WO2021153858A1 - Dispositif d'aide à l'identification à l'aide de données d'image de maladies cutanées atypiques - Google Patents

Dispositif d'aide à l'identification à l'aide de données d'image de maladies cutanées atypiques Download PDF

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Publication number
WO2021153858A1
WO2021153858A1 PCT/KR2020/008024 KR2020008024W WO2021153858A1 WO 2021153858 A1 WO2021153858 A1 WO 2021153858A1 KR 2020008024 W KR2020008024 W KR 2020008024W WO 2021153858 A1 WO2021153858 A1 WO 2021153858A1
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WO
WIPO (PCT)
Prior art keywords
skin disease
image
information
skin
learning
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PCT/KR2020/008024
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English (en)
Korean (ko)
Inventor
장현재
김석호
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주식회사 에프앤디파트너스
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Publication of WO2021153858A1 publication Critical patent/WO2021153858A1/fr

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    • 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
    • G16H30/00—ICT specially adapted for the handling or processing of medical images
    • G16H30/20—ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
    • 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
    • G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
    • 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
    • G16H70/00—ICT specially adapted for the handling or processing of medical references
    • G16H70/60—ICT specially adapted for the handling or processing of medical references relating to pathologies

Definitions

  • the deep learning technique is a model of an artificial neural network that mimics the nervous system of an organism. If the existing artificial neural network model consists of a thin layer of neuron models, the deep learning technique builds a deep layer of neuron models. It is a technique to apply a model that increases the learning ability of a neural network by raising it.
  • the data-based artificial intelligence system generated by applying all the data used by doctors for diagnosis in the medical field that is, various clinical information other than medical images, has improved diagnostic performance compared to medical machine learning algorithms learned only from medical images. can be expected
  • a reading aid device using atypical skin disease image data according to the present invention
  • 1 is an exemplary view showing the shape of a general point and skin cancer.
  • FIG. 10 is an exemplary diagram of a convolution operation of a reading aid device using image data for atypical skin diseases according to an embodiment of the present invention.
  • Skin disease classified into the class by comparing the self-photographed skin disease image information or the skin disease image information transmitted by the smart device 2000 with the learning result information for class classification generated by the image-based skin disease learning unit 100 a skin disease learning apparatus 1000 configured to generate a diagnosis result and transmit the skin disease diagnosis result to the smart device 2000 of the user;
  • the image-based skin disease learning unit 100 As shown in Figure 5, the image-based skin disease learning unit 100,
  • a skin disease image conversion module 120 for converting the acquired skin disease image information according to the specifications of the CNN structure
  • skin disease image information to be learned A is malignant disease class numerical data 0.3, skin disease class numerical data 0.6, and normal skin class numerical data 0.1
  • the class is created as the learning result information of the skin disease image information A to be learned.
  • a photographed image output layer 2110 for outputting a skin image matched with the skin disease diagnosis result transmitted by the skin disease learning apparatus 1000;
  • an illumination wavelength band changing layer ( 2130);

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  • Health & Medical Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Public Health (AREA)
  • Medical Informatics (AREA)
  • Epidemiology (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Biomedical Technology (AREA)
  • Data Mining & Analysis (AREA)
  • Radiology & Medical Imaging (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Databases & Information Systems (AREA)
  • Pathology (AREA)
  • Measuring And Recording Apparatus For Diagnosis (AREA)
  • Image Analysis (AREA)
  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)

