Selected parameters of the corneal deformation in the Corvis tonometer

Introduction: Contemporary ophthalmology knows many methods of measuring intraocular pressure, namely the methods of non-contact and impression applanation tonometry. In non-contact applanation tonometers, e.g. the Corvis, the corneal flattening is caused by an air puff. Image registration of the corneal deflection performed by a tonometer enables to determine other interesting biomechanical parameters of the eye, which are not available in the tonometer. The measurement of new selected parameters is presented in this paper. Material and method: Images with an M x N x I resolution of 200 x 576 x 140 pixels were acquired from the Corvis device in the source recording format *.cst. A total of 13'400 2D images of patients examined routinely in the Clinical Department of Ophthalmology, in District Railway Hospital in Katowice, Poland, were analysed in accordance with the Declaration of Helsinki. A new method has been proposed for the analysis of corneal deflection images in the Corvis tonometer with the use of the Canny edge detection method, mathematical morphology methods and context free operations. Results: The resulting image analysis tool allows determination of the response of the cornea and the entire eyeball to an air puff. The paper presents the method that enables the measurement of the amplitude of curvature changes in the frequency range from 150 to 500 Hz and automatic designation of the eyeball movement direction. The analysis of these data resulted in 3 new features of dynamics of the eye reaction to an air puff. Classification of these features enabled to propose 4 classes of deformation. The proposed algorithm allows to obtain reproducible results fully automatically at a time of 5 s per patient using the Core i5 CPU M460 @ 2.5GHz 4GB of RAM. Conclusions: The paper presents the possibility of using a profiled algorithm of image analysis, proposed by the authors, to measure additional cornea deformation parameters. The new tool enables automatic measurement of the additional new parameters when using the Corvis tonometer. A detailed clinical examination based on this method will be presented in subsequent paper

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

BACKGROUND: The Corvis® 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® 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® 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® 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® 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

Automatic method of analysis and measurement of additional parameters of corneal deformation in the Corvis tonometer

Introduction: The method for measuring intraocular pressure using the Corvis tonometer provides a sequence of images of corneal deformation. Deformations of the cornea are recorded using the ultra-high-speed Scheimpflug camera. This paper presents a new and reproducible method of analysis of corneal deformation images that allows for automatic measurements of new features, namely new three parameters unavailable in the original software. Material and method: The images subjected to processing had a resolution of 200 × 576 × 140 pixels. They were acquired from the Corvis tonometer and simulation. In total 14000 2D images were analysed. The image analysis method proposed by the author automatically detects the edge of the cornea and sclera fragments. For this purpose, new methods of image analysis and processing proposed by the author as well as those well-known, such as Canny filter, binarization, median filtering etc., have been used. The presented algorithms were implemented in Matlab (version 7.11.0.584 - R2010b) with Image Processing toolbox (version 7.1 -R2010b) using both known algorithms for image analysis and processing and those proposed by the author. Results: Owing to the proposed algorithm it is possible to determine three parameters: (1) the degree of the corneal reaction relative to the static position; (2) the corneal length changes; (3) the ratio of amplitude changes to the corneal deformation length. The corneal reaction is smaller by about 30.40% compared to its static position. The change in the corneal length during deformation is very small, approximately 1% of its original length. Parameter (3) enables to determine the applanation points with a correlation of 92% compared to the conventional method for calculating corneal flattening areas. The proposed algorithm provides reproducible results fully automatically within a few seconds/per patient using Core i7 processor. Conclusions: Using the proposed algorithm, it is possible to measure new, additional parameters of corneal deformation, which are not available in the original software. The presented analysis method provides three new parameters of the corneal reaction. Detailed clinical studies based on this method will be presented in subsequent papers

Novel dynamic corneal response parameters in a practice use: a critical review

Background: Non-contact tonometers based on the method using air puff and Scheimpflug’s fast camera are one of the latest devices allowing the measurement of intraocular pressure and additional biomechanical parameters of the cornea. Biomechanical features significantly affect changes in intraocular pressure values, as well as their changes, may indicate the possibility of corneal ectasia. This work presents the latest and already known biomechanical parameters available in the new offered software. The authors focused on their practical application and the diagnostic credibility indicated in the literature. Discussion: An overview of available literature indicates the importance of new dynamic corneal parameters. The latest parameters developed on the basis of biomechanics analysis of corneal deformation process, available in non-contact tonometers using Scheimpflug’s fast camera, are used in the evaluation of laser refractive surgery procedures, e.g. LASIK procedure. In addition, the assessment of changes in biomechanically corrected intraocular pressure confirms its independence from changes in the corneal biomechanics which may allow an intraocular pressure real assessment. The newly developed Corvis Biomechanical Index combined with the corneal tomography and topography assessment is an important aid in the classification of patients with keratoconus. Conclusion: New parameters characterising corneal deformation, including Corvis Biomechanical Index and biomechanical compensated intraocular pressure, significantly extend the diagnostic capabilities of this device and may be helpful in assessing corneal diseases of the eye. Nevertheless, further research is needed to confirm their diagnostic pertinence

Quantitative assessment of the impact of biomedical image acquisition on the results obtained from image analysis and processing

