A supervised blood vessel segmentation technique for digital Fundus images using Zernike Moment based features

This paper proposes a new supervised method for blood vessel segmentation using Zernike moment-based shape descriptors. The method implements a pixel wise classification by computing a 11-D feature vector comprising of both statistical (gray-level) features and shape-based (Zernike moment) features....

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Detalles Bibliográficos
Autores principales: Adapa, Dharmateja, Joseph Raj, Alex Noel, Alisetti, Sai Nikhil, Zhuang, Zhemin, K., Ganesan, Naik, Ganesh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7059933/
https://www.ncbi.nlm.nih.gov/pubmed/32142540
http://dx.doi.org/10.1371/journal.pone.0229831

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7059933/
https://www.ncbi.nlm.nih.gov/pubmed/32142540
http://dx.doi.org/10.1371/journal.pone.0229831

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