The corneal endothelium serves as the posterior barrier of the cornea. Factors such as clarity and refractive properties of
the cornea are in direct relationship to the quality of the endothelium. The endothelial cell density is considered the most
important morphological factor of the corneal endothelium. Pathological conditions and physical trauma may threaten
the endothelial cell density to such an extent that the optical property of the cornea and thus clear eyesight is threatened.
Diagnosis of the corneal endothelium through morphometry is an important part of several clinical applications.
Morphometry of the corneal endothelium is presently carried out by semi automated analysis of pictures captured by a
Clinical Specular Microscope (CSM). Because of the occasional need of operator involvement, this process can be
tedious, having a negative impact on sampling size. This study was dedicated to the development and use of fully
automated analysis of a very large range of images of the corneal endothelium, captured by CSM, using Fourier
analysis. Software was developed in the mathematical programming language Matlab. Pictures of the corneal
endothelium, captured by CSM, were read into the analysis software. The software automatically performed digital
enhancement of the images, normalizing lights and contrasts. The digitally enhanced images of the corneal endothelium
were Fourier transformed, using the fast Fourier transform (FFT) and stored as new images. Tools were developed and
applied for identification and analysis of relevant characteristics of the Fourier transformed images. The data obtained
from each Fourier transformed image was used to calculate the mean cell density of its corresponding corneal
endothelium. The calculation was based on well known diffraction theory. Results in form of estimated cell density of
the corneal endothelium were obtained, using fully automated analysis software on 292 images captured by CSM. The
cell density obtained by the fully automated analysis was compared to the cell density obtained from classical, semi-automated
analysis and a relatively large correlation was found.
The corneal endothelium serves as the posterior barrier of the cornea. Factors such as clarity and refractive properties of the cornea are in direct relationship to the quality of the endothelium. The endothelial cell density is considered the most important morphological factor. Morphometry of the corneal endothelium is presently done by semi-automated analysis of pictures captured by a Clinical Specular Microscope (CSM). Because of the occasional need of operator involvement, this process can be tedious, having a negative impact on sampling size. This study was dedicated to the development of fully automated analysis of images of the corneal endothelium, captured by CSM, using Fourier analysis. Software was developed in the mathematical programming language Matlab. Pictures of the corneal endothelium, captured by CSM, were read into the analysis software. The software automatically performed digital enhancement of the images. The digitally enhanced images of the corneal endothelium were transformed, using the fast Fourier transform (FFT). Tools were developed and applied for identification and analysis of relevant characteristics of the Fourier transformed images. The data obtained from each Fourier transformed image was used to calculate the mean cell density of its corresponding corneal endothelium. The calculation was based on well known diffraction theory. Results in form of estimated cell density of the corneal endothelium were obtained, using fully automated analysis software on images captured by CSM. The cell density obtained by the fully automated analysis was compared to the cell density obtained from classical, semi-automated analysis and a relatively large correlation was found.
We are developing automated morphometric analysis of the corneal endothelium. Here, the general impact of horizontal
offset of the cornea on morphometry was examined. Errors due to perspective during imaging with a Clinical Specular
Microscope (CSM) were analyzed considering semi automated analysis software and fully automated Fourier analysis
software. Methods: A mathematical model of the cornea was created. Trigonometry was applied to find the relationship
between the horizontal offset of the cornea relative to the microscope objective, and the consecutive errors from
perspective changes in the image. An experimental setup was created using a cornea made of polymethyl methacrylate
(PMMA). The posterior surface of the PMMA cornea was horizontally marked. The PMMA cornea was placed in a
holder. Difference in refractive index between real endothelium and aqueous humor was emulated using high refractive
index liquid. Images with varying horizontal offset on the PMMA corneal posterior surface, along with their relative
offset coordinates were captured, using CSM. Results: Experiments using controlled offset of the cornea in relation to its
center estimated that analyzable images can be acquired within an interval of 1.26 mm, using central cornea sampling
CSM. Because of refractive indices along with light scattering differences between the corneal tissue and PMMA , the
1.26 mm interval should be considered a first estimate for feasible CSM images. The effect of corneal endothelial offset
during imaging with CSM or fully automated Fourier analysis should be considered.
As a part of an ongoing research project on morphometrical diagnosis of the corneal
endothelium, an experimental optical setup has been created. The structure of the corneal
endothelial cells could be considered a reflecting periodical aperture. Hence, the diffraction
pattern reflected from the endothelium contains valuable morphometrical information. In the
present work, focus has been on sampling the posterior surface of explanted corneas.
Methods: An optical setup was created, using a 632.8 nm He-Ne laser as the light source. The
desired diffraction pattern was produced as a collimated reflection. Hence, because the
posterior surface of the cornea is concave, lenses were used to attain the right divergence of
the light impingent on the corneal endothelium. These lenses also made it possible to adjust
the sampling spot size. A beam splitter (BS) was used to provide an optical path for both the impinging laser beam as well as the reflected diffracted beam. The lens acting as a Fourier lens was then placed after the BS. At the back focal plane of the Fourier lens, a CCD detector was used for recording in the Fourier plane. In the process of creating the setup, explanted corneas were emulated using grated contact lenses. Results: The current optical set up allows identification of a diffraction pattern from a concave spherical surface with a radius of curvature of the same order as a human cornea.
As a part of an ongoing project on corneal endothelium morphometry by diffraction, a model for corneal endothelium simulation has been developed. The model has been developed in the mathematical programming language Matlab. Images of corneal endothelium were simulated and the diffraction pattern of the image was calculated. The diffraction pattern was calculated for a series of endothelial images while varying important variables in the simulated image. This rendered the theoretical relationships between values of variables in the diffraction pattern and values of morphometric variables in the image. At this stage, the analysis focused on the expression of endothelial mean cell size and coefficient of variation in the diffraction pattern, respectively. As expected from diffraction theory, it was found that there is a direct linear relationship between mean cell size and distance between periodic variations in the diffraction pattern. We further found that the ratio between the intensity in the central maximum and the intensity in the first harmonic of the diffraction pattern was functionally depending on the variation in cell size. The current findings demonstrate that it is possible to theoretically determine average cell size and coefficient of variation of cell size in the diffraction pattern.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.