SG11201912260TA - Method of modifying a retina fundus image for a deep learning model - Google Patents
Method of modifying a retina fundus image for a deep learning modelInfo
- Publication number
- SG11201912260TA SG11201912260TA SG11201912260TA SG11201912260TA SG11201912260TA SG 11201912260T A SG11201912260T A SG 11201912260TA SG 11201912260T A SG11201912260T A SG 11201912260TA SG 11201912260T A SG11201912260T A SG 11201912260TA SG 11201912260T A SG11201912260T A SG 11201912260TA
- Authority
- SG
- Singapore
- Prior art keywords
- modifying
- learning model
- deep learning
- fundus image
- retina fundus
- Prior art date
Links
Classifications
-
- 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
- G06T7/0014—Biomedical image inspection using an image reference approach
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/28—Quantising the image, e.g. histogram thresholding for discrimination between background and foreground patterns
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B3/00—Apparatus for testing the eyes; Instruments for examining the eyes
- A61B3/0016—Operational features thereof
- A61B3/0025—Operational features thereof characterised by electronic signal processing, e.g. eye models
-
- 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
-
- 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
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
- G06T11/001—Texturing; Colouring; Generation of texture or colour
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
- G06T11/40—Filling a planar surface by adding surface attributes, e.g. colour or texture
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
- G06V10/443—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components by matching or filtering
- G06V10/449—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters
- G06V10/451—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters with interaction between the filter responses, e.g. cortical complex cells
- G06V10/454—Integrating the filters into a hierarchical structure, e.g. convolutional neural networks [CNN]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/764—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/18—Eye characteristics, e.g. of the iris
- G06V40/193—Preprocessing; Feature extraction
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B3/00—Apparatus for testing the eyes; Instruments for examining the eyes
- A61B3/10—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions
- A61B3/12—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions for looking at the eye fundus, e.g. ophthalmoscopes
-
- 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
- G06T2207/20081—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
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
- G06T2207/30041—Eye; Retina; Ophthalmic
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2210/00—Indexing scheme for image generation or computer graphics
- G06T2210/41—Medical
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V2201/00—Indexing scheme relating to image or video recognition or understanding
- G06V2201/03—Recognition of patterns in medical or anatomical images
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Evolutionary Computation (AREA)
- Multimedia (AREA)
- Molecular Biology (AREA)
- Biomedical Technology (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Medical Informatics (AREA)
- Biophysics (AREA)
- Software Systems (AREA)
- Computing Systems (AREA)
- Ophthalmology & Optometry (AREA)
- Veterinary Medicine (AREA)
- General Engineering & Computer Science (AREA)
- Animal Behavior & Ethology (AREA)
- Public Health (AREA)
- Heart & Thoracic Surgery (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Surgery (AREA)
- Mathematical Physics (AREA)
- Databases & Information Systems (AREA)
- Biodiversity & Conservation Biology (AREA)
- Signal Processing (AREA)
