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Automatic estimation of endothelium cell density in donor corneas by means of Fourier analysis
No full textOne of the main clinical parameters expressing the health of a cornea is
the cell density of its endothelium. This information is particularly important in an
eye bank environment, where donor corneas are screened to assess their suitability
as a human graft. Endothelium cell density is conventionally estimated by a long,
tedious and error-prone manual counting procedure, performed by cornea experts
on specimen images observed through an optical microscope. An alternative solution
is proposed: a computer program that provides automatic estimation of cell
density in donor corneas by analysing the spatial frequencies contained in the
image. A circular band in the 2D discrete Fourier transform of the image is shown
to contain the relevant information about the cell density. A system for extracting
from this spatial frequency information an estimate of the cell density has been
developed. A clinical evaluation of the proposed technique was performed on 18
corneas, where the densities provided by the proposed technique were compared
with those manually obtained by two experts. The results showed an average
percentage difference of 3% (maximum 19%), a value well within the measured
inter-expert range of variability. The proposed automatic procedure confirmed its
ability to estimate correctly corneal endothelium cell density
Detecting the optic disc in retinal images by means of a geometrical model of vessel network
No full textDetection of vessel caliber irregularities in color retinal fundus images by means of fine tracking
No full textDetection of optic disc in retinal images by means of a geometrical model of vessel structure
Full text linkWe present here a new method to identify the position
of the optic disc (OD) in retinal fundus images. The method is
based on the preliminary detection of the main retinal vessels. All
retinal vessels originate from the OD and their path follows a similar
directional pattern (parabolic course) in all images. To describe
the general direction of retinal vessels at any given position in the
image, a geometrical parametric model was proposed, where two of
the model parameters are the coordinates of the OD center. Using
as experimental data samples of vessel centerline points and corresponding
vessel directions, provided by any vessel identification
procedure, model parameters were identified by means of a simulated
annealing optimization technique. These estimated values
provide the coordinates of the center of OD. A Matlab® prototype
implementing this method was developed. An evaluation of the proposed
procedure was performed using the set of 81 images from the
STARE project, containing images from both normal and pathological
subjects. The OD position was correctly identified in 79 out
of 81 images (98%), even in rather difficult pathological situations
A model of the retinal vessel network as a tool to detect the position of optic disc in fundus images
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