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Arquivos Brasileiros de Oftalmologia

Print version ISSN 0004-2749On-line version ISSN 1678-2925


CARVALHO, Luis Alberto Vieira de  and  BRUNO, Odemir Martinez. Different techniques for Plácido image analysis may improve precision of videokeratography. Arq. Bras. Oftalmol. [online]. 2005, vol.68, n.6, pp.797-805. ISSN 1678-2925.

PURPOSE: Videokeratography (VK) has been a widespread technology for corneal surface analysis since the mid-80s. The objective of this study was to develop different techniques for Plácido image edge detection and compare the results of each algorithm in terms of the consequences for axial curvature computations. METHODS: Plácido images from an Eyesys system 2000 were captured for 4 different spherical surfaces.Each image was saved in bitmap format at the hard disk of an IBM computer. Six different image-processing algorithms were developed using different techniques well-documented in the literature. The six methods were as follows: (1) First order numerical derivative, (2) First and (3) Second order Fourier derivative, (4) the Marr-Hildreth filter, (5) Canny's Method, (6) Mathematical morphology. Each algorithm was tested on each of the Plácido images. RESULTS: Edge radial distance from center of Plácido image was compared for each algorithm and a computer simulation of the videokeratography system. Mean deviation in terms of pixels/millimeters/dioptric power for all spheres for methods (1)-(6) were, respectively: (1) 33.1695/0.7961/0.79, (2) 32.79/0.7870/0.7724, (3) 60.7150/1.4572/1.4192, (4)18.97/0.4553/0.4572, (5) 46.33/1.1119/1.0917, (6) 20.55/0.4932/0.48. CONCLUSION: Researchers and clinical ophthalmologists should be more careful when choosing commercial videokeratographs and also when comparing measurements of different instruments, given that there may be differences associated with the image processing technique. We have shown here that the Marr/Hildreth (method (4)) image processing method is more precise than other methods such as Fourier or first order numerical methods.

Keywords : Corneal topography [instrumentation]; Algorithms; Cornea [anatomy & histology]; Image processing computer-assisted.

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