- Quality & Reliability (AREA)
- Radiology & Medical Imaging (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Human Computer Interaction (AREA)
- Eye Examination Apparatus (AREA)
- Image Analysis (AREA)
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
SG10201706186V | 2017-07-28 | ||
PCT/SG2018/050363 WO2019022663A1 (en) | 2017-07-28 | 2018-07-24 | METHOD FOR MODIFYING RETINA BACKGROUND IMAGE FOR DEEP LEARNING MODEL |
Publications (1)
Publication Number | Publication Date |
---|---|
SG11201912260TA true SG11201912260TA (en) | 2020-01-30 |
Family
ID=65040684
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
SG11201912260TA SG11201912260TA (en) | 2017-07-28 | 2018-07-24 | Method of modifying a retina fundus image for a deep learning model |
Country Status (5)
Country | Link |
---|---|
US (1) | US11200707B2 (zh) |
EP (1) | EP3659067B1 (zh) |
CN (2) | CN113284101A (zh) |
SG (1) | SG11201912260TA (zh) |
WO (1) | WO2019022663A1 (zh) |
Families Citing this family (14)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US11200665B2 (en) * | 2017-08-02 | 2021-12-14 | Shanghai Sixth People's Hospital | Fundus image processing method, computer apparatus, and storage medium |
CN108230296B (zh) * | 2017-11-30 | 2023-04-07 | 腾讯科技(深圳)有限公司 | 图像特征的识别方法和装置、存储介质、电子装置 |
CN110648303B (zh) * | 2018-06-08 | 2022-07-26 | 上海市第六人民医院 | 眼底图像分析方法、计算机设备和存储介质 |
EP3924885A4 (en) * | 2019-02-12 | 2022-11-16 | National University of Singapore | RETINAL VESSEL MEASUREMENT |
CN110013216B (zh) * | 2019-03-12 | 2022-04-22 | 中山大学中山眼科中心 | 一种人工智能白内障分析系统 |
JP7105369B2 (ja) * | 2019-03-28 | 2022-07-22 | オリンパス株式会社 | トラッキング装置、学習済モデル、内視鏡システム及びトラッキング方法 |
CN110361625B (zh) * | 2019-07-23 | 2022-01-28 | 中南大学 | 一种用于逆变器开路故障诊断的方法和电子设备 |
CN112967331B (zh) * | 2021-03-25 | 2021-12-17 | 北京的卢深视科技有限公司 | 一种图像处理的方法、电子设备及存储介质 |
CN113344894B (zh) * | 2021-06-23 | 2024-05-14 | 依未科技(北京)有限公司 | 眼底豹纹斑特征提取及特征指数确定的方法和装置 |
AT525510A1 (de) * | 2021-09-24 | 2023-04-15 | Mathias Zirm Univ Prof Dr | Verfahren zum Betrieb einer digitalen Kamera zur Abbildung der Netzhaut |
CN116168255B (zh) * | 2023-04-10 | 2023-12-08 | 武汉大学人民医院(湖北省人民医院) | 一种长尾分布鲁棒的视网膜oct图像分类方法 |
CN116309584B (zh) * | 2023-05-22 | 2023-07-28 | 泰安光明爱尔眼科医院有限公司 | 一种用于白内障区域识别的图像处理系统 |
CN116504378B (zh) * | 2023-06-26 | 2023-10-31 | 杭州目乐医疗科技股份有限公司 | 一种视力筛查仪的控制方法与系统 |
CN116740203B (zh) * | 2023-08-15 | 2023-11-28 | 山东理工职业学院 | 用于眼底相机数据的安全存储方法 |
Family Cites Families (23)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP5539123B2 (ja) * | 2010-08-31 | 2014-07-02 | キヤノン株式会社 | 眼科撮影装置および眼科撮影装置を用いた撮影方法 |
US9564085B2 (en) * | 2012-05-27 | 2017-02-07 | Dialog Semiconductor Inc. | Selective dimming to reduce power of a light emitting display device |
AU2014271202B2 (en) | 2013-05-19 | 2019-12-12 | Commonwealth Scientific And Industrial Research Organisation | A system and method for remote medical diagnosis |
JP6367530B2 (ja) * | 2013-07-11 | 2018-08-01 | 株式会社トーメーコーポレーション | 断層画像撮影装置及び断層画像の画像生成制御方法 |
EP3061063A4 (en) * | 2013-10-22 | 2017-10-11 | Eyenuk, Inc. | Systems and methods for automated analysis of retinal images |
CN103870838A (zh) * | 2014-03-05 | 2014-06-18 | 南京航空航天大学 | 糖尿病视网膜病变的眼底图像特征提取方法 |
CN104102899B (zh) * | 2014-05-23 | 2017-07-14 | 首都医科大学附属北京同仁医院 | 视网膜血管识别方法及装置 |
CN104463140B (zh) * | 2014-12-23 | 2017-09-29 | 天津工业大学 | 一种彩色眼底图像视盘自动定位方法 |
US9757023B2 (en) * | 2015-05-27 | 2017-09-12 | The Regents Of The University Of Michigan | Optic disc detection in retinal autofluorescence images |
US10722115B2 (en) * | 2015-08-20 | 2020-07-28 | Ohio University | Devices and methods for classifying diabetic and macular degeneration |
US10405739B2 (en) * | 2015-10-23 | 2019-09-10 | International Business Machines Corporation | Automatically detecting eye type in retinal fundus images |
CN105761254B (zh) * | 2016-02-04 | 2019-01-01 | 浙江工商大学 | 基于图像特征的眼底图像配准方法 |
CN105787927B (zh) * | 2016-02-06 | 2018-06-01 | 上海市第一人民医院 | 一种眼底彩色照相图像中渗出自动化识别方法 |
