@inproceedings{5e2cab6e39b64e66a102a37df9348497,
title = "Similarity evaluation of retinal vascular network based on tree edit distance",
abstract = "The similarity of retinal vascular networks has important applications in the early diagnosis, prediction, and treatment of retinal diseases, such as diabetic retinopathy and age-related macular degeneration (AMD). Unlike direct comparison of vascular parameters or vessel segmentation pixels, a method for calculating the distance between vascular networks based on the tree edit distance is proposed in this paper to represent the similarity between vascular networks. We model the retinal vessel as a tree structure and calculate the tree edit distance between vessel trees which is sensitive to geometrical and topological changes of vessels. Since the retinal vascular network is composed of multiple vessel trees, we weight the distance between vessels and sum them up to represent the distance between networks. The smaller the distance, the higher the network similarity. Finally, experimental results verify that our proposed network distance algorithm can evaluate the similarity between networks objectively.",
keywords = "retinal vascular network similarity, retinal vessel tree, tree edit distance",
author = "Wenjian Li and Guannan Wu and Huiqi Li",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023 ; Conference date: 18-08-2023 Through 22-08-2023",
year = "2023",
doi = "10.1109/ICIEA58696.2023.10241828",
language = "English",
series = "Proceedings of the 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "722--727",
editor = "Wenjian Cai and Guilin Yang and Jun Qiu and Tingting Gao and Lijun Jiang and Tianjiang Zheng and Xinli Wang",
booktitle = "Proceedings of the 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023",
address = "United States",
}
