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

Published

Journal Article

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.

Full Text

Duke Authors

Cited Authors

  • Chiu, SJ; Toth, CA; Bowes Rickman, C; Izatt, JA; Farsiu, S

Published Date

  • May 2012

Published In

Volume / Issue

  • 3 / 5

Start / End Page

  • 1127 - 1140

PubMed ID

  • 22567602

Pubmed Central ID

  • 22567602

Electronic International Standard Serial Number (EISSN)

  • 2156-7085

International Standard Serial Number (ISSN)

  • 2156-7085

Digital Object Identifier (DOI)

  • 10.1364/BOE.3.001127

Language

  • eng