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Proceedings Paper

Computer-aided methods for quantitative assessment of longitudinal changes in retinal images presenting with maculopathy
Author(s): Peter Soliz; Mark P. Wilson; Sheila Coyne Nemeth; Phong Nguyen
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Paper Abstract

This paper presents the results from applying a computer- based methodology for making precise measurements of longitudinal changes in a patient's digital retinal images presenting with age-related macular degeneration. The digital retinal image analysis system applies recognized principles in automatic image segmentation and integrates the automation with a graphical user interface. Drusen, retinal lesions associated with age-related macular degeneration (ARMD), were segmented using a region-growing algorithm. The algorithm calculates the 76 percentile intensity in a region to provide seed points for the neighborhood-growing algorithm. Twenty-one cases were analyzed. Agreement statistics (kappa) were determined by comparing the automated results with those provided from manually derived measurements. Agreement statistics ranged from 0.49 to 0.71 for different regions of the retina. The manual analysis ground truth was performed by trained graders from the University of Wisconsin Reading Center using guidelines found in the Wisconsin Age-Related Maculopathy Degeneration Grading Scheme (WARMGS). Because of the time required, the ophthalmic graders can only grade (size, area, type) the most prominent drusen in specific regions, resulting in a small sampling of drusen lesions in the retina. The computer-based approach allows one to efficiently and comprehensively grade all of the lesions for larger numbers of images. The additional advantage, however, is in the precision and total area that can be graded with the computer-aided technology. Computer-registered longitudinal images produced a precise determination of the temporal changes in the individual lesions. This study has demonstrated a robust segmentation and registration methodology for automatic and semiautomatic detection and measurement of abnormal regions in longitudinal retinal images.

Paper Details

Date Published: 17 May 2002
PDF: 12 pages
Proc. SPIE 4681, Medical Imaging 2002: Visualization, Image-Guided Procedures, and Display, (17 May 2002); doi: 10.1117/12.466917
Show Author Affiliations
Peter Soliz, Kestrel Corp. (United States)
Mark P. Wilson, Kestrel Corp. (United States)
Sheila Coyne Nemeth, Kestrel Corp. (United States)
Phong Nguyen, Kestrel Corp. (United States)

Published in SPIE Proceedings Vol. 4681:
Medical Imaging 2002: Visualization, Image-Guided Procedures, and Display
Seong Ki Mun, Editor(s)

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