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. 2018 Mar;6(1):36-45.
doi: 10.1007/s40135-018-0161-8. Epub 2018 Jan 29.

Retinal Telemedicine

Ru-Ik Chee  1 , Dana Darwish  1 , Alvaro Fernandez-Vega  1   2   3 , Samir Patel  2 , Karyn Jonas  1 , Susan Ostmo  3 , J Peter Campbell  3 , Michael F Chiang  3 , Rv Paul Chan  1
Affiliations

Retinal Telemedicine

Ru-Ik Chee et al. Curr Ophthalmol Rep. 2018 Mar.

Abstract

Purpose of review: An update and overview of the literature on current telemedicine applications in retina.

Recent findings: The application of telemedicine to the field of Ophthalmology and Retina has been growing with advancing technologies in ophthalmic imaging. Retinal telemedicine has been most commonly applied to diabetic retinopathy and retinopathy of prematurity in adult and pediatric patients respectively. Telemedicine has the potential to alleviate the growing demand for clinical evaluation of retinal diseases. Subsequently, automated image analysis and deep learning systems may facilitate efficient processing of large, increasing numbers of images generated in telemedicine systems. Telemedicine may additionally improve access to education and standardized training through tele-education systems.

Summary: Telemedicine has the potential to be utilized as a useful adjunct but not a complete replacement for physical clinical examinations. Retinal telemedicine programs should be carefully and appropriately integrated into current clinical systems.

Keywords: Retina; deep learning; diabetic retinopathy; image analysis; retinopathy of prematurity; telemedicine.

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Conflict of interest statement

Conflict of Interest Ru-ik Chee, Dana Darwish, Alvaro Fernandez-Vega, Samir Patel, Karyn Jonas, Susan Ostmo, Peter Campbell, and R.V. Paul Chan declare no conflict of interest.

Figures

Figure 1
Figure 1
Image of plus disease processed by the Imaging and Informatics in Retinopathy of Prematurity (i-ROP) deep learning algorithm.
See this image and copyright information in PMC

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