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Title: Detection of Anatomic Structures in Human Retinal Imagery

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.

Authors:
 [1];  [1];  [1];  [1]
  1. ORNL
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
962599
DOE Contract Number:  
DE-AC05-00OR22725
Resource Type:
Journal Article
Resource Relation:
Journal Name: IEEE Transactions on Medical Imaging; Journal Volume: 26; Journal Issue: 12
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; RETINA; DISEASES; IMAGE PROCESSING; PERFORMANCE; DATA ANALYSIS; DETECTION; diabetic retinopathy; red-free fundus imagery; vascular segmentation; optic nerve detection; macula localization; feature analysis; Bayesian classifier

Citation Formats

Tobin Jr, Kenneth William, Chaum, Edward, Muthusamy Govindasamy, Vijaya Priya, and Karnowski, Thomas Paul. Detection of Anatomic Structures in Human Retinal Imagery. United States: N. p., 2007. Web. doi:10.1109/TMI.2007.902801.
Tobin Jr, Kenneth William, Chaum, Edward, Muthusamy Govindasamy, Vijaya Priya, & Karnowski, Thomas Paul. Detection of Anatomic Structures in Human Retinal Imagery. United States. doi:10.1109/TMI.2007.902801.
Tobin Jr, Kenneth William, Chaum, Edward, Muthusamy Govindasamy, Vijaya Priya, and Karnowski, Thomas Paul. Mon . "Detection of Anatomic Structures in Human Retinal Imagery". United States. doi:10.1109/TMI.2007.902801.
@article{osti_962599,
title = {Detection of Anatomic Structures in Human Retinal Imagery},
author = {Tobin Jr, Kenneth William and Chaum, Edward and Muthusamy Govindasamy, Vijaya Priya and Karnowski, Thomas Paul},
abstractNote = {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.},
doi = {10.1109/TMI.2007.902801},
journal = {IEEE Transactions on Medical Imaging},
number = 12,
volume = 26,
place = {United States},
year = {Mon Jan 01 00:00:00 EST 2007},
month = {Mon Jan 01 00:00:00 EST 2007}
}