WO2020032559A3 - 뉴럴 네트워크를 이용한 질병의 진단 시스템 및 방법 - Google Patents
뉴럴 네트워크를 이용한 질병의 진단 시스템 및 방법 Download PDFInfo
- Publication number
- WO2020032559A3 WO2020032559A3 PCT/KR2019/009844 KR2019009844W WO2020032559A3 WO 2020032559 A3 WO2020032559 A3 WO 2020032559A3 KR 2019009844 W KR2019009844 W KR 2019009844W WO 2020032559 A3 WO2020032559 A3 WO 2020032559A3
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- slide
- neural network
- patch
- disease
- generating
- Prior art date
Links
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- 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
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- 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
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- 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
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/0059—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
- A61B5/0075—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence by spectroscopy, i.e. measuring spectra, e.g. Raman spectroscopy, infrared absorption spectroscopy
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/43—Detecting, measuring or recording for evaluating the reproductive systems
- A61B5/4375—Detecting, measuring or recording for evaluating the reproductive systems for evaluating the male reproductive system
- A61B5/4381—Prostate evaluation or disorder diagnosis
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4842—Monitoring progression or stage of a disease
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
- A61B5/7267—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems involving training the classification device
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20021—Dividing image into blocks, subimages or windows
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20076—Probabilistic image processing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20081—Training; Learning
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20084—Artificial neural networks [ANN]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
- G06T2207/30024—Cell structures in vitro; Tissue sections in vitro
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
- G06T2207/30081—Prostate
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
- G06T2207/30096—Tumor; Lesion
Landscapes
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Public Health (AREA)
- General Health & Medical Sciences (AREA)
- Biomedical Technology (AREA)
- Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Pathology (AREA)
- Primary Health Care (AREA)
- Epidemiology (AREA)
- Data Mining & Analysis (AREA)
- Artificial Intelligence (AREA)
- Databases & Information Systems (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Radiology & Medical Imaging (AREA)
- Theoretical Computer Science (AREA)
- Mathematical Physics (AREA)
- Evolutionary Computation (AREA)
- Molecular Biology (AREA)
- Biophysics (AREA)
- General Physics & Mathematics (AREA)
- Signal Processing (AREA)
- Surgery (AREA)
- Veterinary Medicine (AREA)
- Animal Behavior & Ethology (AREA)
- Heart & Thoracic Surgery (AREA)
- Fuzzy Systems (AREA)
- Physiology (AREA)
- Psychiatry (AREA)
- Quality & Reliability (AREA)
- Computing Systems (AREA)
- General Engineering & Computer Science (AREA)
- Computational Linguistics (AREA)
- Software Systems (AREA)
- Measuring And Recording Apparatus For Diagnosis (AREA)
- Image Analysis (AREA)
- Image Processing (AREA)
Abstract
뉴럴 네트워크를 통한 학습을 수행하여 학습된 뉴럴 네트워크를 이용하여 생체조직의 이미지를 입력할 경우 소정의 질병(예컨대, 전립선 암)을 진단할 수 있으며 질병으로 진단된 조직(티슈) 부위를 정확히 파악할 수 있도록 시각화하는 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 진단 시스템은, 상기 슬라이드가 소정의 크기로 분할된 소정의 패치 각각에 질병이 존재하는지 여부인 패치 레벨 진단결과를 생성하는 패치 뉴럴 네트워크, 상기 슬라이드에 포함된 다수의 패치들 각각의 패치 진단결과에 기초하여 상기 슬라이드에 상응하는 패치 레벨 히트맵 이미지를 생성하는 히트맵 생성모듈, 상기 슬라이드에 상응하는 HSV(Hue-Saturation-Value) 모델에 기초하여 상기 슬라이드에 상응하는 티슈 마스크 이미지를 생성하는 티슈 마스크 생성모듈 및 상기 패치 레벨 히트맵 이미지와 상기 티슈 마스크 이미지에 기초하여 상기 슬라이드에 상응하는 질병 진단 시각화 이미지를 생성하는 시각화 모듈을 포함하는 진단 시스템이 제공된다.
