Cargando…

Rapid Grading of Fundus Photographs for Diabetic Retinopathy Using Crowdsourcing

BACKGROUND: Screening for diabetic retinopathy is both effective and cost-effective, but rates of screening compliance remain suboptimal. As screening improves, new methods to deal with screening data may help reduce the human resource needs. Crowdsourcing has been used in many contexts to harness d...

Descripción completa

Detalles Bibliográficos
Autores principales:	Brady, Christopher J, Villanti, Andrea C, Pearson, Jennifer L, Kirchner, Thomas R, Gupta, Omesh P, Shah, Chirag P
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	JMIR Publications Inc. 2014
Materias:	Original Paper
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4259907/ https://www.ncbi.nlm.nih.gov/pubmed/25356929 http://dx.doi.org/10.2196/jmir.3807

Ejemplares similares

Inter-observer agreement in grading severity of diabetic retinopathy in wide-field fundus photographs
por: Srinivasan, Sangeetha, et al.
Publicado: (2023)

A Virtual Reading Center Model Using Crowdsourcing to Grade Photographs for Trachoma: Validation Study
por: Brady, Christopher J, et al.
Publicado: (2023)

Digital image processing software for diagnosing diabetic retinopathy from fundus photograph
por: Ratanapakorn, Tanapat, et al.
Publicado: (2019)

Cameras for Public Health Surveillance: A Methods Protocol for Crowdsourced Annotation of Point-of-Sale Photographs
por: Ilakkuvan, Vinu, et al.
Publicado: (2014)

Semi-automated quantification of hard exudates in colour fundus photographs diagnosed with diabetic retinopathy
por: Marupally, Abhilash Goud, et al.
Publicado: (2017)

Automatic Detection of Diabetic Retinopathy in Retinal Fundus Photographs Based on Deep Learning Algorithm
por: Li, Feng, et al.
Publicado: (2019)

Segmentation of Laser Marks of Diabetic Retinopathy in the Fundus Photographs Using Lightweight U-Net
por: Jiang, Yukang, et al.
Publicado: (2021)

A Deep Learning Framework for Earlier Prediction of Diabetic Retinopathy from Fundus Photographs
por: Gunasekaran, K., et al.
Publicado: (2022)

An Evaluation System of Fundus Photograph-Based Intelligent Diagnostic Technology for Diabetic Retinopathy and Applicability for Research
por: Yang, Wei-Hua, et al.
Publicado: (2019)

Mobile Telemedicine Screening for Diabetic Retinopathy Using Nonmydriatic Fundus Photographs in Burgundy: 11 Years of Results
por: Charlot, Anthony, et al.
Publicado: (2022)

Trends in Diabetic Retinopathy, Visual Acuity, and Treatment Outcomes for Patients Living With Diabetes in a Fundus Photograph–Based Diabetic Retinopathy Screening Program in Bangladesh
por: Muqit, Mahiul M. K., et al.
Publicado: (2019)

Agreement on Grading Retinal Findings of Patients with Diabetes Using Fundus Photographs by Allied Medical Personnel when Compared to an Ophthalmologist at a Diabetic Retinopathy Screening Program in Nepal
por: Thapa, Raba, et al.
Publicado: (2020)

On a New Instrument for Photographing the Fundus Oculi
por: Rosebrugh, A. M.
Publicado: (1864)

Diagnostic Accuracy of Detecting Diabetic Retinopathy by Using Digital Fundus Photographs in the Peripheral Health Facilities of Bangladesh: Validation Study
por: Begum, Tahmina, et al.
Publicado: (2021)

2D alpha-shapes to quantify retinal microvasculature morphology and their application to proliferative diabetic retinopathy characterisation in fundus photographs
por: Pead, Emma, et al.
Publicado: (2021)

Performance of the AIDRScreening system in detecting diabetic retinopathy in the fundus photographs of Chinese patients: a prospective, multicenter, clinical study
por: Yang, Yao, et al.
Publicado: (2022)

