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Purpose: Fluorescence imaging is a valuable tool for studying tear film dynamics andcorneal staining. Automating the quantification of fluorescence images is a challenging necessary step for making connections to mathematical models. A significant partof the challenge is identifying the region of interest, specifically the cornea, for collected data with widely varying characteristics.Methods: The gradient of pixel intensity at the cornea–sclera limbus is used as the objective of standard optimization to find a circle that best represents the cornea. Results of the optimization in one image are used as initial conditions in the next imageof a sequence. Additional initial conditions are chosen heuristically. The algorithm iscoded in open-source software.Results: The algorithm was first applied to 514 videos of 26 normal subjects, for a total of over 87,000 images. Only in 12 of the videos does the standard deviation in thedetected corneal radius exceed 1% of the image height, and only 3 exceeded 2%. The algorithm was applied to a sample of images from a second study with 142 dry-eye subjects. Significant staining was present in a substantial number of these images. Visual inspection and statistical analysis show good resuls for both normal and dry-eye images.Conclusion: The new algorithm is highly effective over a wide range of tear film andcorneal staining images collected at different times and locations. 

Abstract We present a mathematical model to study the influence of a lipid reservoir, seen experimentally, at the lid margin on the formation and relaxation of the tear film during a partial blink. Applying the lubrication limit, we derive two coupled non-linear partial differential equations characterizing the evolution of the aqueous tear fluid and the covering insoluble lipid concentration. Departing from prior works, we explore a new set of boundary conditions (BCs) enforcing hypothesized lipid concentration dynamics at the lid margins. Using both numerical and analytical approaches, we find that the lipid-focused BCs strongly impact tear film formation and thinning rates. Specifically, during the upstroke of the eyelid, we find specifying the lipid concentration at the lid margin accelerates thinning. Parameter regimes that cause tear film formation success or failure are identified. More importantly, this work expands our understanding of the consequences of lipid dynamics near the lid margins for tear film formation.