Introduction: Dedicated, automatic algorithms for image analysis and processing are becoming more and more common in medical diagnosis. When creating dedicated algorithms, many factors must be taken into consideration. They are associated with selecting the appropriate algorithm parameters and taking into account the impact of data acquisition on the results obtained. An important feature of algorithms is the possibility of their use in other medical units by other operators. This problem, namely operator's (acquisition) impact on the results obtained from image analysis and processing, has been shown on a few examples. Material and method: The analysed images were obtained from a variety of medical devices such as thermal imaging, tomography devices and those working in visible light. The objects of imaging were cellular elements, the anterior segment and fundus of the eye, postural defects and others. In total, almost 200'000 images coming from 8 different medical units were analysed. All image analysis algorithms were implemented in C and Matlab. Results: For various algorithms and methods of medical imaging, the impact of image acquisition on the results obtained is different. There are different levels of algorithm sensitivity to changes in the parameters, for example: (1) for microscope settings and the brightness assessment of cellular elements there is a difference of 8%; (2) for the thyroid ultrasound images there is a difference in marking the thyroid lobe area which results in a brightness assessment difference of 2%. The method of image acquisition in image analysis and processing also affects: (3) the accuracy of determining the temperature in the characteristic areas on the patient's back for the thermal method - error of 31%; (4) the accuracy of finding characteristic points in photogrammetric images when evaluating postural defects - error of 11%; (5) the accuracy of performing ablative and non-ablative treatments in cosmetology - error of 18% for the nose, 10% for the cheeks, and 7% for the forehead. Similarly, when: (7) measuring the anterior eye chamber - there is an error of 20%; (8) measuring the tooth enamel thickness - error of 15%; (9) evaluating the mechanical properties of the cornea during pressure measurement - error of 47%. Conclusions: The paper presents vital, selected issues occurring when assessing the accuracy of designed automatic algorithms for image analysis and processing in bioengineering. The impact of acquisition of images on the problems arising in their analysis has been shown on selected examples. It has also been indicated to which elements of image analysis and processing special attention should be paid in their design

Accurate Estimation of Intraocular Pressure and Corneal Material Behaviour Using a Non-Contact Method

The present study is quantifying the effect of corneal parameters(including corneal geometry and material stiffness) with potential considerable influence on intraocular pressure (IOP) and corneal material estimation using finite element method to develop biomechanically-corrected IOP algorithm and biomechanically estimated material algorithm on the non-contact tonometry to estimate higher accurate IOP (with a reduced effect of CCT and age) compared to device’s IOP measurement and the in-vivo corneal material behaviour (with a reduced effect of IOP). The CorVis-ST (Oculus, Wetzlar, Germany) measures IOP using high-speed Scheimpflug technology, which can record the deformation of the cornea during the air pressure application and use this information to define the relationship between the true IOP and dynamic response parameters obtained from CorVis-ST. Hence, in this study the OCULUS CorVis-ST was used for the development of a precise method for estimation of intraocular pressure and corneal material behaviour. Numerical analysis using the finite element method (FEM) had been adapted to represent the operation of the IOP measurement by using the CorVis-ST. The analysis considered the important biomechanical parameters of the eye including IOP, central corneal thickness (CCT), corneal geometry (central radius of curvature, Rc; and anterior corneal asphericity, P), and corneal material behaviour. The numerical simulation results demonstrated higher association of IOP predictions with the first applanation pressure (AP1) rather than CCT and corneal material stiffness (related to age), and higher association of corneal material properties with the ratio between corneal displacement and AP1. The numerical simulation results for healthy and Keratoconic eyes were used as a base to develop algorithms for estimating the true IOP with a reduced effect of CCT and corneal material stiffness, and corneal material behaviour (stress-strain relationship) with a reduced effect of the true IOP. Biomechanically-corrected IOP (bIOP) algorithms for both healthy and keratoconic eyes were validated in clinical data (including healthy, KC, and refractive surgery data) with the aim of significantly reducing IOP dependence on CCT and corneal biomechanics and in experimental ex-vivo human eye tests to assess the accuracy of the bIOP algorithms. The results of experimental ex-vivo human eye tests showed that bIOP had a higher accuracy than the IOP measurement using the CorVis-ST and exhibited no significant correlation with CCT (p=0.756), whereas CVS-IOP was significantly correlated with CCT (p 0.05), In addition, no significant difference in bIOP was found between pre- and post-operative data (0.1±2.1 mmHg, p=0.80 for LASIK and 0.8±1.8 mm Hg, P=0.273 for SMILE), whereas there were significant decreases after surgeries in GAT-IOP (-3.2±3.4 mmHg and -3.2±2.1 mmHg, respectively; both p 0.05) in the values of IOP between healthy and KC patients, using the bIOP and bIOPkc algorithms, while there was a significant difference with CVS-IOP (p0.05) and IOP (p>0.05) but was significantly correlated with age (p<0.01). The stiffness estimates and their variation with age were also significantly correlated (p<0.01) with stiffness estimates obtained in earlier studies on ex-vivo human tissue [1]. In addition, in KC eyes the β predications remain at approximately 80% of the normal cornea’s level. All developed algorithms for IOP and corneal material behaviour estimation demonstrated great success in significantly on providing close estimates of true IOP and corneal material behaviour and reducing the effect of corneal thickness and material stiffness on IOP measurement and the effect of IOP on the corneal material estimation