Print Email Facebook Twitter Fully automatic evaluation of the corneal endothelium from in vivo confocal microscopy Title Fully automatic evaluation of the corneal endothelium from in vivo confocal microscopy Author Selig, B. Vermeer, K.A. Rieger, B. Hillenaar, T. Hendriks, C.L.L. Faculty Applied Sciences Department ImPhys/Imaging Physics Date 2015-04-26 Abstract Background Manual 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. Methods In 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. Results The 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 publishedmethods. Conclusions The 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. Subject frequency analysisstochastic watershed segmentationimage-based quantificationin vivo imagingCorneal endothelium To reference this document use: http://resolver.tudelft.nl/uuid:935e0b92-a087-4b19-9834-6df6c0f40850 DOI https://doi.org/10.1186/s12880-015-0054-3 Publisher BioMed Central ISSN 1471-2342 Source http://www.biomedcentral.com/1471-2342/15/13 Source BMC Medical Imaging, 15, 2015 Part of collection Institutional Repository Document type journal article Rights © 2015 The Author(s)This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0) Files PDF Rieger_2015.pdf 3.48 MB Close viewer /islandora/object/uuid:935e0b92-a087-4b19-9834-6df6c0f40850/datastream/OBJ/view