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Biomedical Optics Express

Biomedical Optics Express

  • Editor: Joseph A. Izatt
  • Vol. 4, Iss. 6 — Jun. 1, 2013
  • pp: 924–937

Automatic cone photoreceptor segmentation using graph theory and dynamic programming

Stephanie J. Chiu, Yuliya Lokhnygina, Adam M. Dubis, Alfredo Dubra, Joseph Carroll, Joseph A. Izatt, and Sina Farsiu  »View Author Affiliations


Biomedical Optics Express, Vol. 4, Issue 6, pp. 924-937 (2013)
http://dx.doi.org/10.1364/BOE.4.000924


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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.

© 2013 OSA

OCIS Codes
(100.0100) Image processing : Image processing
(170.4470) Medical optics and biotechnology : Ophthalmology
(110.1080) Imaging systems : Active or adaptive optics

ToC Category:
Image Processing

History
Original Manuscript: March 12, 2013
Revised Manuscript: May 13, 2013
Manuscript Accepted: May 17, 2013
Published: May 22, 2013

Citation
Stephanie J. Chiu, Yuliya Lokhnygina, Adam M. Dubis, Alfredo Dubra, Joseph Carroll, Joseph A. Izatt, and Sina Farsiu, "Automatic cone photoreceptor segmentation using graph theory and dynamic programming," Biomed. Opt. Express 4, 924-937 (2013)
http://www.opticsinfobase.org/boe/abstract.cfm?URI=boe-4-6-924


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