Automatic cone photoreceptor segmentation using graph theory and dynamic programming.

Alfredo Dubra // Publications // Jun 01 2013

PubMed ID: 23761854

Author(s): Chiu SJ, Lokhnygina Y, Dubis AM, Dubra A, Carroll J, Izatt JA, Farsiu S. Automatic cone photoreceptor segmentation using graph theory and dynamic programming. Biomed Opt Express. 2013 May 22;4(6):924-37. doi: 10.1364/BOE.4.000924. Print 2013 Jun 1. PMID 23761854

Journal: Biomedical Optics Express, Volume 4, Issue 6, Jun 2013

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.