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
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- 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
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- 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)
- Image Analysis (AREA)
- Eye Examination Apparatus (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 of modifying a retina fundus image for a 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 (en) |
EP (1) | EP3659067B1 (en) |
CN (2) | CN110914835B (en) |
SG (1) | SG11201912260TA (en) |
WO (1) | WO2019022663A1 (en) |
Families Citing this family (14)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2019024568A1 (en) * | 2017-08-02 | 2019-02-07 | 上海市第六人民医院 | Ocular fundus image processing method and apparatus, computer device, and storage medium |
CN110349156B (en) * | 2017-11-30 | 2023-05-30 | 腾讯科技(深圳)有限公司 | Method and device for identifying lesion characteristics in fundus picture and storage medium |
CN110648303B (en) * | 2018-06-08 | 2022-07-26 | 上海市第六人民医院 | Fundus image analysis method, computer device, and storage medium |
SG11202108411SA (en) | 2019-02-12 | 2021-08-30 | Nat Univ Singapore | Retina vessel measurement |
CN110013216B (en) * | 2019-03-12 | 2022-04-22 | 中山大学中山眼科中心 | Artificial intelligence cataract analysis system |
WO2020194663A1 (en) * | 2019-03-28 | 2020-10-01 | オリンパス株式会社 | Tracking device, pretained model, endoscope system, and tracking method |
CN110361625B (en) * | 2019-07-23 | 2022-01-28 | 中南大学 | Method for diagnosing open-circuit fault of inverter and electronic equipment |
CN112967331B (en) * | 2021-03-25 | 2021-12-17 | 北京的卢深视科技有限公司 | Image processing method, electronic equipment and storage medium |
CN113344894B (en) * | 2021-06-23 | 2024-05-14 | 依未科技(北京)有限公司 | Method and device for extracting features of fundus leopard spots and determining feature indexes |
AT525510A1 (en) * | 2021-09-24 | 2023-04-15 | Mathias Zirm Univ Prof Dr | Method of operating a digital camera to image the retina |
CN116168255B (en) * | 2023-04-10 | 2023-12-08 | 武汉大学人民医院(湖北省人民医院) | Retina OCT (optical coherence tomography) image classification method with robust long tail distribution |
CN116309584B (en) * | 2023-05-22 | 2023-07-28 | 泰安光明爱尔眼科医院有限公司 | Image processing system for cataract area identification |
CN116504378B (en) * | 2023-06-26 | 2023-10-31 | 杭州目乐医疗科技股份有限公司 | Control method and system of vision screening instrument |
CN116740203B (en) * | 2023-08-15 | 2023-11-28 | 山东理工职业学院 | Safety storage method for fundus camera data |
Family Cites Families (23)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP5539123B2 (en) * | 2010-08-31 | 2014-07-02 | キヤノン株式会社 | Ophthalmologic photographing apparatus and photographing method using ophthalmic photographing apparatus |
US9564085B2 (en) * | 2012-05-27 | 2017-02-07 | Dialog Semiconductor Inc. | Selective dimming to reduce power of a light emitting display device |
US9898659B2 (en) | 2013-05-19 | 2018-02-20 | Commonwealth Scientific And Industrial Research Organisation | System and method for remote medical diagnosis |
JP6367530B2 (en) * | 2013-07-11 | 2018-08-01 | 株式会社トーメーコーポレーション | Tomographic imaging apparatus and tomographic image generation control method |
US8879813B1 (en) * | 2013-10-22 | 2014-11-04 | Eyenuk, Inc. | Systems and methods for automated interest region detection in retinal images |
CN103870838A (en) * | 2014-03-05 | 2014-06-18 | 南京航空航天大学 | Eye fundus image characteristics extraction method for diabetic retinopathy |
CN104102899B (en) * | 2014-05-23 | 2017-07-14 | 首都医科大学附属北京同仁医院 | Retinal vessel recognition methods and device |
CN104463140B (en) * | 2014-12-23 | 2017-09-29 | 天津工业大学 | A kind of colored eye fundus image optic disk automatic positioning method |
US9757023B2 (en) * | 2015-05-27 | 2017-09-12 | The Regents Of The University Of Michigan | Optic disc detection in retinal autofluorescence images |
WO2017031099A1 (en) * | 2015-08-20 | 2017-02-23 | 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 (en) * | 2016-02-04 | 2019-01-01 | 浙江工商大学 | Ocular fundus image registration method based on characteristics of image |
CN105761258B (en) * | 2016-02-06 | 2018-06-01 | 上海市第一人民医院 | A kind of color fundus photograph image bleeding automatic identification method |
CN105787927B (en) * | 2016-02-06 | 2018-06-01 | 上海市第一人民医院 | Automatic identification method is oozed out in a kind of color fundus photograph image |
CN106355599B (en) * | 2016-08-30 | 2019-03-29 | 上海交通大学 | Retinal vessel automatic division method based on non-fluorescence eye fundus image |
WO2018045363A1 (en) * | 2016-09-02 | 2018-03-08 | Gargeya Rishab | Screening method for automated detection of vision-degenerative diseases from color fundus images |
CN106407917B (en) * | 2016-09-05 | 2017-07-25 | 山东大学 | The retinal vessel extracting method and system distributed based on Dynamic Multi-scale |
CN106408562B (en) * | 2016-09-22 | 2019-04-09 | 华南理工大学 | Eye fundus image Segmentation Method of Retinal Blood Vessels and system based on deep learning |
CN106725295A (en) | 2016-11-29 | 2017-05-31 | 瑞达昇科技(大连)有限公司 | A kind of miniature check-up equipment, device and its application method |
CN106651899B (en) * | 2016-12-09 | 2019-07-23 | 东北大学 | Eye fundus image aneurysms detection system based on Adaboost |
CN106846301B (en) * | 2016-12-29 | 2020-06-23 | 北京理工大学 | Retina image classification method and device |
WO2018148451A1 (en) * | 2017-02-08 | 2018-08-16 | Scanoptix, Inc. | Device and method for capturing, analyzing, and sending still and video images of the fundus |
US10019788B1 (en) * | 2017-02-14 | 2018-07-10 | Cogniac, Corp. | Machine-learning measurements of quantitative feature attributes |
-
2018
- 2018-07-24 EP EP18838100.8A patent/EP3659067B1/en active Active
- 2018-07-24 CN CN201880047123.7A patent/CN110914835B/en active Active
- 2018-07-24 US US16/634,442 patent/US11200707B2/en active Active
- 2018-07-24 WO PCT/SG2018/050363 patent/WO2019022663A1/en active Application Filing
- 2018-07-24 SG SG11201912260TA patent/SG11201912260TA/en unknown
- 2018-07-24 CN CN202110528492.1A patent/CN113284101A/en active Pending
Also Published As
Publication number | Publication date |
---|---|
EP3659067A4 (en) | 2021-04-07 |
CN110914835B (en) | 2024-04-19 |
US20200211235A1 (en) | 2020-07-02 |
EP3659067C0 (en) | 2023-09-20 |
US11200707B2 (en) | 2021-12-14 |
WO2019022663A1 (en) | 2019-01-31 |
EP3659067A1 (en) | 2020-06-03 |
CN110914835A (en) | 2020-03-24 |
CN113284101A (en) | 2021-08-20 |
EP3659067B1 (en) | 2023-09-20 |
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