Priority Applications (5)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
ES19848575T ES2969065T3 (es) | 2018-08-07 | 2019-08-07 | Sistema y procedimiento para el diagnóstico de enfermedades mediante red neuronal |
US17/266,090 US20210304405A1 (en) | 2018-08-07 | 2019-08-07 | System and method for disease diagnosis using neural network |
CN201980052666.2A CN112740335A (zh) | 2018-08-07 | 2019-08-07 | 基于神经网络的疾病诊断系统和方法 |
EP19848575.7A EP3819912B1 (en) | 2018-08-07 | 2019-08-07 | System and method for disease diagnosis using neural network |
JP2021505740A JP2021533470A (ja) | 2018-08-07 | 2019-08-07 | ニューラルネットワークを用いた疾病の診断システム及び方法 |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
KR1020180092011A KR102185893B1 (ko) | 2018-08-07 | 2018-08-07 | 뉴럴 네트워크를 이용한 질병의 진단 시스템 및 방법 |
KR10-2018-0092011 | 2018-08-07 |
Publications (2)
Publication Number | Publication Date |
---|---|
WO2020032559A2 WO2020032559A2 (ko) | 2020-02-13 |
WO2020032559A3 true WO2020032559A3 (ko) | 2020-03-26 |
Family
ID=69413822
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/KR2019/009844 WO2020032559A2 (ko) | 2018-08-07 | 2019-08-07 | 뉴럴 네트워크를 이용한 질병의 진단 시스템 및 방법 |
Country Status (7)
Country | Link |
---|---|
US (1) | US20210304405A1 (ko) |
EP (1) | EP3819912B1 (ko) |
JP (1) | JP2021533470A (ko) |
KR (1) | KR102185893B1 (ko) |
CN (1) | CN112740335A (ko) |
ES (1) | ES2969065T3 (ko) |
WO (1) | WO2020032559A2 (ko) |
Families Citing this family (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN116324874A (zh) * | 2020-11-06 | 2023-06-23 | 威里利生命科学有限责任公司 | 对前列腺癌预后的人工智能预测 |
KR102246319B1 (ko) * | 2021-01-07 | 2021-05-03 | 주식회사 딥바이오 | 병리 검체에 대한 판단 결과를 제공하는 인공 뉴럴 네트워크의 학습 방법, 및 이를 수행하는 컴퓨팅 시스템 |
KR20220114351A (ko) * | 2021-02-08 | 2022-08-17 | 전남대학교산학협력단 | Ppg 기반 스펙트로그램 및 cnn에 기반하는 통증 평가 방법 및 장치 |
KR102517326B1 (ko) * | 2021-02-08 | 2023-04-05 | 전북대학교산학협력단 | 다중분광 영상에 기반을 둔 산림 병해충 탐지 장치 |
KR102430796B1 (ko) * | 2022-03-14 | 2022-08-09 | 주식회사 딥바이오 | 딥러닝 모델의 분산 훈련을 위한 전체 슬라이드 이미지 분배 방법 및 이를 수행하는 컴퓨팅 시스템 |
KR102642137B1 (ko) * | 2022-08-08 | 2024-03-06 | 한국과학기술원 | 딥 러닝 모델의 불확실성을 고려한 조직 이미지 분류 장치 및 조직 이미지 분류 방법 |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20140233826A1 (en) * | 2011-09-27 | 2014-08-21 | Board Of Regents Of The University Of Texas System | Systems and methods for automated screening and prognosis of cancer from whole-slide biopsy images |
KR101590483B1 (ko) * | 2013-11-25 | 2016-02-01 | 조선대학교산학협력단 | 형태학적 연산을 이용한 이미지 분할 처리방법 |
KR20160142791A (ko) * | 2015-06-03 | 2016-12-13 | 삼성전자주식회사 | 뉴럴 네트워크 실시 방법 및 장치 |
US20180114317A1 (en) * | 2016-10-21 | 2018-04-26 | Nantomics, Llc | Digital histopathology and microdissection |
KR20180066983A (ko) * | 2016-12-11 | 2018-06-20 | 주식회사 딥바이오 | 뉴럴 네트워크를 이용한 질병의 진단 시스템 및 그 방법 |
Family Cites Families (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP4777024B2 (ja) * | 2005-09-06 | 2011-09-21 | キヤノン株式会社 | 画像処理装置および画像処理装置の制御方法 |
US10417525B2 (en) | 2014-09-22 | 2019-09-17 | Samsung Electronics Co., Ltd. | Object recognition with reduced neural network weight precision |
US10839510B2 (en) * | 2015-08-19 | 2020-11-17 | Colorado Seminary, Which Owns And Operates The University Of Denver | Methods and systems for human tissue analysis using shearlet transforms |
US20170215728A1 (en) * | 2016-02-01 | 2017-08-03 | University Of Washington | Applanation tonometer |
US9589374B1 (en) * | 2016-08-01 | 2017-03-07 | 12 Sigma Technologies | Computer-aided diagnosis system for medical images using deep convolutional neural networks |
CN106372390B (zh) * | 2016-08-25 | 2019-04-02 | 汤一平 | 一种基于深度卷积神经网络的预防肺癌自助健康云服务系统 |
US11379688B2 (en) * | 2017-03-16 | 2022-07-05 | Packsize Llc | Systems and methods for keypoint detection with convolutional neural networks |
CN107492099B (zh) * | 2017-08-28 | 2021-08-20 | 京东方科技集团股份有限公司 | 医学图像分析方法、医学图像分析系统以及存储介质 |
CN107609503A (zh) * | 2017-09-05 | 2018-01-19 | 刘宇红 | 智能癌变细胞识别系统及方法、云平台、服务器、计算机 |
CN108230257A (zh) * | 2017-11-15 | 2018-06-29 | 北京市商汤科技开发有限公司 | 图像处理方法、装置、电子设备及存储介质 |
-
2018
- 2018-08-07 KR KR1020180092011A patent/KR102185893B1/ko active IP Right Grant