Automated Brightness and Contrast Adjustment of Color Fundus Photographs for the Grading of Age-Related Macular Degeneration
por: Tsikata, Edem, et al.
Publicado: (2017)

Deep Learning Fundus Image Analysis for Diabetic Retinopathy and Macular Edema Grading
por: Sahlsten, Jaakko, et al.
Publicado: (2019)

Diagnostic accuracy of a digital fundus photographic system for detection of retinopathy of prematurity requiring treatment (ROP-RT)
por: Wongwai, Phanthipha, et al.
Publicado: (2018)

Registration of OCT fundus images with color fundus photographs based on blood vessel ridges
por: Li, Ying, et al.
Publicado: (2010)

Frequency, severity and risk indicators of retinopathy in patients with diabetes screened by fundus photographs: a study from primary health care
por: Memon, Saleh, et al.
Publicado: (2014)

Global Assessment of Retinal Arteriolar, Venular and Capillary Microcirculations Using Fundus Photographs and Optical Coherence Tomography Angiography in Diabetic Retinopathy
por: Tan, Tien-En, et al.
Publicado: (2019)

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
por: Bawankar, Pritam, et al.
Publicado: (2017)

Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photographs using deep learning
por: Varadarajan, Avinash V., et al.
Publicado: (2020)

Reproduction study using public data of: Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs
por: Voets, Mike, et al.
Publicado: (2019)

Predicting Optical Coherence Tomography-Derived High Myopia Grades From Fundus Photographs Using Deep Learning
por: Wu, Zhenquan, et al.
Publicado: (2022)

An Artificial-Intelligence–Based Automated Grading and Lesions Segmentation System for Myopic Maculopathy Based on Color Fundus Photographs
por: Tang, Jia, et al.
Publicado: (2022)

A review on automatic analysis techniques for color fundus photographs
por: Besenczi, Renátó, et al.
Publicado: (2016)

The subjectivity of objective evaluation of torsion on fundus photographs by practicing strabismologists
por: Jethani, Jitendra, et al.
Publicado: (2018)

Towards population-independent, multi-disease detection in fundus photographs
por: Matta, Sarah, et al.
Publicado: (2023)

The use of artificial intelligence in detecting papilledema from fundus photographs
por: Anandi, Lazuardiah, et al.
Publicado: (2023)

Test accuracy of artificial intelligence-based grading of fundus images in diabetic retinopathy screening: A systematic review
por: Zhelev, Zhivko, et al.
Publicado: (2023)

Fundus fluorescence Angiography in diagnosing diabetic retinopathy
por: Wang, Shuhui, et al.
Publicado: (2017)

Selfie fundus imaging for diabetic retinopathy screening
por: Kumari, Somya, et al.
Publicado: (2021)

Validation of Artificial Intelligence Algorithm in the Detection and Staging of Diabetic Retinopathy through Fundus Photography: An Automated Tool for Detection and Grading of Diabetic Retinopathy
por: Pawar, Bhargavi, et al.
Publicado: (2021)

Dataset from fundus images for the study of diabetic retinopathy
por: Castillo Benítez, Veronica Elisa, et al.
Publicado: (2021)

An analysis of companion animal tick encounters as revealed by photograph‐based crowdsourced data
por: Kopsco, Heather L., et al.
Publicado: (2021)

Differential distribution of manifest lesions in diabetic retinopathy by fundus fluorescein angiography and fundus photography
por: Li, Xiaoli, et al.
Publicado: (2020)

A Deep Learning Based Approach for Grading of Diabetic Retinopathy Using Large Fundus Image Dataset
por: Mehboob, Ayesha, et al.
Publicado: (2022)

Evaluation of a System for Automatic Detection of Diabetic Retinopathy From Color Fundus Photographs in a Large Population of Patients With Diabetes: Response to Olson et al.
por: Abràmoff, Michael D., et al.
Publicado: (2008)

Cannot write session to /tmp/vufind_sessions/sess_2t6vb68gpvsg5sej6gti9h1get