DocumentCode :
946649
Title :
Detection of Anatomic Structures in Human Retinal Imagery
Author :
Tobin, Kenneth W. ; Chaum, Edward ; Govindasamy, V.P. ; Karnowski, T.P.
Author_Institution :
Oak Ridge Nat. Lab., Oak Ridge
Volume :
26
Issue :
12
fYear :
2007
Firstpage :
1729
Lastpage :
1739
Abstract :
The widespread availability of electronic imaging devices throughout the medical community is leading to a growing body of research on image processing and analysis to diagnose retinal disease such as diabetic retinopathy (DR). Productive computer-based screening of large, at-risk populations at low cost requires robust, automated image analysis. In this paper we present results for the automatic detection of the optic nerve and localization of the macula using digital red-free fundus photography. Our method relies on the accurate segmentation of the vasculature of the retina followed by the determination of spatial features describing the density, average thickness, and average orientation of the vasculature in relation to the position of the optic nerve. Localization of the macula follows using knowledge of the optic nerve location to detect the horizontal raphe of the retina using a geometric model of the vasculature. We report 90.4% detection performance for the optic nerve and 92.5% localization performance for the macula for red-free fundus images representing a population of 345 images corresponding to 269 patients with 18 different pathologies associated with DR and other common retinal diseases such as age-related macular degeneration.
Keywords :
biomedical optical imaging; diseases; eye; feature extraction; image segmentation; medical image processing; photography; IEEE electronic imaging devices; anatomic structures; automated image analysis; automatic detection; computer-based screening; diabetic retinopathy; digital fundus photography; human retinal imagery; image processing; macula localization; optic nerve; red-free fundus photography; retina; retinal disease diagnosis; vasculature segmentation; Bayesian classifier; diabetic retinopathy; feature analysis; macula localization; optic nerve detection; red-free fundus imagery; vascular segmentation; Algorithms; Artificial Intelligence; Fluorescein Angiography; Fundus Oculi; Humans; Image Interpretation, Computer-Assisted; Image Processing, Computer-Assisted; Macula Lutea; Optic Nerve; Pattern Recognition, Automated; Photography; Retina; Retinal Diseases; Retinal Vessels; Sensitivity and Specificity;
fLanguage :
English
Journal_Title :
Medical Imaging, IEEE Transactions on
Publisher :
ieee
ISSN :
0278-0062
Type :
jour
DOI :
10.1109/TMI.2007.902801
Filename :
4359034
Link To Document :
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