@inproceedings{b3c0117c747c4d02acab8dbf6371c119,
title = "An automated image processing system for the detection of photoreceptor cells in adaptive optics retinal images",
abstract = "This paper presents an automated image processing framework for facilitating the accurate detection of photoreceptor cells. The performance of the proposed method was evaluated in terms of cone density calculated on synthetic and high-resolution retinal images. The validation study on the synthetic data showed an average accuracy of 98.8% for the proposed method in comparison with 93.9% obtained by the Li and Roorda algorithm. The cone density calculated on the high-resolution retinal images demonstrated satisfactory agreement with the histological data as well as previously published data on photoreceptor packing density at a given location.",
keywords = "Adaptive Optics retinal imaging, Image enhancement, Object detection, Photoreceptor cells",
author = "Anfisa Lazareva and Panos Liatsis and Rauscher, {Franziska G.}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 22nd International Conference on Systems, Signals and Image Processing, IWSSIP 2015 ; Conference date: 10-09-2015 Through 12-09-2015",
year = "2015",
month = oct,
day = "30",
doi = "10.1109/IWSSIP.2015.7314210",
language = "British English",
series = "2015 22nd International Conference on Systems, Signals and Image Processing - Proceedings of IWSSIP 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "196--199",
editor = "Shahjahan Miah and Alena Uus and Panos Liatsis",
booktitle = "2015 22nd International Conference on Systems, Signals and Image Processing - Proceedings of IWSSIP 2015",
address = "United States",
}