Practical considerations for optic nerve location in telemedicine.
The projected increase in diabetes in the United States and worldwide has created a need for broad-based, inexpensive screening for diabetic retinopathy (DR), an eye disease which can lead to vision impairment. A telemedicine network with retina cameras and automated quality control, physiological feature location, and lesion / anomaly detection is a low-cost way of achieving broad-based screening. In this work we report on the effect of quality estimation on an optic nerve (ON) detection method with a confidence metric. We report on an improvement of the method using a data set from an ophthalmologist practice then show the results of the method as a function of image quality on a set of images from an on-line telemedicine network collected in Spring 2009 and another broad-based screening program. We show that the fusion method, combined with quality estimation processing, can improve detection performance and also provide a method for utilizing a physician-in-the-loop for images that may exceed the capabilities of automated processing.
Karnowski
T P
TP
Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA. karnowskitp@ornl.gov
Aykac
D
D
Chaum
E
E
Giancardo
L
L
Li
Y
Y
Tobin
K W
KW
Abramoff
M D
MD
D003930:Diabetic Retinopathy / Q000473:pathology*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D009900:Optic Nerve / Q000473:pathology*; D011873:Radiology Information Systems / Q000458:organization & administration*; D015203:Reproducibility of Results; D042262:Retinoscopy / Q000379:methods*; D012680:Sensitivity and Specificity; D017216:Telemedicine / Q000379:methods*