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.

Principles of operation, accuracy and precision of an Eye Surface Profiler

“…Placido disk videokeratoscopy has the ability to measure a larger portion of the corneal surface than a keratometer, extending, on average, to about 9 mm horizontally and to about 7.5 mm vertically for Caucasian eyes. Further coverage extension has been attempted with extrapolation techniques, particularly for the software based contact lens fitting tools or with a map stitching technique, in which central and peripheral videokeratoscopy topographies were combined, extending the measured area, on average, to about 11 mm horizontally and 10 mm vertically . The latter technique has been recently realised in one of the commercially available videokeratoscopes…”

Effect of Misalignment between Successive Corneal Videokeratography Maps on the Repeatability of Topography Data

“…The ICP algorithm, originally proposed to align 3D surfaces, has become the dominant method for matching maps collected for the same object but from different viewpoints [ 23 ]. The use of ICP algorithm to estimate and correct for misalignment in corneal topography maps is believed to be more straightforward and potentially more computationally efficient than earlier methods such as those developed by Tobias et al [ 8 ] and Franklin et al [ 24 , 25 ].…”

“…The more pronounced fit errors in peripheral areas compared to central areas and in posterior maps compared to anterior maps may have been caused by optical distortion due to aberrations in the instrument’s measuring lens [ 17 , 23 ], and is expected to have affected the values of misalignment between measurements, as estimated by the ICP algorithm. It can therefore be argued that the accuracy of topographic data and the repeatability of VK maps could be improved by utilising only the central regions of anterior maps when estimating misalignment.…”

Study on the Compressive Properties of an Elastomeric Porous Cylinder Using 360° Three-Dimensional Digital Image Correlation System

“…Step 3: The binocular stereovision technique is utilized to reconstruct the 3D world coordinates of each surface point of the rigid body object, while simultaneously solving the vector motion trajectory of each surface in relation to the center of gravity. Additionally, the iterative closest point (ICP) [ 23 ] algorithm is employed in conjunction with the least square method to obtain the rotation matrix and translation matrix between distinct world coordinate systems. This enables the calibration of the spatial position relationship of the camera systems to be accomplished and the seamless integration of the local coordinate system into a world coordinate system.…”