A Novel System for Ocular Surface Temperature Measurement and Tracking

Abstract

Ocular surface temperature (OST) is affected by changes in eye physiology caused by normal homeostasis, environmental changes, or systemic and local disease. OST can help a physician diagnose eye disease with improved accuracy and provide useful information for eye research. This paper presents a novel system, including novel hardware design and novel algorithms, capable of automatically measuring and tracking OST from the cornea over any period of time. The system uses an infrared (IR) camera and a visible (VIS) camera to capture synchronous thermal and visible videos, respectively, from the eye surface. The frames for each camera video sequence are then registered together (video registration) using two sets of control points. The points are manually selected on the first pair of timestamped IR/VIS frames and tracked over all subsequent frames using the Lucas-Kanade (LK) optical flow algorithm (point tracking). A mean square error (MSE) of 5.43±2.01 pixels was reported for salient point tracking of the IR video and 6.81±2.32 pixels for tracking of the VIS video. Overall MSE for registration was 5.03 ±1.82 pixels. The corneal area was segmented in the VIS images and localized on the IR images using the semantic segmentation method (corneal segmentation). A mean Intersection over Union (IoU) of 94.6% was found, representing the accuracy of corneal segmentation. A system for measuring and tracking eye surface temperature over time was developed. The system is able to localize the cornea on both VIS and IR images, and report temperature profiles of the cornea over the period of measurement. Experimental results show that the system can work as a tool for measuring and tracking OST over time.INDEX TERMS dual camera imaging system, eye temperature, ocular semantic segmentation, ocular surface temperature, thermal imaging This article has been accepted for publication in IEEE Access.