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• W206112009 abstract "This thesis deals with the automatic analysis of confocal images of the cornea, and with the automatic estimation of clinical parameters.Corneal diseases and dystrophies (dry-eye, keratoconus, conjunctivitis, herpes keratitis, lattice dystrophy, etc.) affect vision in widely differing ways. Some cause severe visual impairment, while a few cause no vision problems and are discovered during an eye examination. Other dystrophies may cause repeated episodes of pain without leading to permanent loss of vision. Corneal structures are very sensitive to corneal pathologies: nerve fibers, keratocytes, endothelial cells change their morphology. Changes in the morphology of corneal structures are also related to age or prolonged contact lens wear, to surgical interventions on cornea, such as LASIK or PRK, or to transplantation.In vivo confocal microscopy of the cornea allows to acquire in a rapid and non-invasive way images of the various corneal layers and structures. Analyzing these images has been shown to be quite important to provide clinical information on the cornea state of health. At present, all the analyses of corneal structures are based on manual or semi-automatic methods, and thus the derived clinical parameter values are subjective and error prone.Thus, a reliable automatic tool for evaluating corneal pathologies is strongly needed. Every automatic method for analyzing the cornea must go through some well defined steps. First, it has to detect the main anatomical structures of the cornea: nerve fibers, keratocytes and endothelial cells. Then it has to quantitatively measure the identified structures. Finally, it has to estimate the parameters of clinical interest.In this thesis a new algorithm to extract the nerve fibers will be described. Density and morphology of nerve fibers are correlated to corneal pathologies. Then a method for visualizing all corneal structures in the 3D volume will be presented. Keratocytes volumetric density is an important clinical parameter: an algorithm for the automatic recognition of keratocytes in the 3D volume and for the estimation of the volumetric density has been developed. Finally, an algorithm for the automatic endothelial cell contour detection and the estimation of cells density and morphology will be described.The algorithms presented in this thesis make it possible to conceive a tool to be used for the automatic analyses of the cornea. It will allow to obtain a quantitative and reproducible description of the whole cornea and specific details of the individual structures. It shall provide a diagnostic tool to aid the clinical practice." @default.
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• W206112009 date "2008-01-01" @default.
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• W206112009 title "Automatyc analysis of confocal images of the cornea" @default.
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