Retinal network characterization through fundus image processing: significant point identification on vessel centerline
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Morales Martínez, Sandra; Naranjo Ornedo, Valeriana; Angulo, Jesús; Legaz Aparicio, Alvar Ginés; Verdú Monedero, RafaelÁrea de conocimiento
Teoría de la Señal y las ComunicacionesPatrocinadores
This work was supported by the Ministerio de Economia y Competitividad Spain, Project ACRIMA (TIN2013-46751-R). The authors would like to thank people who provide the public databases used in this work (DRIVE, STARE and VARIA).Fecha de publicación
2017-03-23Editorial
ElsevierCita bibliográfica
Morales, S.; Naranjo Ornedo, V.; Angulo, J.; Legaz-Aparicio, A.; Verdu-Monedero, R. (2017). Retinal network characterization through fundus image processing: Significant point identification on vessel centerline. Signal Processing: Image Communication. 59:50-64. https://doi.org/10.1016/j.image.2017.03.013Palabras clave
Retinal skeletonVessel centerline
Significant points
Bifurcations
Crossings
Bifurcation angles
Resumen
This paper describes a new approach for significant point identification on vessel centerline. Significant points such as bifurcations and crossovers are able to define and characterize the retinal vascular network. In particular, hit-or-miss transformation is used to detect terminal, bifurcation and simple crossing points but a post-processing stage is needed to identify complex intersections. This stage focuses on the idea that the intersection of two vessels creates a sort of close loop formed by the vessels and this effect can be used to differentiate a bifurcation from a crossover. Experimental results show quantitative improvements by increasing the number of true positives and reducing the false positives and negatives in the significant point detection when the proposed method is compared with another state-of-the-art work. A sensitivity equal to 1 and a predictive positive value of 0.908 was achieved in the analyzed cases. Hit-or-miss transformation must be applied on a binary ...
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