May 2004
Volume 45, Issue 13
Free
ARVO Annual Meeting Abstract  |   May 2004
Color mapping of tear lipid layer thickness distribution from the image analysis in DR–1 tear lipid layer interference images
Author Affiliations & Notes
  • E. Goto
    Iidabashi Eye Clinic, Tokyo, Japan
    Department of Ophthalmology, Tokyo Dental College, Ichikawa, Japan
  • M. Dogru
    Department of Ophthalmology, Tokyo Dental College, Ichikawa, Japan
  • T. Kojima
    Department of Ophthalmology, Tokyo Dental College, Ichikawa, Japan
  • S. Suzuki
    Department of Ophthalmology, Tokyo Dental College, Ichikawa, Japan
  • R. Ishida
    Department of Ophthalmology, Tokyo Dental College, Ichikawa, Japan
  • R. Honda
    Department of Ophthalmology, Tokyo Dental College, Ichikawa, Japan
  • K. Tsubota
    Department of Ophthalmology, Tokyo Dental College, Ichikawa, Japan
  • Footnotes
    Commercial Relationships  E. Goto, None; M. Dogru, None; T. Kojima, None; S. Suzuki, None; R. Ishida, None; R. Honda, None; K. Tsubota, None.
  • Footnotes
    Support  none
Investigative Ophthalmology & Visual Science May 2004, Vol.45, 3458. doi:
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    • Get Citation

      E. Goto, M. Dogru, T. Kojima, S. Suzuki, R. Ishida, R. Honda, K. Tsubota; Color mapping of tear lipid layer thickness distribution from the image analysis in DR–1 tear lipid layer interference images . Invest. Ophthalmol. Vis. Sci. 2004;45(13):3458.

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

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Abstract

Abstract: : Purpose: Tear interferometry using DR–1 camera is an important technique to observe tear lipid layer status in dry eye clinical field. From 0 to around 100 nm (interference order 0∼1/2) of lipid layer thickness, monochromatic gray interference color is presented and this range of interference color has been considered as normal–like (indicated as Grade 1 or 2 by Yokoi et al). However, the evaluation of difference in intensity of gray interference color from raw DR–1 tear interference images is difficult. Thus easier and more detailed analysis system has been expected in this range of tear interference color. In this study, we try to develop the color mapping system of tear lipid layer thickness distribution from the DR–1 tear interference images in the range of interference order 0∼1/2. Methods: Recently reported DR–1 image quantification system (Goto et al, IOVS, 2003) was applied to all the pixels (around 0.15 mega pixels) of DR–1 images and color mapping system was programmed using image analysis software, ImageJ. This method was tried to one subject, one eye of each normal, mild dry eye, short break–up time type dry eye, and meibomian gland dysfunction group to show whether this mapping could describe the difference of interference images between them. Results: Color mapping of lipid layer thickness was successfully provided. Lipid layer thickness was 70, 30, 40, and 20 nm in the subjects above, respectively. Conclusions: Color mapping of tear lipid layer thickness distribution was successfully provided. Although data from larger scale of subjects are required, this system would contribute to more detailed evaluation (such as Foulier analysis) in DR–1 tear interferometry.

Keywords: cornea: tears/tear film/dry eye • topography 
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