Título:
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Network-based features for retinal fundus vessel structure analysis
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Autor/a:
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Amil Marletti, Pablo; Reyes Manzano, César F.; Guzmán Vargas, Lev; Sendiña, Irene; Masoller Alonso, Cristina
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Otros autores:
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Universitat Politècnica de Catalunya. Doctorat en Física Computacional i Aplicada; Universitat Politècnica de Catalunya. Departament de Física; Universitat Politècnica de Catalunya. DONLL - Dinàmica no Lineal, Òptica no Lineal i Làsers |
Abstract:
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Retinal fundus imaging is a non-invasive method that allows visualizing the structure of the blood vessels in the retina whose features may indicate the presence of diseases such as diabetic retinopathy (DR) and glaucoma. Here we present a novel method to analyze and quantify changes in the retinal blood vessel structure in patients diagnosed with glaucoma or with DR. First, we use an automatic unsupervised segmentation algorithm to extract a tree-like graph from the retina blood vessel structure. The nodes of the graph represent branching (bifurcation) points and endpoints, while the links represent vessel segments that connect the nodes. Then, we quantify structural differences between the graphs extracted from the groups of healthy and non-healthy patients. We also use fractal analysis to characterize the extracted graphs. Applying these techniques to three retina fundus image databases we find significant differences between the healthy and non-healthy groups (p-values lower than 0.005 or 0.001 depending on the method and on the database). The results are sensitive to the segmentation method (manual or automatic) and to the resolution of the images. |
Abstract:
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Peer Reviewed |
Materia(s):
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-Àrees temàtiques de la UPC::Física -Fundus oculi -Algorithms -Fons de l'ull -Algorismes de segmentació -Algorismes -- Simulació per ordinador |
Derechos:
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Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
Tipo de documento:
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Artículo - Versión publicada Artículo |
Editor:
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Public Library of Science (PLOS)
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