Multi-objective Evolutionary-Fuzzy for Vessel Tortuosity Characterisation-Reference-Cited by-同舟云学术

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Multi-objective Evolutionary-Fuzzy for Vessel Tortuosity Characterisation

Published:2022-07-12 Issue: Volume: Page:581-588
ISSN:2367-3370
Container-title:Proceedings of Seventh International Congress on Information and Communication Technology
language:
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Author:

Mapayi Temitope,Owolawi Pius A.,Adio Adedayo O.

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-2394-4_53

Reference32 articles.

1. Aslani S, Sarnel H (2016) A new supervised retinal vessel segmentation method based on robust hybrid features. Biomed Sig Proc Cont 30:1–12

2. Bhuiyan A, Nath B, Ramamohanarao K, Kawasaki R, Wong TY (2012) Automated analysis of retinal vascular tortuosity on color retinal images. J Med Syst 36(2):689–697

3. Bribiesca E (2013) A measure of tortuosity based on chain coding. Pattern Recogn 46(3):716–724

4. Chakraborti T, Jha DK, Chowdhury AS, Jiang X (2014) A self-adaptive matched filter for retinal blood vessel detection. Mach Vis Appl 26(1):55–68

5. Chen Y (2017) A labeling-free approach to supervising deep neural networks for retinal blood vessel segmentation. arXiv preprint arXiv:1704.07502

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