TY - GEN
T1 - Using a patient image archive to diagnose retinopathy
AU - Tobinlph, Kenneth W.
AU - Abramoff, Michael D.
AU - Chaum, Edward
AU - Giancardo, Luca
AU - Govindasamy, V. Priya
AU - Karnowski, Thomas P.
AU - Tennant, Matthew T.S.
AU - Swainson, Stephen
PY - 2008
Y1 - 2008
N2 - Diabetes has become an epidemic that is expected to impact 365 Million people worldwide by 2025. Consequently, diabetic retinopathy is the leading cause of blindness in the industrialized world today. If detected early, treatments can preserve vision and significantly reduce debilitating blindness. Through this research we are developing and testing a method for automating the diagnosis of retinopathy in a screening environment using a patient archive and digital fundus imagery. We present an overview of our content-based image retrieval (CBIR) approach and provide performance results for a dataset of 98 images from a study in Canada when compared to an archive of 1,355 patients from a study in the Netherlands. An aggregate performance of 89% correct diagnosis is achieved, demonstrating the potential of automated, web-based diagnosis for a broad range of imagery collected under different conditions and with different cameras.
AB - Diabetes has become an epidemic that is expected to impact 365 Million people worldwide by 2025. Consequently, diabetic retinopathy is the leading cause of blindness in the industrialized world today. If detected early, treatments can preserve vision and significantly reduce debilitating blindness. Through this research we are developing and testing a method for automating the diagnosis of retinopathy in a screening environment using a patient archive and digital fundus imagery. We present an overview of our content-based image retrieval (CBIR) approach and provide performance results for a dataset of 98 images from a study in Canada when compared to an archive of 1,355 patients from a study in the Netherlands. An aggregate performance of 89% correct diagnosis is achieved, demonstrating the potential of automated, web-based diagnosis for a broad range of imagery collected under different conditions and with different cameras.
UR - https://www.scopus.com/pages/publications/61849139034
M3 - Conference contribution
AN - SCOPUS:61849139034
SN - 9781424418152
T3 - Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"
SP - 5441
EP - 5444
BT - Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
T2 - 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
Y2 - 20 August 2008 through 25 August 2008
ER -