Segmentation methods and morphometry of confocal microscopy imaged corneal epithelial cells

被引:5
作者
Bhattacharya, Pradipta
Edwards, Katie
Schmid, Katrina L.
机构
[1] Queensland Univ Technol, Sch Optometry & Vis Sci, Kelvin Grove, Qld, Australia
[2] Queensland Univ Technol, Fac Hlth, Ctr Vis & Eye Res, Kelvin Grove, Qld, Australia
关键词
Cornea; Epithelial cell; Confocal microscopy; ImageJ; Morphometric parameters; SCANNING SLIT; WHITE-LIGHT; LIMBAL; EYES;
D O I
10.1016/j.clae.2022.101720
中图分类号
R77 [眼科学];
学科分类号
100212 ;
摘要
Purpose: To develop and explore automated cell identification and segmentation methods for morphometry of confocal microscopy imaged corneal epithelial cells using ImageJ software. Methods: In vivo confocal microscopy images of the intermediate (wing) and basal cell layers of the central and peripheral corneas of 20 healthy participants were analysed. The intermediate and basal cell areas obtained using the two new techniques (i.e., manual- and auto- thresholding) were compared with the widely used manual tracing technique. A predefined range of epithelial cell morphometric parameters was used as image descriptors to improve cell identification and segmentation. Results: The mean intermediate cell area obtained using the manual tracing (central; 120 +/- 14 mu m2, peripheral; 123 +/- 15 mu m2) was statistically similar (p > 0.05) to the manual thresholding (central; 119 +/- 7 mu m2, peripheral; 119 +/- 8) but not with the auto thresholding technique (central; 101 +/- 8 mu m2, peripheral; 101 +/- 7 mu m2). BlandAltman limits of agreement for the mean difference (measurement bias) in central and peripheral intermediate cell area determined via manual tracing and manual thresholding techniques were 1 mu m2 (+25 to - 23 mu m2) and 4 mu m2 (+29.8 to - 21.9 mu m2). There were statistically significant differences in basal cell area between the three methods. Conclusion: The manual thresholding technique may be used for automated identification and segmentation of corneal epithelial intermediate cells (central and peripheral) for assessing various morphometric parameters. However, measurement of the corneal epithelial basal cells is less reliable using thresholding techniques.
引用
收藏
页数:9
相关论文
共 42 条
  • [1] Abramoff M. D., 2004, Biophotonics Int., V11, P36
  • [2] ULTRASTRUCTURAL-STUDY OF THE CORNEAL EPITHELIUM IN THE RECURRENT EROSION SYNDROME
    AITKEN, DA
    BEIROUTY, ZA
    LEE, WR
    [J]. BRITISH JOURNAL OF OPHTHALMOLOGY, 1995, 79 (03) : 282 - 289
  • [3] Alkabes M., 2007, Investigative Ophthalmology Visual Science, V48, P3880
  • [4] A Quick & Automated Method for Measuring Cell Area Using ImageJ
    Baviskar, Sandhya N.
    [J]. AMERICAN BIOLOGY TEACHER, 2011, 73 (09) : 554 - 556
  • [5] Central corneal basal cell density and nerve parameters in ocular surface disease and limbal stem cell deficiency: a review and meta-analysis
    Bhattacharya, Pradipta
    Edwards, Katie
    Harkin, Damien
    Schmid, Katrina L.
    [J]. BRITISH JOURNAL OF OPHTHALMOLOGY, 2020, 104 (12) : 1633 - 1639
  • [6] Botha CP, 2014, VIS COMP MED THEOR
  • [7] A reproducible automated segmentation algorithm for corneal epithelium cell images from in vivo laser scanning confocal microscopy
    Bullet, Julien
    Gaujoux, Thomas
    Borderie, Vincent
    Bloch, Isabelle
    Laroche, Laurent
    [J]. ACTA OPHTHALMOLOGICA, 2014, 92 (04) : e312 - e316
  • [8] Unbiased corneal tissue analysis using Gabor-domain optical coherence microscopy and machine learning for automatic segmentation of corneal endothelial cells
    Canavesi, Cristina
    Cogliati, Andrea
    Hindman, Holly B.
    [J]. JOURNAL OF BIOMEDICAL OPTICS, 2020, 25 (09)
  • [9] Watershed Cuts: Minimum Spanning Forests and the Drop of Water Principle
    Cousty, Jean
    Bertrand, Gilles
    Najman, Laurent
    Couprie, Michel
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2009, 31 (08) : 1362 - 1374
  • [10] In Vivo Confocal Microscopy of Corneal Nerves in Health and Disease
    Cruzat, Andrea
    Qazi, Yureeda
    Hamrah, Pedram
    [J]. OCULAR SURFACE, 2017, 15 (01) : 15 - 47