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

Overview of attention for article published in BMC Medical Imaging, April 2015
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  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

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Title
Fully automatic evaluation of the corneal endothelium from in vivo confocal microscopy
Published in
BMC Medical Imaging, April 2015
DOI 10.1186/s12880-015-0054-3
Pubmed ID
Authors

Bettina Selig, Koenraad A Vermeer, Bernd Rieger, Toine Hillenaar, Cris L Luengo Hendriks

Abstract

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. 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. 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 published methods. 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.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Finland 1 3%
Poland 1 3%
Unknown 32 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 18%
Student > Master 5 15%
Researcher 4 12%
Student > Bachelor 3 9%
Other 3 9%
Other 7 21%
Unknown 6 18%
Readers by discipline Count As %
Computer Science 6 18%
Engineering 5 15%
Biochemistry, Genetics and Molecular Biology 3 9%
Medicine and Dentistry 3 9%
Mathematics 2 6%
Other 7 21%
Unknown 8 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 February 2021.
All research outputs
#6,283,036
of 22,800,560 outputs
Outputs from BMC Medical Imaging
#78
of 596 outputs
Outputs of similar age
#74,671
of 265,108 outputs
Outputs of similar age from BMC Medical Imaging
#4
of 10 outputs
Altmetric has tracked 22,800,560 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 596 research outputs from this source. They receive a mean Attention Score of 2.1. This one has done well, scoring higher than 86% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 265,108 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.