Open AccessAutomatic assessment of tear film and tear meniscus parameters in healthy subjects using ultrahigh-resolution optical coherence tomography
Author(s) -
Hannes Stegmann,
Valentin Aranha dos Santos,
Alina Messner,
Angelika Unterhuber,
Doreen Schmidl,
Gerhard Garhöfer,
Leopold Schmetterer,
René M. Werkmeister
Publication year - 2019
Publication title -
biomedical optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.362
H-Index - 86
ISSN - 2156-7085
DOI - 10.1364/boe.10.002744
Subject(s) - optical coherence tomography , meniscus , ophthalmology , segmentation , medicine , radius , biomedical engineering , optics , nuclear medicine , materials science , artificial intelligence , computer science , physics , computer security , incidence (geometry)
Many different parameters exist for the investigation of tear film dynamics. We present a new tear meniscus segmentation algorithm which automatically extracts tear meniscus area (TMA), height (TMH), depth (TMD) and radius (TMR) from UHR-OCT measurements and apply it to a data set including repeated measurements from ten healthy subjects. Mean values and standard deviations are 0.0174 ± 0.007 mm 2 , 0.272 ± 0.069 mm, 0.191 ± 0.049 mm and 0.309 ± 0.123 mm for TMA, TMH, TMD and TMR, respectively. A significant correlation was found between all respective tear meniscus parameter pairs (all p < 0.001, all Pearson's r ≥ 0.657). Challenges, limitations and potential improvements related to the data acquisition and the algorithm itself are discussed. The automatic segmentation of tear meniscus measurements acquired with UHR-OCT might help in a clinical setting to further understand the tear film and related medical conditions like dry eye disease.