Corneal topography matching by iterative registration

Wang, Junjie, Elsheikh, Ahmed ORCID: 0000-0001-7456-1749, Davey, Pinakin, Wang, Weizhuo Victor, Bao, FangJun and Mottershead, John ORCID: 0000-0003-1279-2562
(2014) Corneal topography matching by iterative registration. Journal Of Engineering In Medicine - Part H, 228 (11). pp. 1154-1167.

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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 paper Direct Search (DS) optimisation using the Nelder-Mead algorithm as well as several variants of the Iterative Closest/Corresponding Point (ICP) 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 ICP 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 ICP 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.

Item Type: Article
Uncontrolled Keywords: cornea, iterative closest/corresponding point algorithm, image registration, topography matching, Zernike polynomial
Depositing User: Symplectic Admin
Date Deposited: 02 Mar 2015 09:58
Last Modified: 16 Dec 2022 12:29
DOI: 10.1177/0954411914559080
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