about
The Accuracy and Reliability of Crowdsource Annotations of Digital Retinal ImagesGaps in Glaucoma care: A systematic review of monoscopic disc photos to screen for glaucomaAutomated detection of diabetic retinopathy in retinal imagesCrowdsourcing as a novel technique for retinal fundus photography classification: analysis of images in the EPIC Norfolk cohort on behalf of the UK Biobank Eye and Vision Consortium.Automated detection of diabetic retinopathy: barriers to translation into clinical practiceTelemedicine and ocular health in diabetes mellitus.The reading of components of diabetic retinopathy: an evolutionary approach for filtering normal digital fundus imaging in screening and population based studies.Computational quantification of complex fundus phenotypes in age-related macular degeneration and Stargardt diseaseRetinal imaging and image analysis.Results of Automated Retinal Image Analysis for Detection of Diabetic Retinopathy from the Nakuru Study, Kenya.Combined Methods for Diabetic Retinopathy Screening, Using Retina Photographs and Tear Fluid Proteomics Biomarkers.Imager evaluation of diabetic retinopathy at the time of imaging in a telemedicine program.Validation of tablet-based evaluation of color fundus images.Validating retinal fundus image analysis algorithms: issues and a proposal.Guest editorial: Opportunities in rehabilitation research.Brightness-preserving fuzzy contrast enhancement scheme for the detection and classification of diabetic retinopathy disease.Digital ocular fundus imaging: a review.Screening for diabetic retinopathy: review of current methods.Screening, prevention, and ambitious management of diabetic macular edema in patients with type 1 diabetes.Automated retinal image analysis for diabetic retinopathy in telemedicine.Evaluation of automated image analysis software for the detection of diabetic retinopathy to reduce the ophthalmologists' workload.A study of whether automated Diabetic Retinopathy Image Assessment could replace manual grading steps in the English National Screening Programme.An Active Learning Classifier for Further Reducing Diabetic Retinopathy Screening System CostDevelopment and Validation of a Deep Learning System for Diabetic Retinopathy and Related Eye Diseases Using Retinal Images From Multiethnic Populations With Diabetes.Validation of automated screening for referable diabetic retinopathy with the IDx-DR device in the Hoorn Diabetes Care System.Sensitivity and specificity of automated analysis of single-field non-mydriatic fundus photographs by Bosch DR Algorithm-Comparison with mydriatic fundus photography (ETDRS) for screening in undiagnosed diabetic retinopathy.Tracking and diameter estimation of retinal vessels using Gaussian process and Radon transform.The Tromsø Eye Study: study design, methodology and results on visual acuity and refractive errors.Improved automated screening of diabetic retinopathy.Automated Detection of Diabetic Retinopathy using Deep Learning.
P2860
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P2860
description
2010 nî lūn-bûn
@nan
2010 թուականի Յունիսին հրատարակուած գիտական յօդուած
@hyw
2010 թվականի հունիսին հրատարակված գիտական հոդված
@hy
2010年の論文
@ja
2010年論文
@yue
2010年論文
@zh-hant
2010年論文
@zh-hk
2010年論文
@zh-mo
2010年論文
@zh-tw
2010年论文
@wuu
name
Automated early detection of diabetic retinopathy.
@ast
Automated early detection of diabetic retinopathy.
@en
type
label
Automated early detection of diabetic retinopathy.
@ast
Automated early detection of diabetic retinopathy.
@en
prefLabel
Automated early detection of diabetic retinopathy.
@ast
Automated early detection of diabetic retinopathy.
@en
P2093
P2860
P1433
P1476
Automated early detection of diabetic retinopathy.
@en
P2093
Gwénolé Quellec
James C Folk
Joseph M Reinhardt
Meindert Niemeijer
Michael D Abràmoff
Stephen R Russell
Vinit B Mahajan
P2860
P304
P356
10.1016/J.OPHTHA.2010.03.046
P577
2010-06-01T00:00:00Z