@inproceedings{5e72e97b9b8342f881d7c58fdbf765f2,
title = "Automatic detection of arteriovenous nicking in retinal images",
abstract = "Morphological changes of retinal vessels such as arteriovenous (AV) nicking are signs of many systemic diseases. In this paper, an automatic method for AV-nicking detection is proposed. The proposed method includes crossover point detection and AV-nicking identification. Vessel segmentation, vessel thinning, and feature point recognition are performed to detect crossover point. A method of vessel diameter measurement is proposed with processing of removing voids, hidden vessels and micro-vessels in segmentation. The AV-nicking is detected based on the features of vessel diameter measurement. The proposed algorithms have been tested using clinical images. The results show that nicking points in retinal images can be detected successfully in most cases.",
keywords = "arteriovenous nicking detection, retinal image",
author = "Jieliang Kang and Zhiyang Ma and Huiqi Li and Liang Xu and Li Zhang",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 11th IEEE Conference on Industrial Electronics and Applications, ICIEA 2016 ; Conference date: 05-06-2016 Through 07-06-2016",
year = "2016",
month = oct,
day = "19",
doi = "10.1109/ICIEA.2016.7603690",
language = "English",
series = "Proceedings of the 2016 IEEE 11th Conference on Industrial Electronics and Applications, ICIEA 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "795--800",
booktitle = "Proceedings of the 2016 IEEE 11th Conference on Industrial Electronics and Applications, ICIEA 2016",
address = "United States",
}
