This thesis contains the development of three different methodologies based on machine learning supervised approaches for the automatic assessment of retinal image quality. The objective is to compare their performances, strengths and drawbacks in order to understand which one is preferable for the embedding into an highly automated screening system.
Development of new techniques for the automatic assessment of retinal image quality
Gazzina, Silvia
2019/2020
Abstract
This thesis contains the development of three different methodologies based on machine learning supervised approaches for the automatic assessment of retinal image quality. The objective is to compare their performances, strengths and drawbacks in order to understand which one is preferable for the embedding into an highly automated screening system.File in questo prodotto:
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silvia_gazzina_tesi.pdf
Open Access dal 17/04/2022
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Utilizza questo identificativo per citare o creare un link a questo documento:
https://hdl.handle.net/20.500.12608/28928