A new method for detecting the outer corneal contour in images from an ultra-fast Scheimpflug camera

Background: The Corvis (R) ST tonometer is an innovative device which, by combining a classic non-contact tonometer with an ultra-fast Scheimpflug camera, provides a number of parameters allowing for the assessment of corneal biomechanics. The acquired biomechanical parameters improve medical diagnosis of selected eye diseases. One of the key elements in biomechanical measurements is the correct corneal contour detection, which is the basis for further calculations. The presented study deals with the problem of outer corneal edge detection based on a series of images from the afore-mentioned device. Corneal contour detection is the first and extremely important stage in the acquisition and analysis of corneal dynamic parameters. Result: A total of 15,400 images from the Corvis (R) ST tonometer acquired from 110 patients undergoing routine ophthalmologic examinations were analysed. A method of outer corneal edge detection on the basis of a series of images from the Corvis (R) ST was proposed. The method was compared with known and commonly used edge detectors: Sobel, Roberts, and Canny operators, as well as others, known from the literature. The analysis was carried out in MATLAB (R) version 9.0.0.341360 (R2016a) with the Image Processing Toolbox (version 9.4) and the Neural Network Toolbox (version 9.0). The method presented in this paper provided the smallest values of the mean error (0.16%), stability (standard deviation 0.19%) and resistance to noise, characteristic for Corvis (R) ST tonometry tests, compared to the methods known from the literature. The errors were 5.78 +/- 9.19%, 3.43 +/- 6.21%, and 1.26 +/- 3.11% for the Roberts, Sobel, and Canny methods, respectively. Conclusions: The proposed new method for detecting the outer corneal contour increases the accuracy of intraocular pressure measurements. It can be used to analyse dynamic parameters of the cornea.