April 2010
Volume 51, Issue 13
ARVO Annual Meeting Abstract  |   April 2010
Automated Processing of HRT Corneal Images to Objectively Assess Changes in Corneal Health
Author Affiliations & Notes
  • C. W. Sindt
    Ophthalmology, University of Iowa, Iowa City, Iowa
  • B. Lay
    ADCIS, Herouville Saint-Clair, France
  • J. R. Kern
    Global Medical Affairs, Alcon Laboratories, Fort Worth, Texas
  • M. E. Verdugo
    Global Medical Affairs, Alcon Laboratories, Fort Worth, Texas
  • Footnotes
    Commercial Relationships  C.W. Sindt, Alcon Research, LTD, C; Alcon Research, LTD, R; B. Lay, ADCIS, F; J.R. Kern, Alcon Research, LTD, F; M.E. Verdugo, Alcon Research, LTD, F.
  • Footnotes
    Support  Alcon Research, LTD
Investigative Ophthalmology & Visual Science April 2010, Vol.51, 5665. doi:
  • Views
  • Share
  • Tools
    • Alerts
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      C. W. Sindt, B. Lay, J. R. Kern, M. E. Verdugo; Automated Processing of HRT Corneal Images to Objectively Assess Changes in Corneal Health. Invest. Ophthalmol. Vis. Sci. 2010;51(13):5665.

      Download citation file:

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

  • Supplements

Purpose: : In vivo histology of corneal structures assessed via the Heidelberg HRT Rostock (HRT) confocal microscope may serve as an indicator of corneal health. However, the resulting amount of data is massive and difficult to manage. The objective of this project was to use image processing techniques to objectively evaluate HRT confocal images for changes in corneal health.

Methods: : Forty central corneal images in 2um depths were collected in both eyes of 65 subjects with the HRT. A subset of images were selected and manually analyzed by experts to identify epithelial wing cell density and the presence of immune cells. Software was developed to select the best image for wing cells, nerve layer and immune cells. Using selected images, additional software based on advanced image processing techniques was developed to automatically detect and calculate multiple attributes for each cell type. Objective measures from the software were compared to manual annotation to validate the imaging segmentation algorithm.

Results: : Automatic detection produced better, more consistent and faster results than manual counting for epithelial density and immune cell presence. Software was able to accurately identify objects of interest without human interaction. Wing cells, nerve layer and immune cells were objectively analyzed for density, area, position, shape and consistency in morphology. Software was validated on 390 images and includes a graphical interface which allows any HRT user to easily assess images and export measurements for statistical analysis.

Conclusions: : This research demonstrates that by using confocal imaging and the associated software described in clinical practice, one can objectively evaluate changes in corneal health, allowing for more timely intervention and appropriate treatment choice. Future development will involve the analysis of additional corneal structures, as well as the use of three dimensional image processing techniques to display 3-D objects and more effectively track changes over time.

Clinical Trial: : www.clinicaltrials.gov NCT00804999

Keywords: microscopy: confocal/tunneling • cornea: epithelium • image processing 

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.