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- Materials and methods
Purpose: We aimed at developing simulation software capable of producing images of corneal endothelium close to identical to images captured by clinical specular microscopy with defined morphometrical characteristics. It was further planned to demonstrate the usefulness of the simulator by analysing measurement errors associated with a trained operator using a commercially available semi-automatic algorithm for analysis of simulated images.
Methods: Software was developed that allows creation of unique images of the corneal endothelium expressing morphology close to identical with that seen in images of corneal specular microscopy. Several hundred unique images of the corneal endothelium were generated with randomization, spanning a physiological range of endothelial cell density. As an example of the usefulness of the simulator for analysis of measurement errors in corneal specular microscopy, a total of 12 of all the images generated were randomly selected such that the endothelial cell density expressed was evenly distributed over the physiological range of endothelial cell density. The images were transferred to a personal computer. The imagenet-640 software was used to analyse endothelial cell size variation, percentage of hexagonal endothelial cells, and endothelial cell density.
Results: The simulator developed allows randomized generation of corneal specular microscopy images with a preset expected average and variation of cell structure. Calculated morphometric information of each cell is stored in the simulator. The image quality can secondarily be varied with a toolbox of filters to approximate a large spectrum of clinically captured images. As an example of the use of the simulator, measurement errors associated with one trained operator using the imagenet-640 software, and focusing on endothelial cell density, were examined. The functional dependence between morphometric information estimated with the imagenet-640 software algorithm and real morphometric information as provided by the simulator was analysed with regression. It was demonstrated that that the estimations of endothelial cell size variation was associated with a scaling error and that the random error was strongly dependent on the operator.
Conclusion: The newly developed simulator for randomized generation of morphometrically defined corneal specular microscopy images for the first time makes it possible to estimate a spatial scaling error of an available semi-automatic algorithm and to determine the random measurement error of important morphometric estimates in a defined reference sample of images. It is anticipated that the simulator will be a valuable tool for the generation of a large set of morphometrically well-characterized corneal specular microscopy images that can be used for calibration among research centres, for minimization of random errors and for measurement of quality control. Simulated images will be useful for the development of fully automatic analysis of corneal endothelial cell morphometry.
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- Materials and methods
The current paper describes a simulator for the generation of images of corneal endothelium as imaged with clinical specular microscopy (CSM).
The cornea serves as a protective barrier for the interior of the eye while simultaneously transmitting light. The cornea–air interface provides a large proportion of the refractive power of the optical apparatus of the eye because of a large shift of refractive index. High and even transmittance of the cornea is vital for clear vision. The innermost layer of the cornea, the endothelium, is a monolayer of flat, nonmitotic polygonal cells. In a healthy sample of corneal endothelium, a majority of the cells are hexagonal (Fig. 1).
The endothelium acts as a posterior physical barrier of the cornea and helps to control the fluid balance of the interior of the cornea by an energy-dependent mechanism. A well-functioning endothelium is vital for maintenance of the optical properties of the cornea. Surgical trauma to endothelial cells is repaired by lateral expansion of neighbouring endothelial cells, thus reducing the density of endothelial cells. If the density of endothelial cells becomes too low, the clarity of the cornea is threatened (Bourne et al. 1976; Waring et al. 1982). It is therefore important to evaluate the corneal endothelium prior to anterior segment surgery (Wirbelauer et al. 2005).
Because of the limitations of classic morphometric CSM analysis, new strategies are desirable. The periodic nature of the corneal endothelium makes morphometric analysis of its frequency domain an attractive alternative to the current CSM analysis. Epithelial cell analysis through Fraunhofer diffraction and thus an optical Fourier transform (Hecht 2002) was explored by Lambert and Klyce (Lambert & Klyce 1981) and was explored for analysis of corneal endothelium by Masters (Masters 1988; Masters et al. 1990). It has already been shown that the diffraction pattern of specular images of the corneal endothelium, obtained as the Fourier transform of the image, can be used to identify mean endothelial cell size and hence cell density (Doughty et al. 1997; Fitzke et al. 1997; Foracchia & Ruggeri 2004; Ruggeri et al. 2005, 2007).
However, no widely used working alternative method have been realized as of yet, and CSM with subsequent semi-automated border detection is still used for corneal endothelial morphometry. Development of an automized method would require an extensive reference database of clinically collected samples that is morphometrically characterized without significant random error. The lack of such a reference database has possibly been one important obstacle for transferring theoretical suggestions such as e.g. Fourier transforms of corneal endothelium to useful clinical strategies.
Current computer technology makes it possible to emulate images of morphometrically characterized cell structures. This provides a possibility to generate an extensive database of defined images by simulation. Such a database could be used for development of fully automatic algorithms for morphometry of the corneal endothelium.
There have been several attempts to develop algorithms for emulation of cell structure (Honda 1978; Weliky & Oster 1990; Meineke et al. 2001; Sanchez-Marin 2005). Simulation of cell structures has been shown as a useful tool to explore and evaluate new methods of cell morphometry (Fitzke et al. 1997; Bucht et al. 2006). Analysis of these studies revealed the need for a completely new simulator for clinical CSM images incorporating the following features: (i) The image should be generated based on randomization such that only the expected value and the variability of key independent morphometric variables are parameters for the randomization. (ii) The randomly generated cell structure should be morphometrically characterized without error. (iii) It should be possible to deteriorate the image quality with a set of filters to closely approximate image quality obtained when collecting images in a clinical setting.
The aim of the current study was to develop a software-based simulator based on the above three criteria. It was intended to use the simulator to generate a large database of morphometrically defined standard CSM images that can be used for validation of algorithms for morphometry of clinical CSM images. To demonstrate the realism of the CSM images automatically generated by the simulator and the simulator usefulness for evaluation of measurement errors associated with semi-automatic clinical CSM, it was planned to analyse measurement errors associated with a trained operator’s estimation of polymegethism, pleomorphism and endothelial cell density in a subset of 12 images using the commercially available morphometric analysis software, imagnet-640 software.