The analysis of microscopy images of corneal endothelium is routinely carried out at eye banks to assess cell density, one of the main indicators of cornea health state and quality. We propose here a new method to derive endothelium cell density that, at variance with most of the available techniques, does not require the identification of cell contours. It exploits the feature that endothelium cells are approximately laid out as a regular tessellation of hexagonal shapes. This technique estimates the inverse transpose of a matrix generating this cellular lattice, from which the density is easily obtained. The algorithm has been implemented in a Matlab prototype and tested on a set of 21 corneal endothelium images. The cell densities obtained matched quite well with the ones manually estimated by eye-bank experts: the percent difference between them was on average -0.1% (6.5% for absolute values). Albeit the performances of this new algorithm on the images of our test set are definitely good, a careful evaluation on a much larger data set is needed before any clinical application of the proposed technique could be envisaged. The collection of an adequate number of endothelium images and of their manual densities is currently in progress.

A lattice estimation approach for the automatic evaluation of corneal endothelium density

GRISAN, ENRICO;PAVIOTTI, ANNA;LAURENTI, NICOLA;RUGGERI, ALFREDO
2005

Abstract

The analysis of microscopy images of corneal endothelium is routinely carried out at eye banks to assess cell density, one of the main indicators of cornea health state and quality. We propose here a new method to derive endothelium cell density that, at variance with most of the available techniques, does not require the identification of cell contours. It exploits the feature that endothelium cells are approximately laid out as a regular tessellation of hexagonal shapes. This technique estimates the inverse transpose of a matrix generating this cellular lattice, from which the density is easily obtained. The algorithm has been implemented in a Matlab prototype and tested on a set of 21 corneal endothelium images. The cell densities obtained matched quite well with the ones manually estimated by eye-bank experts: the percent difference between them was on average -0.1% (6.5% for absolute values). Albeit the performances of this new algorithm on the images of our test set are definitely good, a careful evaluation on a much larger data set is needed before any clinical application of the proposed technique could be envisaged. The collection of an adequate number of endothelium images and of their manual densities is currently in progress.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11577/2433244
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