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A deep learning approach for the quantification of lower tear meniscus height
Biomedical Signal Processing and Control, 2021Abstract The quantification of the tear meniscus height can be helpful in the diagnosis of Dry Eyes Disease. This paper presents a method for automatic quantitation of lower tear meniscus height (TMH) with fully convolutional neural networks (FCNN) and investigate its performance and efficacy compared to manual measurements.
Yongjin Zhou, Ying Jie
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Clinical assessment of the lower tear meniscus height
Ophthalmic and Physiological Optics, 2009Abstract Purpose: Different values of the lower tear meniscus height (TMH) can be obtained depending on the method and technique of measurement employed. This study aimed to assess (1) differences between the absolute (TMH‐A), reflex (TMH‐R) and fluorescein (TMH‐F) lower tear meniscus heights,
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Interobserver variability of an open-source software for tear meniscus height measurement
Contact Lens and Anterior Eye, 2016Different values of the lower tear meniscus height (TMH) can be obtained depending on the method and technique of measurement employed. The aim of this study was to analyse the interobserver variability of a method for measuring TMH by using an open source software.On a group of 176 subjects, two videos of the central lower tear meniscus, first under ...
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Automated inferior tear meniscus height measurement in a sequence of video
2012 IEEE-EMBS Conference on Biomedical Engineering and Sciences, 2012Video analysis of the dynamics of the tear meniscus height (TMH) have been used in the diagnosis of dry eye. However, the existing techniques require substantial manual intervention. This research work aims to automate the process of estimating the change in the inferior TMH without manual intervention.
Mohd Zulfaezal Che Azemin
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