Abstract
The application of computer-based imaging algorithms to the diagnosis of human disease is already a reality, used routinely today in radiology, mammography, and pathology [1–3]. Recent advances in the imaging of the eye, in particular nonmydriatic and cross-sectional images of the retina, now provide high-quality digital data to diagnose and quantify features of many diseases, including diabetic retinopathy (DR). The potential of these imaging methods is clear. New computer-based systems and diagnostic algorithms hold the promise of producing low-cost, potentially automated, diagnostic imaging systems for managing diseases like DR on a societal scale.
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Acknowledgments
These studies were supported in part by grants from Oak Ridge National Laboratory, the National Eye Institute, (EY017065), and the Health Resources and Services Administration, by an unrestricted UTHSC departmental grant from Research to Prevent Blindness, New York, NY and by the Plough Foundation, Memphis, TN.
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Karnowski, T.P., Li, Y., Giancardo, L., Aykac, D., Tobin, K.W., Chaum, E. (2012). Automated Image Analysis and the Application of Diagnostic Algorithms in an Ocular Telehealth Network. In: Yogesan, K., Goldschmidt, L., Cuadros, J. (eds) Digital Teleretinal Screening. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25810-7_5
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