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

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.

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.

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.

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.