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Biomedical Optics Express

Biomedical Optics Express

  • Editor: Joseph A. Izatt
  • Vol. 3, Iss. 5 — May. 1, 2012
  • pp: 1127–1140

Automatic segmentation of closed-contour features in ophthalmic images using graph theory and dynamic programming

Stephanie J. Chiu, Cynthia A. Toth, Catherine Bowes Rickman, Joseph A. Izatt, and Sina Farsiu  »View Author Affiliations

Biomedical Optics Express, Vol. 3, Issue 5, pp. 1127-1140 (2012)

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This paper presents a generalized framework for segmenting closed-contour anatomical and pathological features using graph theory and dynamic programming (GTDP). More specifically, the GTDP method previously developed for quantifying retinal and corneal layer thicknesses is extended to segment objects such as cells and cysts. The presented technique relies on a transform that maps closed-contour features in the Cartesian domain into lines in the quasi-polar domain. The features of interest are then segmented as layers via GTDP. Application of this method to segment closed-contour features in several ophthalmic image types is shown. Quantitative validation experiments for retinal pigmented epithelium cell segmentation in confocal fluorescence microscopy images attests to the accuracy of the presented technique.

© 2012 OSA

OCIS Codes
(100.0100) Image processing : Image processing
(170.4470) Medical optics and biotechnology : Ophthalmology

ToC Category:
Image Processing

Original Manuscript: March 21, 2012
Revised Manuscript: April 24, 2012
Manuscript Accepted: April 25, 2012
Published: April 26, 2012

Stephanie J. Chiu, Cynthia A. Toth, Catherine Bowes Rickman, Joseph A. Izatt, and Sina Farsiu, "Automatic segmentation of closed-contour features in ophthalmic images using graph theory and dynamic programming," Biomed. Opt. Express 3, 1127-1140 (2012)

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