skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

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}
}
  • Highlights: •UVB irradiation induces RPE autophagy. •EGCG treatment represses UVB-mediated autophagy. •EGCG regulates UVB-mediated autophagy through mTOR signaling pathway. •EGCG sensitizes RPE cells to UVB-induced damage in an autophagy-dependent manner. -- Abstract: Autophagy is an intracellular catabolic process involved in protein and organelle degradation via the lysosomal pathway that has been linked in the pathogenesis of age-related macular degeneration (AMD). UVB irradiation-mediated degeneration of the macular retinal pigment epithelial (RPE) cells is an important hallmark of AMD, which is along with the change in RPE autophagy. Thus, pharmacological manipulation of RPE autophagy may offer an alternative therapeutic target in AMD.more » Here, we found that epigallocatechin-3-gallate (EGCG), a polyphenolic compound from green tea, plays a regulatory role in UVB irradiation-induced autophagy in RPE cells. UVB irradiation results in a marked increase in the amount of LC3-II protein in a dose-dependent manner. EGCG administration leads to a significant reduction in the formation of LC3-II and autophagosomes. mTOR signaling activation is required for EGCG-induced LC3-II formation, as evidenced by the fact that EGCG-induced LC3-II formation is significantly impaired by rapamycin administration. Moreover, EGCG significantly alleviates the toxic effects of UVB irradiation on RPE cells in an autophagy-dependent manner. Collectively, our study reveals a novel role of EGCG in RPE autophagy. EGCG may be exploited as a potential therapeutic reagent for the treatment of pathological conditions associated with abnormal autophagy.« less
  • Delayed clearance of free form all-trans-retinal (atRAL) is estimated be the key cause of retinal pigment epithelium (RPE) cells injury during the pathogenesis of retinopathies such as age-related macular degeneration (AMD), however, the underlying molecular mechanisms are far from clear. In this study, we investigated the cytotoxicity effect and underlying molecular mechanism of atRAL on human retinal pigment epithelium ARPE-19 cells. The results indicated that atRAL could cause cell dysfunction by inducing oxidative and nitrosative stresses in ARPE-19 cells. The oxidative stress induced by atRAL was mediated through up-regulation of reactive oxygen species (ROS) generation, activating mitochondrial-dependent and MAPKs signalingmore » pathways, and finally resulting in apoptosis of ARPE-19 cells. The NADPH oxidase inhibitor apocynin could partly attenuated ROS generation, indicating that NADPH oxidase activity was involved in atRAL-induced oxidative stress in ARPE-19 cells. The nitrosative stress induced by atRAL was mainly reflected in increasing nitric oxide (NO) production, enhancing iNOS, ICAM-1 and VCAM-1 expressions, and promoting monocyte adhesion. Furthermore, above effects could be dramatically blocked by using a nuclear factor kappa B (NF-κB) inhibitor SN50, indicated that atRAL-induced oxidative and nitrosative stresses were mediated by NF-κB. The results provide better understanding of atRAL-induced toxicity in human RPE cells. - Highlights: • atRAL induces oxidative stress-mediated apoptosis in ARPE-19 cells. • atRAL induces oxidative stress-mediated inflammation in ARPE-19 cells. • NF-κB is involved in atRAL-induced oxidative and nitrosative stresses.« less
  • Growth activity in different areas of human septal cartilage was measured by the in vitro incorporation of /sup 35/S-labeled NaSO/sub 4/ into chondroitin sulfate. Septal cartilage without perichondrium was obtained during rhinoplasty from 36 patients aged 6 to 35 years. It could be shown that the anterior free end of the septum displays high growth activity in all age groups. The supra-premaxillary area displayed its highest growth activity during prepuberty, showing thereafter a continuous decline during puberty and adulthood. A similar age-dependent pattern in growth activity was found in the caudal prolongation of the septal cartilage. No age-dependent variations couldmore » be detected in the posterior area of the septal cartilage.« less
  • Purpose: To develop a novel statistics-based method for automated detection of anatomical changes using cone-beam CT data. A method was developed that can provide a reliable and automated early warning system that enables a “just-in-time” adaptation of the treatment plan. Methods: Anatomical changes were evaluated by comparing the original treatment planning CT with daily CBCT images taken prior treatment delivery. The external body contour was computed on a given CT slice and compared against the corresponding contour on the daily CBCT. In contrast to threshold-based techniques, a statistical approach was employed to evaluate the difference between the contours using amore » given confidence level. The detection tool used the two-sample Kolmogorov-Smirnov test, which is a non-parametric technique that compares two samples drawn from arbitrary probability distributions. 11 H'N patients were retrospectively selected from a clinical imaging database with a total of 186 CBCT images. Six patients in the database were confirmed to have anatomic changes during the course of radiotherapy. Five of the H'N patients did not have significant changes. The KS test was applied to the contour data using a sliding window analysis. The confidence level of 0.99 was used to moderate false detection. Results: The algorithm was able to correctly detect anatomical changes in 6 out of 6 patients with an excellent spatial accuracy as early as at the 14th elapsed day. The algorithm provided a consistent and accurate delineation of the detected changes. The output of the anatomical change tool is easy interpretable, and can be shown overlaid on a 3D rendering of the patient's anatomy. Conclusion: The detection method provides the basis for one of the key components of Adaptive Radiation Therapy. The method uses tools that are readily available in the clinic, including daily CBCT imaging, and image co-registration facilities.« less