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Proceedings Paper

Segmentation of ophthalmic optical coherence tomography images using graph cuts
Author(s): Xiao T. Li; Stephanie J. Chiu; Peter Nicholas; Cynthia A. Toth; Joseph A. Izatt; Sina Farsiu
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Paper Abstract

We describe an efficient approach for the automated segmentation of pathological/morphological structures in ophthalmic Spectral Domain Optical Coherence Tomography (SDOCT) images. In this algorithm, image pixels are treated as nodes of a graph with edge weights assigned to associate pairs of pixels. The weights vary according to the distances, brightness differences, and feature variations between pixel pairs. Cuts through the graph with minimum accumulated weights correspond to morphological layer boundaries. This approach has been applied to SDOCT images with encouraging results and thus forms an adaptable framework for the segmentation of many different ophthalmic structures.

Paper Details

Date Published: 2 March 2010
PDF: 8 pages
Proc. SPIE 7550, Ophthalmic Technologies XX, 75501O (2 March 2010); doi: 10.1117/12.842299
Show Author Affiliations
Xiao T. Li, Duke Univ. (United States)
Stephanie J. Chiu, Duke Univ. (United States)
Peter Nicholas, Duke Univ. Medical Ctr. (United States)
Cynthia A. Toth, Duke Univ. Medical Ctr. (United States)
Duke Univ. (United States)
Joseph A. Izatt, Duke Univ. (United States)
Duke Univ. Medical Ctr. (United States)
Sina Farsiu, Duke Univ. Medical Ctr. (United States)
Duke Univ. (United States)


Published in SPIE Proceedings Vol. 7550:
Ophthalmic Technologies XX
Fabrice Manns; Per G. Söderberg; Arthur Ho, Editor(s)

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