Abstract

La présente invention se rapporte à un dispositif d'aide à l'identification à l'aide de données d'image de maladies cutanées atypiques et, plus particulièrement, un dispositif destiné à aider à l'identification à l'aide de données d'image de maladies cutanées atypiques, les informations d'image de maladies cutanées étant classées en classes préconfigurées ; ces dernières étant apprises, stockées et gérées ; un dispositif d'apprentissage de maladie cutanée ou un dispositif intelligent pouvant être utilisé pour déterminer, parmi une maladie maligne, une maladie de pigment de la peau, une maladie infectieuse, et une peau normale, à quelle catégorie appartient une image de maladie cutanée acquise à partir d'un utilisateur qui a subi une authentification d'utilisateur ; et ces dernières sont simultanément fournies à une unité d'apprentissage de maladies cutanées à base d'image de telle sorte que ces dernières peuvent être apprises à nouveau.
PCT/KR2020/008024 2020-01-31 2020-06-20 Dispositif d'aide à l'identification à l'aide de données d'image de maladies cutanées atypiques WO2021153858A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
KR1020200011633A KR102162683B1 (ko) 2020-01-31 2020-01-31 비정형 피부질환 영상데이터를 활용한 판독보조장치
KR10-2020-0011633 2020-01-31

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WO2021153858A1 true WO2021153858A1 (fr) 2021-08-05

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KR (1) KR102162683B1 (fr)
WO (1) WO2021153858A1 (fr)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113808738A (zh) * 2021-09-18 2021-12-17 安徽爱朋科技有限公司 一种基于自识别影像的疾病识别系统

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114093507B (zh) * 2021-11-26 2024-02-13 南京邮电大学 边缘计算网络中基于对比学习的皮肤病智能分类方法
KR102654796B1 (ko) * 2021-11-29 2024-04-11 (주)스톤랩 시각 인공지능 활용 비침습 피부 생체지표 추정 기반 피부염 판별 시스템 및 그 방법
CN115631386B (zh) * 2022-12-19 2023-03-10 天津医之本医疗科技有限公司 一种基于机器学习的病理图像分类方法和系统

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KR20140018748A (ko) * 2012-08-03 2014-02-13 삼성전자주식회사 의료 영상에서 병변의 분석 장치 및 방법
KR101792541B1 (ko) * 2016-10-20 2017-11-02 주식회사 에프앤디파트너스 피부 진단 정보를 이용한 스마트기기 피부관리 서비스 제공시스템
KR20180068703A (ko) * 2016-12-14 2018-06-22 최성숙 구강 관리 서비스 시스템 및 방법
KR20190051256A (ko) * 2017-11-06 2019-05-15 주식회사 베이바이오텍 이미지 분석 결과 및 학습된 피부 인식기에 기초하여 피부의 상태를 평가하는 방법 및 프로그램
KR102041906B1 (ko) * 2019-03-06 2019-11-07 주식회사 에프앤디파트너스 안면피부촬영장치를 통해 촬영된 영상 이미지를 활용하여 피부질환을 판별하는 인공지능 기반의 안면 피부질환 판별용 api 엔진

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KR101623431B1 (ko) 2015-08-06 2016-05-23 주식회사 루닛 의료 영상의 병리 진단 분류 장치 및 이를 이용한 병리 진단 시스템

Patent Citations (5)

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KR20140018748A (ko) * 2012-08-03 2014-02-13 삼성전자주식회사 의료 영상에서 병변의 분석 장치 및 방법
KR101792541B1 (ko) * 2016-10-20 2017-11-02 주식회사 에프앤디파트너스 피부 진단 정보를 이용한 스마트기기 피부관리 서비스 제공시스템
KR20180068703A (ko) * 2016-12-14 2018-06-22 최성숙 구강 관리 서비스 시스템 및 방법
KR20190051256A (ko) * 2017-11-06 2019-05-15 주식회사 베이바이오텍 이미지 분석 결과 및 학습된 피부 인식기에 기초하여 피부의 상태를 평가하는 방법 및 프로그램
KR102041906B1 (ko) * 2019-03-06 2019-11-07 주식회사 에프앤디파트너스 안면피부촬영장치를 통해 촬영된 영상 이미지를 활용하여 피부질환을 판별하는 인공지능 기반의 안면 피부질환 판별용 api 엔진

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113808738A (zh) * 2021-09-18 2021-12-17 安徽爱朋科技有限公司 一种基于自识别影像的疾病识别系统

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