TMIS : a new image‐based software application for the measurement of tear meniscus height

Purpose To present a new automated image recognition software for the measurement of tear meniscus height ( TMH ) and investigate its correlation and efficacy compared with an open‐source software ( NIH ImageJ) and manual evaluation. Methods A total of 520 slit lamp photographs, among which 276 were in ×16 magnification and 244 were ×40 magnified, captured from 138 eyes of 69 healthy subjects were assessed for TMH by the new automated Tear Meniscus Identification Software ( TMIS ), ImageJ and human graders. Images processing of TMIS included filtration, recognition and measurement of slit lamp photographs under certain algorithm, which output two measurement patterns, TMIS M ax and TMIS M ean . TMH measured by ImageJ software, considered as the reference value, was conducted by a masked observer while four masked ophthalmologists performed the manual evaluation. Results In both magnifications, TMH measured by TMIS M ean showed similar values with ImageJ while manual evaluation demonstrated underestimated results, and a strong correlation was detected between TMIS and ImageJ. In ×16 magnified photographs, manually obtained TMH revealed a higher correlation with ImageJ, whereas a notably stronger correlation of TMIS with ImageJ was observed in ×40 photographs. Correspondingly, the accuracy for both TMIS M ax and TMIS M ean appeared to be lower than most doctors in ×16 slit lamp images, in contrast to a better precision of TMIS M ean in ×40 ones. Conclusion The new software displayed high accuracy and efficacy in ×40 magnification and TMIS M ean pattern, suggesting the possibility of this automated TMH measurement platform to be a valid tool in dry eye screening and follow‐up practice.