BR112021024432A2 - Sistema automático de diagnóstico de câncer cervical - Google Patents

Sistema automático de diagnóstico de câncer cervical

Info

Publication number
BR112021024432A2
BR112021024432A2 BR112021024432A BR112021024432A BR112021024432A2 BR 112021024432 A2 BR112021024432 A2 BR 112021024432A2 BR 112021024432 A BR112021024432 A BR 112021024432A BR 112021024432 A BR112021024432 A BR 112021024432A BR 112021024432 A2 BR112021024432 A2 BR 112021024432A2
Authority
BR
Brazil
Prior art keywords
cervical cancer
cervical
machine learning
automatic
information
Prior art date
Application number
BR112021024432A
Other languages
English (en)
Inventor
Hoon Jeong Jae
Original Assignee
Aidot Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from KR1020190109333A external-priority patent/KR102316557B1/ko
Application filed by Aidot Inc filed Critical Aidot Inc
Publication of BR112021024432A2 publication Critical patent/BR112021024432A2/pt

Links

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0033—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
    • A61B5/004—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 adapted for image acquisition of a particular organ or body part
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/1032—Determining colour for diagnostic purposes
    • 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
    • A61B5/4306—Detecting, measuring or recording for evaluating the reproductive systems for evaluating the female reproductive systems, e.g. gynaecological evaluations
    • A61B5/4318—Evaluation of the lower reproductive system
    • A61B5/4331—Evaluation of the lower reproductive system of the cervix
    • 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
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • 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
    • G16H50/70—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
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G06N20/20—Ensemble learning
    • 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
    • G06N3/0464—Convolutional networks [CNN, ConvNet]

Landscapes

  • Health & Medical Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Medical Informatics (AREA)
  • Public Health (AREA)
  • Biomedical Technology (AREA)
  • General Health & Medical Sciences (AREA)
  • Pathology (AREA)
  • Physics & Mathematics (AREA)
  • Biophysics (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Molecular Biology (AREA)
  • Surgery (AREA)
  • Animal Behavior & Ethology (AREA)
  • Veterinary Medicine (AREA)
  • Data Mining & Analysis (AREA)
  • Artificial Intelligence (AREA)
  • Primary Health Care (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Epidemiology (AREA)
  • Radiology & Medical Imaging (AREA)
  • Databases & Information Systems (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Mathematical Physics (AREA)
  • Evolutionary Computation (AREA)
  • Software Systems (AREA)
  • Theoretical Computer Science (AREA)
  • Signal Processing (AREA)
  • Fuzzy Systems (AREA)
  • Reproductive Health (AREA)
  • Physiology (AREA)
  • Psychiatry (AREA)
  • Oral & Maxillofacial Surgery (AREA)
  • Gynecology & Obstetrics (AREA)
  • Dentistry (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Computing Systems (AREA)
  • Image Analysis (AREA)
  • Image Processing (AREA)

Abstract

sistema automático de diagnóstico de câncer cervical. a presente invenção se refere a um sistema automático de diagnóstico de câncer cervical para realizar aprendizagem de máquina, classificando dados cervicais necessários para o diagnóstico automático de câncer cervical de acordo com critérios precisos e diagnosticando automaticamente o câncer cervical com base na aprendizagem de máquina, o sistema automático de diagnóstico de câncer cervical incluindo: um gerador de dados de aprendizagem configurado para classificar dados de imagem fotografada não classificados para um colo do útero transmitidos de um dispositivo externo ou um armazenamento de acordo com uma combinação de critérios de classificação multinível para gerar dados de aprendizagem para cada novo critério de classificação em um modo de aprendizagem; um pré-processador de imagem fotografada configurado para pré-processar imagens do colo do útero fotografadas; um diagnosticador de câncer cervical incluindo um modelo de aprendizagem de máquina para câncer cervical que aprende uma característica dos dados de aprendizagem gerados para cada critério de classificação no modo de aprendizagem, em que o modelo de aprendizagem de máquina gera informações de diagnóstico sobre se o câncer cervical ocorreu em relação à imagem pré-processada do colo do útero fotografado; um controlador de exibição de tela configurado para exibir e emitir uma tela de interface de usuário configurada para exibir as informações de diagnóstico e inserir informações de avaliação de acordo com um especialista em leitura; um gerador de dados de retreinamento configurado para extrair as informações necessárias para o retreinamento de informações de avaliação inseridas através da tela de interface do usuário e solicitar o retreinamento do modelo de aprendizagem de máquina; e um armazenamento de informações de diagnóstico e avaliação configurado para armazenar as informações de diagnóstico sobre a ocorrência de câncer cervical e a inserção de informações de avaliação através da tela de interface do usuário.
BR112021024432A 2019-06-04 2019-12-13 Sistema automático de diagnóstico de câncer cervical BR112021024432A2 (pt)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
KR20190066163 2019-06-04
KR1020190109333A KR102316557B1 (ko) 2019-06-04 2019-09-04 자궁경부암 자동 진단 시스템
PCT/KR2019/017679 WO2020246676A1 (ko) 2019-06-04 2019-12-13 자궁경부암 자동 진단 시스템

