title: Corneal topography matching by iterative registration.
abstract: Videokeratography is used for the measurement of corneal topography in overlapping portions (or maps) which must later be joined together to form the overall topography of the cornea. The separate portions are measured from different viewpoints and therefore must be brought together by registration of measurement points in the regions of overlap. The central map is generally the most accurate, but all maps are measured with uncertainty that increases towards the periphery. It becomes the reference (or static) map, and the peripheral (or dynamic) maps must then be transformed by rotation and translation so that the overlapping portions are matched. The process known as registration, of determining the necessary transformation, is a well-understood procedure in image analysis and has been applied in several areas of science and engineering. In this article, direct search optimisation using the Nelder-Mead algorithm and several variants of the iterative closest/corresponding point routine are explained and applied to simulated and real clinical data. The measurement points on the static and dynamic maps are generally different so that it becomes necessary to interpolate, which is done using a truncated series of Zernike polynomials. The point-to-plane iterative closest/corresponding point variant has the advantage of releasing certain optimisation constraints that lead to persistent registration and alignment errors when other approaches are used. The point-to-plane iterative closest/corresponding point routine is found to be robust to measurement noise, insensitive to starting values of the transformation parameters and produces high-quality results when using real clinical data.
authors.affiliation: School of Engineering, University of Liverpool, Liverpool, UK junjie.wang@liverpool.ac.uk.
authors.forename: Junjie
authors.initials: J
authors.lastname: Wang
authors.affiliation: School of Engineering, University of Liverpool, Liverpool, UK National Institute for Health Research (NIHR) Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK.
authors.forename: Ahmed
authors.initials: A
authors.lastname: Elsheikh
authors.affiliation: College of Optometry, Western University of Health Sciences, Pomona, CA, USA.
authors.forename: Pinakin G
authors.initials: PG
authors.lastname: Davey
authors.affiliation: School of Engineering, Manchester Metropolitan University, Manchester, UK.
authors.forename: Weizhuo
authors.initials: W
authors.lastname: Wang
authors.affiliation: Eye Hospital, Wenzhou Medical University, Wenzhou, China.
authors.forename: Fangjun
authors.initials: F
authors.lastname: Bao
authors.affiliation: School of Engineering, University of Liverpool, Liverpool, UK.
authors.forename: John E
authors.initials: JE
authors.lastname: Mottershead
mesh_terms: D000465:Algorithms; D003315:Cornea / Q000033:anatomy & histology*; D019781:Corneal Topography / Q000379:methods*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D014741:Video Recording / Q000379:methods*
keywords: Cornea; Zernike polynomial; image registration; iterative closest/corresponding point algorithm; topography matching