NDLI: Automatic detection of retina disease: Robustness to image quality and localization of anatomy structure

Content Provider	IEEE Xplore Digital Library
Author	Karnowski, T.P. Aykac, D. Giancardo, L. Li, Y. Nichols, T. Tobin, K.W. Chaum, E.
Copyright Year	2011
Description	Author affiliation: University of Tennessee Health Science Center, 930 Madison Avenue, Suite 731, Memphis TN 38163 (Li, Y.; Chaum, E.) \|\| Oak Ridge National Laboratory, Oak Ridge, TN 37831 USA (Karnowski, T.P.; Aykac, D.; Giancardo, L.; Nichols, T.; Tobin, K.W.)
Abstract	The automated detection of diabetic retinopathy and other eye diseases in images of the retina has great promise as a low-cost method for broad-based screening. Many systems in the literature which perform automated detection include a quality estimation step and physiological feature detection, including the vascular tree and the optic nerve / macula location. In this work, we study the robustness of an automated disease detection method with respect to the accuracy of the optic nerve location and the quality of the images obtained as judged by a quality estimation algorithm. The detection algorithm features microaneurysm and exudate detection followed by feature extraction on the detected population to describe the overall retina image. Labeled images of retinas ground-truthed to disease states are used to train a supervised learning algorithm to identify the disease state of the retina image and exam set. Under the restrictions of high confidence optic nerve detections and good quality imagery, the system achieves a sensitivity and specificity of 94.8% and 78.7% with area-under-curve of 95.3%. Analysis of the effect of constraining quality and the distinction between mild non-proliferative diabetic retinopathy, normal retina images, and more severe disease states is included.
Starting Page	5959
Ending Page	5964
File Size	1815433
Page Count	6
File Format	PDF
ISBN	9781424441211
ISSN	1557170X
e-ISBN	9781457715891
e-ISBN	9781424441228
DOI	10.1109/IEMBS.2011.6091473
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-08-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Optical imaging Diseases Optical filters Retina Lesions Adaptive optics Training
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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