Publications (1)

Publication Number Publication Date
BR112021024432A2 true BR112021024432A2 (pt) 2022-02-01

Family

ID=73652674

Family Applications (1)

Application Number Title Priority Date Filing Date
BR112021024432A BR112021024432A2 (pt) 2019-06-04 2019-12-13 Sistema automático de diagnóstico de câncer cervical

Country Status (4)

Country Link
US (1) US20220328186A1 (pt)
JP (1) JP7346600B2 (pt)
BR (1) BR112021024432A2 (pt)
WO (1) WO2020246676A1 (pt)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
TWI748344B (zh) * 2020-02-14 2021-12-01 聚積科技股份有限公司 發光二極體調屏標準判定模型建立方法
WO2024101484A1 (ko) * 2022-11-11 2024-05-16 주식회사 카이미 인공지능 기반의 병변 검출 방법 및 장치

Family Cites Families (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR100850347B1 (ko) * 2007-10-30 2008-08-05 문정숙 통합의료진단 시스템 및 방법
JP2010204966A (ja) * 2009-03-03 2010-09-16 Nippon Telegr & Teleph Corp <Ntt> サンプリング装置、サンプリング方法、サンプリングプログラム、クラス判別装置およびクラス判別システム。
CN103096786A (zh) * 2010-05-03 2013-05-08 国际科学技术医疗系统有限责任公司 宫颈瘤变检测和诊断的图像分析
KR20130012297A (ko) * 2011-07-25 2013-02-04 삼성전자주식회사 병변 검출 장치, 병변 검출 방법 및 병변 진단 장치
CA2851152A1 (en) * 2011-10-05 2013-04-11 Cireca Theranostics, Llc Method and system for analyzing biological specimens by spectral imaging
KR101538392B1 (ko) * 2013-08-02 2015-07-22 주식회사 이도 자궁경부암 검사의 최종 판단을 위한 검사 결과 큐레이션 시스템
KR101682604B1 (ko) * 2014-10-23 2016-12-05 전북대학교산학협력단 자궁 경부암 자동 진단 시스템
CA3017027A1 (en) * 2016-03-17 2017-09-21 Avigilon Corporation System and method for training object classifier by machine learning
JPWO2018221689A1 (ja) * 2017-06-01 2020-04-02 株式会社ニデック 医療情報処理システム

Also Published As

Publication number Publication date
JP2022535431A (ja) 2022-08-08
JP7346600B2 (ja) 2023-09-19
WO2020246676A1 (ko) 2020-12-10
US20220328186A1 (en) 2022-10-13

Similar Documents

Publication Publication Date Title
US20170154209A1 (en) Image identification apparatus and image identification method
US11227384B2 (en) Methods and systems for determining a diagnostically unacceptable medical image
US10993653B1 (en) Machine learning based non-invasive diagnosis of thyroid disease
KR20190105210A (ko) 통합 의료 진단 서비스 제공 시스템 및 그 방법
BR112021024432A2 (pt) Sistema automático de diagnóstico de câncer cervical
US20190156942A1 (en) Apparatus for assessing medical device quality
WO2020123862A8 (en) Optical apparatus and associated devices for biometric identification and health status determination
US10572994B2 (en) Radiation imaging apparatus, radiation imaging system, radiation imaging method, and computer-readable medium
Greene et al. Under high perceptual load, observers look but do not see
WO2018222897A1 (en) Smartphone-based digital pupillometer
US20170156585A1 (en) Eye condition determination system
WO2016172340A1 (en) System and methods for assessing vision using a computing device
Jelinek et al. Data fusion for multi-lesion diabetic retinopathy detection
KR20220086128A (ko) 의료 영상 기반 질환 중증도 결정 장치 및 방법
CN106255109A (zh) 路由器权限认证方法和系统
Grzybowski et al. Artificial intelligence for diabetic retinopathy screening using color retinal photographs: from development to deployment
BR112020003495A2 (pt) sistema de reconhecimento de íris, método de reconhecimento de íris e meio de armazenamento
Thanos et al. Screening and treatments using telemedicine in retinopathy of prematurity
CN108009534A (zh) 基于瞳孔灰度的活体检测方法
Guarin et al. Automatic facial landmark localization in clinical populations-improving model performance with a small dataset
CN115206494A (zh) 基于眼底图像分类的阅片系统及阅片方法
Kundel How to minimize perceptual error and maximize expertise in medical imaging
US20210357634A1 (en) Methods and systems for processing documents with task-specific highlighting
JP2019113959A (ja) 鼻紋照合システム、鼻紋照合方法及び鼻紋照合プログラム
Lobmaier et al. Emotional expression affects the accuracy of gaze perception

Legal Events

Date Code Title Description
B07A Application suspended after technical examination (opinion) [chapter 7.1 patent gazette]
B09B Patent application refused [chapter 9.2 patent gazette]