[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Hassan et al., 2019 - Google Patents

Deep ensemble learning based objective grading of macular edema by extracting clinically significant findings from fused retinal imaging modalities

Hassan et al., 2019

View HTML
Document ID
9494091721898604268
Author
Hassan B
Hassan T
Li B
Ahmed R
Hassan O
Publication year
Publication venue
Sensors

External Links

Snippet

Macular edema (ME) is a retinal condition in which central vision of a patient is affected. ME leads to accumulation of fluid in the surrounding macular region resulting in a swollen macula. Optical coherence tomography (OCT) and the fundus photography are the two …
Continue reading at www.mdpi.com (HTML) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34—Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
    • G06F19/345—Medical expert systems, neural networks or other automated diagnosis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/32—Medical data management, e.g. systems or protocols for archival or communication of medical images, computerised patient records or computerised general medical references
    • G06F19/322—Management of patient personal data, e.g. patient records, conversion of records or privacy aspects
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/22—Health care, e.g. hospitals; Social work
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; 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
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
    • G06Q50/01—Social networking
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F15/00—Digital computers in general; Data processing equipment in general
    • G06F15/18—Digital computers in general; Data processing equipment in general in which a programme is changed according to experience gained by the computer itself during a complete run; Learning machines
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons

Similar Documents

Publication Publication Date Title
Hassan et al. Deep ensemble learning based objective grading of macular edema by extracting clinically significant findings from fused retinal imaging modalities
Alam et al. Supervised machine learning based multi-task artificial intelligence classification of retinopathies
Maqsood et al. Hemorrhage detection based on 3D CNN deep learning framework and feature fusion for evaluating retinal abnormality in diabetic patients
Malik et al. Data driven approach for eye disease classification with machine learning
Hassan et al. Enhanced deep learning model for classification of retinal optical coherence tomography images
Heo et al. Development of a deep-learning-based artificial intelligence tool for differential diagnosis between dry and neovascular age-related macular degeneration
Kim et al. Development of a fundus image-based deep learning diagnostic tool for various retinal diseases
Muchuchuti et al. Retinal disease detection using deep learning techniques: a comprehensive review
Kim et al. Development and validation of a deep learning system for diagnosing glaucoma using optical coherence tomography
Camara et al. Literature review on artificial intelligence methods for glaucoma screening, segmentation, and classification
Shoukat et al. Automatic diagnosis of glaucoma from retinal images using deep learning approach
He et al. Automatic detection of age-related macular degeneration based on deep learning and local outlier factor algorithm
Hemamalini et al. Outlier Based Skimpy Regularization Fuzzy Clustering Algorithm for Diabetic Retinopathy Image Segmentation
Shamsan et al. Automatic classification of colour fundus images for prediction eye disease types based on hybrid features
Park et al. Deep learning model based on 3D optical coherence tomography images for the automated detection of pathologic myopia
Neto et al. Evaluations of deep learning approaches for glaucoma screening using retinal images from mobile device
Zheng et al. Intelligent evaluation of strabismus in videos based on an automated cover test
Özdaş et al. Classification of retinal diseases in optical coherence tomography images using artificial intelligence and firefly algorithm
Mujeeb Rahman et al. Automatic screening of diabetic retinopathy using fundus images and machine learning algorithms
Saeed et al. An approach to automatic hard exudate detection in retina color images by a telemedicine system based on the d-eye sensor and image processing algorithms
Bragança et al. Detection of glaucoma on fundus images using deep learning on a new image set obtained with a smartphone and handheld ophthalmoscope
Wan Zaki et al. Towards a connected mobile cataract screening system: A future approach
Lin et al. Recent advanced deep learning architectures for retinal fluid segmentation on optical coherence tomography images
Prananda et al. Retinal nerve fiber layer analysis using deep learning to improve glaucoma detection in eye disease assessment
Yasser et al. Automated diagnosis of optical coherence tomography angiography (OCTA) based on machine learning techniques