B2 (ja) | 2023-06-28 |
CN114503153A (zh) | 2022-05-13 |
US20220301712A1 (en) | 2022-09-22 |
WO2021010671A9 (ko) | 2021-05-27 |
EP3989237A2 (en) | 2022-04-27 |
KR20210008283A (ko) | 2021-01-21 |
WO2021010671A2 (ko) | 2021-01-21 |
KR102329546B1 (ko) | 2021-11-23 |
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