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Proceedings Paper

An automated algorithm for photoreceptors counting in adaptive optics retinal images
Author(s): Xu Liu; Yudong Zhang; Dai Yun
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Paper Abstract

Eyes are important organs of humans that detect light and form spatial and color vision. Knowing the exact number of cones in retinal image has great importance in helping us understand the mechanism of eyes’ function and the pathology of some eye disease. In order to analyze data in real time and process large-scale data, an automated algorithm is designed to label cone photoreceptors in adaptive optics (AO) retinal images. Images acquired by the flood-illuminated AO system are taken to test the efficiency of this algorithm. We labeled these images both automatically and manually, and compared the results of the two methods. A 94.1% to 96.5% agreement rate between the two methods is achieved in this experiment, which demonstrated the reliability and efficiency of the algorithm.

Paper Details

Date Published: 15 October 2012
PDF: 5 pages
Proc. SPIE 8419, 6th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optoelectronic Materials and Devices for Sensing, Imaging, and Solar Energy, 84191Z (15 October 2012); doi: 10.1117/12.975947
Show Author Affiliations
Xu Liu, Institute of Optics and Electronics (China)
Key Lab. on Adaptive Optics (China)
Graduate Univ. of Chinese Academy of Sciences (China)
Yudong Zhang, Institute of Optics and Electronics (China)
Key Lab. on Adaptive Optics (China)
Dai Yun, Institute of Optics and Electronics (China)
Key Lab. on Adaptive Optics (China)


Published in SPIE Proceedings Vol. 8419:
6th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optoelectronic Materials and Devices for Sensing, Imaging, and Solar Energy
Yadong Jiang; Junsheng Yu; Zhifeng Wang, Editor(s)

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