Automatic generation of synthetic retinal fundus images: Vascular network

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Abstract

This work is part of an ongoing project aimed to generate synthetic retinal fundus images. This paper concentrates on the generation of synthetic vascular networks with realistic shape and texture characteristics. An example-based method, the Active Shape Model, is used to synthesize reliable vessels’ shapes. An approach based on Kalman Filtering combined with an extension of a Multiresolution Hermite vascular cross-section model has been developed for the simulation of vessels’ textures. The proposed method is able to generate realistic synthetic vascular networks with morphological properties that guarantee the correct flow of the blood and the oxygenation of the retinal surface as observed with fundus cameras. The validity of our synthetic retinal images is demonstrated by qualitative assessment and quantitative analysis.

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Menti, E., Bonaldi, L., Ballerini, L., Ruggeri, A., & Trucco, E. (2016). Automatic generation of synthetic retinal fundus images: Vascular network. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9968 LNCS, pp. 167–176). Springer Verlag. https://doi.org/10.1007/978-3-319-46630-9_17

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