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Influence of applied corneal endothelium image segmentation techniques on the clinical parameters

Piorkowski, Adam (author)
AGH Univ Sci & Technol, Dept Geoinformat & Appl Comp Sci, Krakow, Poland.
Nurzynska, Karolina (author)
Silesian Tech Univ, Inst Informat, Gliwice, Poland.
Gronkowska-Serafin, Jolanta (author)
Pomeranian Med Univ, Dept Ophthalmol, Szczecin, Poland.;Sygehus Sonderjylland, Dept Ophthalmol, Sonderborg, Denmark.
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Selig, Bettina (author)
Uppsala universitet,Bildanalys och människa-datorinteraktion
Boldak, Cezary (author)
Bialystok Tech Univ, Fac Comp Sci, Bialystok, Poland.
Reska, Daniel (author)
Bialystok Tech Univ, Fac Comp Sci, Bialystok, Poland.
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AGH Univ Sci & Technol, Dept Geoinformat & Appl Comp Sci, Krakow, Poland Silesian Tech Univ, Inst Informat, Gliwice, Poland. (creator_code:org_t)
Elsevier BV, 2017
2017
English.
In: Computerized Medical Imaging and Graphics. - : Elsevier BV. - 0895-6111 .- 1879-0771. ; 55, s. 13-27
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • The corneal endothelium state is verified on the basis of an in vivo specular microscope image from which the shape and density of cells are exploited for data description. Due to the relatively low image quality resulting from a high magnification of the living, non-stained tissue, both manual and automatic analysis of the data is a challenging task. Although, many automatic or semi-automatic solutions have already been introduced, all of them are prone to inaccuracy. This work presents a comparison of four methods (fully-automated or semi-automated) for endothelial cell segmentation, all of which represent a different approach to cell segmentation; fast robust stochastic watershed (FRSW), KH method, active contours solution (SNAKE), and TOPCON ImageNET. Moreover, an improvement framework is introduced which aims to unify precise cell border location in images preprocessed with differing techniques. Finally, the influence of the selected methods on clinical parameters is examined, both with and without the improvement framework application. The experiments revealed that although the image segmentation approaches differ, the measures calculated for clinical parameters are in high accordance when CV (coefficient of variation), and CVSL (coefficient of variation of cell sides length) are considered. Higher variation was noticed for the H (hexagonality) metric. Utilisation of the improvement framework assured better repeatability of precise endothelial cell border location between the methods while diminishing the dispersion of clinical parameter values calculated for such images. Finally, it was proven statistically that the image processing method applied for endothelial cell analysis does not influence the ability to differentiate between the images using medical parameters.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Radiologi och bildbehandling (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Radiology, Nuclear Medicine and Medical Imaging (hsv//eng)
NATURVETENSKAP  -- Data- och informationsvetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences (hsv//eng)

Keyword

The corneal endothelium cells
Non-contact specular microscope
Image processing
Segmentation

Publication and Content Type

ref (subject category)
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