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Abstract #82088 Published in IGR 20-4
Network-based features for retinal fundus vessel structure analysis
Amil P; Reyes-Manzano CF; Guzmán-Vargas L; Sendiña-Nadal I; Masoller CPLoS ONE 2019; 14: e0220132
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.
Nonlinear Dynamics, Nonlinear Optics and Lasers, Universitat Politècnica de Catalunya, Terrassa, Spain.
Full articleClassification:
6.9.5 Other (Part of: 6 Clinical examination methods > 6.9 Computerized image analysis)
6.30 Other (Part of: 6 Clinical examination methods)
6.11 Bloodflow measurements (Part of: 6 Clinical examination methods)
2.13 Retina and retinal nerve fibre layer (Part of: 2 Anatomical structures in glaucoma)
