Image harmonization and deep learning automated classification of plus disease in retinopathy of prematurity-Reference-Cited by-同舟云学术

Image harmonization and deep learning automated classification of plus disease in retinopathy of prematurity

Published:2023-10-03 Issue:06 Volume:10 Page:
ISSN:2329-4302
Container-title:Journal of Medical Imaging
language:
Short-container-title:J. Med. Imag.

Author:

Subramaniam Ananya¹,Orge Faruk²,Douglass Michael¹,Can Basak²,Monteoliva Guillermo³,Fried Evelin³,Schbib Vanina⁴,Saidman Gabriela⁵,Peña Brenda⁶,Ulacia Soledad⁷,Acevedo Pedro⁸,Rollins Andrew M.¹,Wilson David L.¹

Affiliation:

1. Case Western Reserve University, Department of Biomedical Engineering, Cleveland, Ohio, United States

2. Case Medical Center University Hospitals, Department of Ophthalmology, Cleveland, Ohio, United States

3. Hospital Italiano de San Justo Agustin Rocca, Buenos Aires, Argentina

4. Hospital de Niños Sor Maria Ludovica, Buenos Aires, Argentina

5. Hospital Evita Pueblo de Berazategui, Buenos Aires, Argentina

6. Centro Integral de Salud Visual Daponte, Buenos Aires, Argentina

7. Mineserio de Salud Argentina, Ministry of Public Works Building, Buenos Aires, Argentina

8. Fundación Oftalmológica Nacional, Bogotá, Colombia

Publisher

SPIE-Intl Soc Optical Eng

Subject

Radiology, Nuclear Medicine and imaging

Reference28 articles.

1. Retinopathy of prematurity: Past, present and future

2. Automated diagnosis of plus disease in retinopathy of prematurity using deep convolutional neural networks | Neonatology | JAMA ophthalmology | JAMA network;Brown,2018

3. Retinopathy of prematurity

4. Plus disease: Why is it important in retinopathy of prematurity?

5. Variability in Plus Disease Identified Using a Deep Learning-Based Retinopathy of Prematurity Severity Scale

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