title: Automatic pupillometry from digital images.
abstract: Determination of two-dimensional characteristics of the anterior surface of the eye is becoming increasingly important in modern optometry and ophthalmology practice. In particular, accurate estimation of the pupil size and centration is crucial in customized refractive surgery, corneal transplantation, and advanced contact lens fitting. The pupil parameters change under different lighting conditions so they often need to be related to some fixed reference such as the limbus outline. However, current commercial pupillometers do not estimate limbus position. We present a novel algorithm for automatic extraction of pupil parameters from digital images that takes the relative limbus information into account. The algorithm utilizes several customized image processing techniques that form a robust procedure which performs well for a wide range of clinical images. We apply the developed algorithm to images obtained by a standard digital camera, and specialized ophthalmic instruments such as a wavefront sensor and a high-speed imaging system.
authors.affiliation: Contact Lens and Visual Optics Laboratory, School of Optometry, Queensland University of Technology, Kelvin Grove Q4059, Brisbane, Australia. d.iskander@qut.edu.au
authors.forename: D Robert
authors.initials: DR
authors.lastname: Iskander
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Collins
authors.forename: Siegfried
authors.initials: S
authors.lastname: Mioschek
authors.forename: Martin
authors.initials: M
authors.lastname: Trunk
mesh_terms: D000465:Algorithms; D001699:Biometry / Q000379:methods; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007498:Iris / Q000033:anatomy & histology; D016850:Limbus Corneae / Q000033:anatomy & histology; D009887:Ophthalmoscopy / Q000379:methods*; D010363:Pattern Recognition, Automated; D010781:Photography / Q000379:methods*; D011680:Pupil; D012815:Signal Processing, Computer-Assisted; D013382:Subtraction Technique; D014741:Video Recording / Q000379:methods