April 2011
Volume 52, Issue 14
Free
ARVO Annual Meeting Abstract  |   April 2011
Automated Segmentation For Corneal Epithelium Cell Images
Author Affiliations & Notes
  • Julien Bullet
    CHNO des XV-XX, Paris, France
  • Thomas Gaujoux
    CHNO des XV-XX, Paris, France
  • Vincent Borderie
    CHNO des XV-XX, Paris, France
  • Laurent Laroche
    CHNO des XV-XX, Paris, France
  • Footnotes
    Commercial Relationships  Julien Bullet, None; Thomas Gaujoux, None; Vincent Borderie, None; Laurent Laroche, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science April 2011, Vol.52, 4192. doi:
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    • Get Citation

      Julien Bullet, Thomas Gaujoux, Vincent Borderie, Laurent Laroche; Automated Segmentation For Corneal Epithelium Cell Images. Invest. Ophthalmol. Vis. Sci. 2011;52(14):4192.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract
 
Purpose:
 

Corneal epithelium images can be obtained through HeidelbergRetina Tomograph corneal module. Automated analysis of epitheliumcells morphology could help clinical and pathological diagnosis.First step toward this analysis is to extract cell borders froman HRT image. We propose an algorithm to automatically performsegmentation of these images (Fig. 1).

 
Methods:
 

Steps of the algorithm include:• A noise reduction througha fast-Fourier-transform (FFT) band pass filter with normalization(pixel values range from 0 to 255).• Image binarizationwith a median value threshold.• Standard watershed algorithmon distance map is used to separate fused cells (Fig 2).• Voronoidiagram segmentation algorithm gives a final border map (Fig3).

 
Results:
 

Most cells borders are correctly found. However, a small numberof oversegmented small cells are present.

 
Conclusions:
 

Epithelial cell image segmentation can be performed automatically,thus allowing a statistical analysis of cell morphological andpathological characteristics  

  

 
Keywords: cornea: epithelium • image processing • imaging/image analysis: non-clinical 
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