Automatic cone photoreceptor segmentation using graph theory and dynamic programming.

Published

Journal Article

Geometrical analysis of the photoreceptor mosaic can reveal subclinical ocular pathologies. In this paper, we describe a fully automatic algorithm to identify and segment photoreceptors in adaptive optics ophthalmoscope images of the photoreceptor mosaic. This method is an extension of our previously described closed contour segmentation framework based on graph theory and dynamic programming (GTDP). We validated the performance of the proposed algorithm by comparing it to the state-of-the-art technique on a large data set consisting of over 200,000 cones and posted the results online. We found that the GTDP method achieved a higher detection rate, decreasing the cone miss rate by over a factor of five.

Full Text

Duke Authors

Cited Authors

  • Chiu, SJ; Lokhnygina, Y; Dubis, AM; Dubra, A; Carroll, J; Izatt, JA; Farsiu, S

Published Date

  • June 2013

Published In

Volume / Issue

  • 4 / 6

Start / End Page

  • 924 - 937

PubMed ID

  • 23761854

Pubmed Central ID

  • 23761854

Electronic International Standard Serial Number (EISSN)

  • 2156-7085

International Standard Serial Number (ISSN)

  • 2156-7085

Digital Object Identifier (DOI)

  • 10.1364/BOE.4.000924

Language

  • eng