A model for corneal endothelial morphometry by diffraction.

Bucht, Curry; Söderberg, Per G.; Manneberg, Göran

doi:10.1117/12.660023

Cited by 3 publications

(7 citation statements)

References 3 publications

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“…The next step in the algorithm was to create cell barriers for the structure. A previous attempt on creating a endothelial cell simulator (Bucht et al. 2006) was based on the Voronoi geometrical method for creation of cell barriers.…”

Section: Methodsmentioning

confidence: 99%

“…The current simulator is a further development of previously published work on emulation of cell structure (Honda 1978;Weliky & Oster 1990;Fitzke et al 1997;Meineke et al 2001;Sanchez-Marin 2005;Bucht et al 2006). The algorithm in the current study is in every part a new development but based on experience gathered from application of previously published algorithms.…”

Section: The Simulatormentioning

confidence: 99%

“…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).…”

Section: Introductionmentioning

confidence: 99%

“…A previous attempt on creating a endothelial cell simulator (Bucht et al 2006) was based on the Voronoi geometrical method for creation of cell barriers. The approach using Voronoi, or Dirichlet tessellation for simulation of cells was introduced by Honda (Honda 1978) and followed up by Weliky et al (Weliky & Oster 1990) and Meineke (Meineke et al 2001).…”

Section: Acta Ophthalmologica 2011mentioning

confidence: 99%

“…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.…”

Section: Introductionmentioning

confidence: 99%

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Simulation of specular microscopy images of corneal endothelium, a tool for control of measurement errors

Bucht

Söderberg

Manneberg

2011

Acta Ophthalmologica

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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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Section: Methodsmentioning

confidence: 99%

Section: The Simulatormentioning

confidence: 99%

“…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).…”

Section: Introductionmentioning

confidence: 99%

Section: Acta Ophthalmologica 2011mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Simulation of specular microscopy images of corneal endothelium, a tool for control of measurement errors

Bucht

Söderberg

Manneberg

2011

Acta Ophthalmologica

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Segmentation of endothelial cells of the cornea from the distance map of confocal microscope images

Herrera-Pereda

Taboada‐Crispi

Babin

et al. 2021

Computers in Biology and Medicine

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Fully automatic evaluation of the corneal endothelium from in vivo confocal microscopy

et al. 2015

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BackgroundManual and semi-automatic analyses of images, acquired in vivo by confocal microscopy, are often used to determine the quality of corneal endothelium in the human eye. These procedures are highly time consuming. Here, we present two fully automatic methods to analyze and quantify corneal endothelium imaged by in vivo white light slit-scanning confocal microscopy.MethodsIn the first approach, endothelial cell density is estimated with the help of spatial frequency analysis. We evaluate published methods, and propose a new, parameter-free method. In the second approach, based on the stochastic watershed, cells are automatically segmented and the result is used to estimate cell density, polymegathism (cell size variability) and pleomorphism (cell shape variation). We show how to determine optimal values for the three parameters of this algorithm, and compare its results to a semi-automatic delineation by a trained observer.ResultsThe frequency analysis method proposed here is more precise than any published method. The segmentation method outperforms the fully automatic method in the NAVIS software (Nidek Technologies Srl, Padova, Italy), which significantly overestimates the number of cells for cell densities below approximately 1200 mm−2, as well as previously published methods.ConclusionsThe methods presented here provide a significant improvement over the state of the art, and make in vivo, automated assessment of corneal endothelium more accessible. The segmentation method proposed paves the way to many possible new morphometric parameters, which can quickly and precisely be determined from the segmented image.Electronic supplementary materialThe online version of this article (doi:10.1186/s12880-015-0054-3) contains supplementary material, which is available to authorized users.

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A model for corneal endothelial morphometry by diffraction.

Cited by 3 publications

References 3 publications

Simulation of specular microscopy images of corneal endothelium, a tool for control of measurement errors

Simulation of specular microscopy images of corneal endothelium, a tool for control of measurement errors

Segmentation of endothelial cells of the cornea from the distance map of confocal microscope images

Fully automatic evaluation of the corneal endothelium from in vivo confocal microscopy

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