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

Abstract

PurposeTo improve the reliability of corneal topographic data through the development of a method to estimate the magnitude of misalignment between successive corneal videokeratography (VK) maps and eliminate the effect of misalignment on the repeatability of topography data.MethodsAnterior and posterior topography maps were recorded twice for 124 healthy eyes of 124 participants using a Pentacam, and the repeatability of measurements was assessed by calculating the differences in elevation between each two sets of data. The repeatability of measurements was re-assessed following the determination of the magnitude of misalignment components (translational displacements: x0, y0 and z0, and rotational displacements: α, β and γ) between each two data sets and using them to modify the second data set within each pair based on an Iterative Closest Point (ICP) algorithm. The method simultaneously considered the anterior and posterior maps taken for the same eye since they were assumed to have the same set of misalignment components. A new parameter, named Combined Misalignment parameter (CM), has been developed to combine the effect of all six misalignment components on topography data and so enable study of the association between misalignment and the data repeatability test results.ResultsThe repeatability tests resulted in average root mean square (RMS) differences in elevation data of 8.46±2.75 μm before ICP map matching when simultaneously considering anterior and posterior surfaces. With map matching and misalignment correction, the differences decreased to 7.28±2.58 μm (P = 0.00). When applied to only the anterior maps, misalignment correction led to a more pronounced reduction in elevation data differences from 4.58±1.84 μm to 2.97±1.29 μm (P = 0.00). CM was found to be associated with the repeatability error (P = 0.00), with posterior maps being responsible for most of the error due to their relatively lower accuracy compared to anterior maps.ConclusionsThe ICP algorithm can be used to estimate, and effectively correct for, the potential misalignment between successive corneal videokeratography maps.

Repeatability of corneal elevation maps in keratoconus patients using the tomography matching method

“…In this study, an ICP algorithm, developed in earlier work 10 was used to estimate misalignment between each two successive tomography measurements. Correction for the small misalignments detected resulted in significantly reduced matching errors between successive maps from 18.43 ± 21.54 μm to 6.35 ± 4.58 μm (p < 0.01) in anterior KC maps and from 29.53 ± 24.62 μm to 19.62 ± 11.79 μm (p < 0.01) in posterior KC maps.…”

“…The device was moved back and realigned again after finishing each acquisition. Tomography measurements were taken by the same trained examiner (LFH), while the details were described in previous studies 10 , 32 . All methods were performed in accordance with the relevant guidelines and regulations.…”

“…A possible complication is that most tomography methods provide elevation data at a set of regularly-spaced discrete points, and therefore misalignment between successive measurements (either taken in the same setting to check repeatability or separated by a time period to check progression) can mean a different set of points is measured every time, leading to considerable differences in results. This study attempts to assess the effectiveness of a surface matching technology – an Iterative Closest Point (ICP) algorithm, developed in an earlier study 10 , 11 . As a feature-based surface matching technique and the dominant method for image registration, ICP checks the similarities between overlapping maps to determine the rigid-body transformations needed for the best possible match.…”

Evaluating the repeatability of corneal elevation through calculating the misalignment between Successive topography measurements during the follow up of LASIK

“…The ICP algorithm has been a dominant method for registration of 3D free-form surfaces, and was introduced successfully to match topography maps in a rapid process (within 1 to 2 seconds) 32–34 .…”

“…Since using six independent misalignment components makes it challenging to have an overall impression of correlation between misalignment and data repeatability, CM was developed to combine their individual effects on data repeatability 32 . RMS should be zero if the second successive measurements matched perfectly with the first, however, this is unlikely to occur in all cases.…”