Automated study of ocular thermal images: Comprehensive analysis of corneal health with different age group subjects and validation

Authors:
Jen-Hong Tan;E. Y. K. Ng;Rajendra Acharya U;C. Chee
Affiliations:
School of Mechanical and Aerospace Engineering, College of Engineering, Nanyang Technological University, 50, Nanyang Avenue, Singapore 639798;School of Mechanical and Aerospace Engineering, College of Engineering, Nanyang Technological University, 50, Nanyang Avenue, Singapore 639798;Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, Singapore;Medical & Surgical Retinal Centre Department of Ophthalmology, National University Hospital, Singapore 119074
Venue:
Digital Signal Processing
Year:
2010

Citing 2
Cited 1

Analysis of Normal Human Eye with Different Age Groups using Infrared Images

Journal of Medical Systems
Snakes, shapes, and gradient vector flow

IEEE Transactions on Image Processing

An Efficient Automated Algorithm to Detect Ocular Surface Temperature on Sequence of Thermograms Using Snake and Target Tracing Function

Journal of Medical Systems

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Abstract

Thermography using infrared (IR) imaging is a non-invasive imaging technique widely used in medical and engineering arena nowadays. This technique is capable of detecting temperature changes in the vascular tissues, and plays an important role in the study of ocular surface temperature and ocular diseases. In this study the performance of an automated algorithm which acquires corneal surface temperature was studied for normal IR thermograms of different age groups. The automated algorithm consists of algorithms intelligently localizing cornea and removing eye lashes, reading in temperature values within the localized cornea without any human intervention for further analysis. Its performance was compared against the results of manual corneal delineation. Our studies showed that the automated algorithm performed as good as the tedious and laborious manual method with the calculated average corneal temperature of 34.01+/-0.64^oC (automated) and 33.99+/-0.63^oC for manual method.