CN105761258B (zh) * | 2016-02-06 | 2018-06-01 | 上海市第一人民医院 | 一种眼底彩色照相图像出血自动化识别方法 |
CN106355599B (zh) * | 2016-08-30 | 2019-03-29 | 上海交通大学 | 基于非荧光眼底图像的视网膜血管自动分割方法 |
WO2018045363A1 (en) * | 2016-09-02 | 2018-03-08 | Gargeya Rishab | Screening method for automated detection of vision-degenerative diseases from color fundus images |
CN106407917B (zh) * | 2016-09-05 | 2017-07-25 | 山东大学 | 基于动态尺度分配的视网膜血管提取方法及系统 |
CN106408562B (zh) * | 2016-09-22 | 2019-04-09 | 华南理工大学 | 基于深度学习的眼底图像视网膜血管分割方法及系统 |
CN106725295A (zh) | 2016-11-29 | 2017-05-31 | 瑞达昇科技(大连)有限公司 | 一种微型体检设备、装置及其使用方法 |
CN106651899B (zh) * | 2016-12-09 | 2019-07-23 | 东北大学 | 基于Adaboost的眼底图像微动脉瘤检测系统 |
CN106846301B (zh) * | 2016-12-29 | 2020-06-23 | 北京理工大学 | 视网膜图像分类方法及装置 |
JP6850506B2 (ja) * | 2017-02-08 | 2021-03-31 | スカノプティックス インク | 検眼鏡を用いた検査中の眼底の静止画像およびビデオ画像を取り込み、分析し、および送信するための装置および方法 |
US10019788B1 (en) * | 2017-02-14 | 2018-07-10 | Cogniac, Corp. | Machine-learning measurements of quantitative feature attributes |
-
2018
- 2018-07-24 CN CN202110528492.1A patent/CN113284101A/zh active Pending
- 2018-07-24 US US16/634,442 patent/US11200707B2/en active Active
- 2018-07-24 SG SG11201912260TA patent/SG11201912260TA/en unknown
- 2018-07-24 EP EP18838100.8A patent/EP3659067B1/en active Active
- 2018-07-24 WO PCT/SG2018/050363 patent/WO2019022663A1/en active Application Filing
- 2018-07-24 CN CN201880047123.7A patent/CN110914835B/zh active Active
Also Published As
Publication number | Publication date |
---|---|
US11200707B2 (en) | 2021-12-14 |
CN110914835A (zh) | 2020-03-24 |
EP3659067C0 (en) | 2023-09-20 |
EP3659067A4 (en) | 2021-04-07 |
EP3659067A1 (en) | 2020-06-03 |
CN113284101A (zh) | 2021-08-20 |
CN110914835B (zh) | 2024-04-19 |
WO2019022663A1 (en) | 2019-01-31 |
EP3659067B1 (en) | 2023-09-20 |
US20200211235A1 (en) | 2020-07-02 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
SG11201912260TA (en) | Method of modifying a retina fundus image for a deep learning model | |
IL262440A (en) | A method for preparing retinal tissue | |
SG11202106315QA (en) | Explainability-based adjustment of machine learning models | |
GB2589272B (en) | A method for creating a prediction model of driving comfort | |
EP3490454A4 (en) | METHODS AND SYSTEMS FOR CHARACTERIZING A SUBJECT FABRIC USING MACHINE LEARNING | |
IL251856A0 (en) | A method for producing retinal tissue | |
HK1219803A1 (zh) | 種語言模型的訓練方法及裝置、設備 | |
HK1246956A1 (zh) | 製造模型的方法和模型 | |
GB201402643D0 (en) | A method of mapping images of human disease | |
EP3329316A4 (en) | PURSUIT OF CORNEAL SPHERE TO GENERATE A MODEL OF EYE | |
SG11201701024WA (en) | Method of implantation of a medical device into neural tissue | |
SI3679894T1 (sl) | Postopek radialnega stisnjenja umetne srčne zaklopke | |
PT3139815T (pt) | Método para a aquisição dos dados de imagem de tomografia de coerência ótica do tecido da retina de um olho de um sujeito humano | |
FI3723849T3 (fi) | Menetelmä implantoitavan lääkinnällisen laitteen pääosan valmistamiseksi | |
EP3566747A4 (en) | MEDICAL IMAGE DATA-BASED METHOD FOR PRODUCING A SMOOTH GEOMETRIC MODEL | |
GB201718895D0 (en) | A method of generating training data | |
EP3719779A4 (en) | SIMULATED EYE BALL, EYE SURGERY TRAINING DEVICE AND EYE SURGERY TRAINING METHOD | |
GB201705665D0 (en) | A system and method for training use of a toothbrush | |
EP3153097C0 (en) | METHOD AND SYSTEM FOR EVALUATING A PERSON’S TRAINING EXPERIENCE | |
IL273946A (en) | Sustained release implants to reduce intraocular pressure with extended duration of activity | |
PL3169243T3 (pl) | Sposób uzyskiwania parametrów czynnościowych mięśnia | |
GB202005721D0 (en) | Opthalmoscope using natural pupil dilation | |
EP3628013C0 (en) | BIOMIMETIC ARTIFICIAL BLOOD VESSEL AND PRODUCTION METHOD THEREOF | |
EP3127558A4 (en) | Method for producing artificial retina | |
IL273635B (en) | A body containing a pair of multifocal ocular implants |