Retina image analysis and ocular telehealth

the Oak Ridge National Laboratory-Hamilton Eye Institute case study

Thomas P. Karnowski, Luca Giancardo, Yaqin Li, Kenneth W. Tobin, Edward Chaum

Research output: Contribution to journalArticle

Abstract

Automated retina image analysis has reached a high level of maturity in recent years, and thus the question of how validation is performed in these systems is beginning to grow in importance. One application of retina image analysis is in telemedicine, where an automated system could enable the automated detection of diabetic retinopathy and other eye diseases as a low-cost method for broad-based screening. In this work, we discuss our experiences in developing a telemedical network for retina image analysis, including our progression from a manual diagnosis network to a more fully automated one. We pay special attention to how validations of our algorithm steps are performed, both using data from the telemedicine network and other public databases.

Original languageEnglish (US)
Pages (from-to)7140-7143
Number of pages4
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume2013
DOIs
StatePublished - 2013
Externally publishedYes

Fingerprint

Telemedicine
Image analysis
Retina
Eye Diseases
Diabetic Retinopathy
Screening
Databases
Costs and Cost Analysis
Costs

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Cite this

Retina image analysis and ocular telehealth : the Oak Ridge National Laboratory-Hamilton Eye Institute case study. / Karnowski, Thomas P.; Giancardo, Luca; Li, Yaqin; Tobin, Kenneth W.; Chaum, Edward.

In: Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, Vol. 2013, 2013, p. 7140-7143.

Research output: Contribution to journalArticle

@article{8ca197e11b374e8080c94d2a2ce6c2e2,
title = "Retina image analysis and ocular telehealth: the Oak Ridge National Laboratory-Hamilton Eye Institute case study",
abstract = "Automated retina image analysis has reached a high level of maturity in recent years, and thus the question of how validation is performed in these systems is beginning to grow in importance. One application of retina image analysis is in telemedicine, where an automated system could enable the automated detection of diabetic retinopathy and other eye diseases as a low-cost method for broad-based screening. In this work, we discuss our experiences in developing a telemedical network for retina image analysis, including our progression from a manual diagnosis network to a more fully automated one. We pay special attention to how validations of our algorithm steps are performed, both using data from the telemedicine network and other public databases.",
author = "Karnowski, {Thomas P.} and Luca Giancardo and Yaqin Li and Tobin, {Kenneth W.} and Edward Chaum",
year = "2013",
doi = "10.1109/EMBC.2013.6611204",
language = "English (US)",
volume = "2013",
pages = "7140--7143",
journal = "Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings",
issn = "1557-170X",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - JOUR

T1 - Retina image analysis and ocular telehealth

T2 - the Oak Ridge National Laboratory-Hamilton Eye Institute case study

AU - Karnowski, Thomas P.

AU - Giancardo, Luca

AU - Li, Yaqin

AU - Tobin, Kenneth W.

AU - Chaum, Edward

PY - 2013

Y1 - 2013

N2 - Automated retina image analysis has reached a high level of maturity in recent years, and thus the question of how validation is performed in these systems is beginning to grow in importance. One application of retina image analysis is in telemedicine, where an automated system could enable the automated detection of diabetic retinopathy and other eye diseases as a low-cost method for broad-based screening. In this work, we discuss our experiences in developing a telemedical network for retina image analysis, including our progression from a manual diagnosis network to a more fully automated one. We pay special attention to how validations of our algorithm steps are performed, both using data from the telemedicine network and other public databases.

AB - Automated retina image analysis has reached a high level of maturity in recent years, and thus the question of how validation is performed in these systems is beginning to grow in importance. One application of retina image analysis is in telemedicine, where an automated system could enable the automated detection of diabetic retinopathy and other eye diseases as a low-cost method for broad-based screening. In this work, we discuss our experiences in developing a telemedical network for retina image analysis, including our progression from a manual diagnosis network to a more fully automated one. We pay special attention to how validations of our algorithm steps are performed, both using data from the telemedicine network and other public databases.

UR - http://www.scopus.com/inward/record.url?scp=84941095051&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84941095051&partnerID=8YFLogxK

U2 - 10.1109/EMBC.2013.6611204

DO - 10.1109/EMBC.2013.6611204

M3 - Article

VL - 2013

SP - 7140

EP - 7143

JO - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

JF - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

SN - 1557-170X

ER -