Automatic cone photoreceptor segmentation using graph theory and dynamic programming.
Published online
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 1, 2013
Published In
Volume / Issue
- 4 / 6
Start / End Page
- 924 - 937
PubMed ID
- 23761854
Pubmed Central ID
- 23761854
International Standard Serial Number (ISSN)
- 2156-7085
Digital Object Identifier (DOI)
- 10.1364/BOE.4.000924
Language
- eng
Conference Location
- United States