An automated algorithm for photoreceptors counting in adaptive optics retinal images

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 8419, Issue , 2012, Pages

  Liu, Xu ^a,b,c   Zhang, Yudong ^a,b   Dai, Yun ^a,b  

^a INSTITUTE OF OPTICS AND ELECTRONICS   (China)

^b INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

^c UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

Author keywords

Adaptive optics; Automated; Cone photoreceptor; Count

Indexed keywords

AUTOMATED; AUTOMATED ALGORITHMS; CONE PHOTORECEPTORS; COUNT; EYE DISEASE; LARGE-SCALE DATUM; REAL TIME; RETINAL IMAGE;

ADAPTIVE OPTICS; AUTOMATION; COLOR VISION; MANUFACTURE; OPHTHALMOLOGY; OPTOELECTRONIC DEVICES; TESTING;

ALGORITHMS;

EID: 84875490306     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.975947     Document Type: Conference Paper

References (7)

1. J. Liang, D. R. Williams and D. T. Miller. Supernormal vision and high-resolution retinal imaging through adaptive optics [J]. Opt. Soc. Am. A, 1997, 14: 2884-2892.
2. A. Roorda and D. R. Williams. The arrangement of the three cone classes in the living human eye [J]. Nature, 1999, 397: 520-522.
3. A. Roorda, A. B. Metha, P. Lennie and D. R. Williams. Packing arrangement of the three cone classes in primate retina [J]. Vision Res, 2001, 41: 1291-1306.
4. H. Hofer, J. Carroll, J. Neitz, M. Neitz and D. R. Williams. Organization of the human trichromatic cone mosaic [J]. The Journal of Neuroscience, 2005, 25: 9669-9679.
5. K. Y. Li and A. Roorda. Intersubject variability of foveal cone photoreceptor density in relation to eye length [J]. IOVS, 2010, 51: 6858-6867.
6. K. Y. Li and A. Roorda. Automated identification of cone photoreceptors in adaptive optics retinal images [J]. Opt. Soc. Am. A, 2007, 24: 1358-1363.
7. H. Bao. Methods Research on Enhancing Retinal Cell Image Quality [D]. Chengdu: Sichuan University, 2010.