title: Automatic cone photoreceptor segmentation using graph theory and dynamic programming.
abstract: 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.
authors.affiliation: Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708, USA.
authors.forename: Stephanie J
authors.initials: SJ
authors.lastname: Chiu
authors.forename: Yuliya
authors.initials: Y
authors.lastname: Lokhnygina
authors.forename: Adam M
authors.initials: AM
authors.lastname: Dubis
authors.forename: Alfredo
authors.initials: A
authors.lastname: Dubra
authors.forename: Joseph
authors.initials: J
authors.lastname: Carroll
authors.forename: Joseph A
authors.initials: JA
authors.lastname: Izatt
authors.forename: Sina
authors.initials: S
authors.lastname: Farsiu
keywords: (100.0100) Image processing; (110.1080) Active or adaptive optics; (170.4470) Ophthalmology