Segmentation of ophthalmic optical coherence tomography images using graph cuts

Xiao T. Li; Stephanie J. Chiu; Peter Nicholas; Cynthia A. Toth; Joseph A. Izatt; Sina Farsiu

doi:10.1117/12.842299

2 March 2010 Segmentation of ophthalmic optical coherence tomography images using graph cuts

Xiao T. Li, Stephanie J. Chiu, Peter Nicholas, Cynthia A. Toth, Joseph A. Izatt, Sina Farsiu

Proceedings Volume 7550, Ophthalmic Technologies XX; 75501O (2010) https://doi.org/10.1117/12.842299
Event: SPIE BiOS, 2010, San Francisco, California, United States

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.

Citation Download Citation

Xiao T. Li, Stephanie J. Chiu, Peter Nicholas, Cynthia A. Toth, Joseph A. Izatt, and Sina Farsiu "Segmentation of ophthalmic optical coherence tomography images using graph cuts", Proc. SPIE 7550, Ophthalmic Technologies XX, 75501O (2 March 2010); https://doi.org/10.1117/12.842299

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KEYWORDS

Image segmentation

Image processing algorithms and systems

Optical coherence tomography

Image processing

3D image processing

Americium

Ophthalmology

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