Abstract
In this paper, we provide a study on eye fundus images of healthy and diabetic patients. Taking benefits from its reconstruction and enhancing properties, the sampling Kantorovich algorithm is used to process the considered images, after registration and averaging processes. Moreover, a hybrid segmentation procedure applied on superficial capillary plexus images (SCP) and one using the local Phansalkar method on choriocapillary images (CC) are exploited in order to asses a cluster counting process which is based on finding connected regions according to the 8–adjacency criterion. The results achieved on the healthy and diabetic patients show that the novel strategy allows to obtain accurate data from both a mathematical and a clinical point of view.
A. Travaglini and G. Vinti have been partially supported within the 2022 GNAMPA-INdAM Project “Enhancement e segmentazione di immagini mediante operatori di tipo campionamento e metodi variazionali per lo studio di applicazioni biomediche” and G. Vinti within the projects Ricerca di Base 2019 dell’Università degli Studi di Perugia— “Integrazione, Approssimazione, Analisi Nonlineare e loro Applicazioni” and “Innovation, digitalisation and sustainability for the diffused economy in Central Italy - VITALITY (proposal identification code n. ECS_00000041)”.
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Acknowledgements
The authors wish to thank prof. C. Cagini and prof. M. Lupidi of the Ophthalmology Section of the Department of Medicine and Surgery of the University of Perugia for having kindly provided the images used in this work.
Moreover, A. Travaglini and G. Vinti are members of the Gruppo Nazionale per l’Analisi Matematica, la Probabilitá e le loro Applicazioni (GNAMPA) of the Istituto Nazionale di Alta Matematica (INdAM), of the network RITA (Research ITalian network on Approximation) and of the UMI group “Teoria dell’Approssimazione e Applicazioni.”
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Travaglini, A., Vinti, G. (2023). A Mathematical Model for the Analysis of Eye Fundus Images in Healthy and Diabetic Patients. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2023 Workshops. ICCSA 2023. Lecture Notes in Computer Science, vol 14108. Springer, Cham. https://doi.org/10.1007/978-3-031-37117-2_38
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