-
2019
- 2019-08-07 CN CN201980052666.2A patent/CN112740335A/zh active Pending
- 2019-08-07 WO PCT/KR2019/009844 patent/WO2020032559A2/ko unknown
- 2019-08-07 US US17/266,090 patent/US20210304405A1/en active Pending
- 2019-08-07 EP EP19848575.7A patent/EP3819912B1/en active Active
- 2019-08-07 ES ES19848575T patent/ES2969065T3/es active Active
- 2019-08-07 JP JP2021505740A patent/JP2021533470A/ja active Pending
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20140233826A1 (en) * | 2011-09-27 | 2014-08-21 | Board Of Regents Of The University Of Texas System | Systems and methods for automated screening and prognosis of cancer from whole-slide biopsy images |
KR101590483B1 (ko) * | 2013-11-25 | 2016-02-01 | 조선대학교산학협력단 | 형태학적 연산을 이용한 이미지 분할 처리방법 |
KR20160142791A (ko) * | 2015-06-03 | 2016-12-13 | 삼성전자주식회사 | 뉴럴 네트워크 실시 방법 및 장치 |
US20180114317A1 (en) * | 2016-10-21 | 2018-04-26 | Nantomics, Llc | Digital histopathology and microdissection |
KR20180066983A (ko) * | 2016-12-11 | 2018-06-20 | 주식회사 딥바이오 | 뉴럴 네트워크를 이용한 질병의 진단 시스템 및 그 방법 |
Also Published As
Publication number | Publication date |
---|---|
JP2021533470A (ja) | 2021-12-02 |
KR102185893B1 (ko) | 2020-12-02 |
US20210304405A1 (en) | 2021-09-30 |
EP3819912C0 (en) | 2023-10-18 |
KR20200016658A (ko) | 2020-02-17 |
EP3819912A4 (en) | 2022-05-04 |
EP3819912B1 (en) | 2023-10-18 |
WO2020032559A2 (ko) | 2020-02-13 |
CN112740335A (zh) | 2021-04-30 |
ES2969065T3 (es) | 2024-05-16 |
EP3819912A2 (en) | 2021-05-12 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
WO2020032559A3 (ko) | 뉴럴 네트워크를 이용한 질병의 진단 시스템 및 방법 | |
US11526983B2 (en) | Image feature recognition method and apparatus, storage medium, and electronic apparatus | |
US10430946B1 (en) | Medical image segmentation and severity grading using neural network architectures with semi-supervised learning techniques | |
CN110570421B (zh) | 多任务的眼底图像分类方法和设备 | |
WO2018155898A1 (en) | Method and apparatus for processing histological image captured by medical imaging device | |
CN106651750A (zh) | 用于基于卷积神经网络回归的2d/3d图像配准的方法和系统 | |
US8605973B2 (en) | Graph cuts-based interactive segmentation of teeth in 3-D CT volumetric data | |
US20190090834A1 (en) | Determining a two-dimensional mammography dataset | |
CN110210483A (zh) | 医疗图像病变区域分割方法、模型训练方法和设备 | |
CN109215104B (zh) | 一种用于经颅刺激治疗的脑结构图像显示方法及装置 | |
CN103610444B (zh) | 用于舌诊仪的多点立体舌像采集装置 | |
Zhu et al. | Weakly-supervised balanced attention network for gastric pathology image localization and classification | |
CN105521562B (zh) | 一种肿瘤热疗的温度场预示与控制装置及方法 | |
WO2021010671A3 (ko) | 뉴럴 네트워크 및 비국소적 블록을 이용하여 세그멘테이션을 수행하는 질병 진단 시스템 및 방법 | |
Pepe et al. | Pattern recognition and mixed reality for computer-aided maxillofacial surgery and oncological assessment | |
WO2020032561A3 (ko) | 다중 색 모델 및 뉴럴 네트워크를 이용한 질병 진단 시스템 및 방법 | |
Ly et al. | New compact deep learning model for skin cancer recognition | |
CN107330948B (zh) | 一种基于流行学习算法的fMRI数据二维可视化方法 | |
Deshpande et al. | Knowledge-driven decision support for assessing dose distributions in radiation therapy of head and neck cancer | |
WO2020032560A3 (ko) | 진단 결과 생성 시스템 및 방법 | |
Wang et al. | Intelligent diagnosis of multiple peripheral retinal lesions in ultra-widefield fundus images based on deep learning | |
Huang et al. | Transde: A transformer and double encoder network for medical image segmentation | |
valli Gogula et al. | A diabetic retinopathy detection method using an improved pillar K-means algorithm | |
Sarica et al. | Advanced feature selection in multinominal dementia classification from structural MRI data | |
CN104188691A (zh) | 超声图像的辅助导航定位方法及系统 |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 19848575 Country of ref document: EP Kind code of ref document: A2 |
|
ENP | Entry into the national phase |
Ref document number: 2021505740 Country of ref document: JP Kind code of ref document: A |
|
NENP | Non-entry into the national phase |
Ref country code: DE |
|
ENP | Entry into the national phase |
Ref document number: 2019848575 Country of ref document: EP Effective date: 20210205 |