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

机译:一种从超快速Scheimpflum相机检测图像中外角膜轮廓的新方法

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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. 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. 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.
机译:corvis? St Tonometer是一种创新装置,通过将经典的非联系眼压计与超快速的Scheimpflug摄像头相结合,提供了许多参数,可以评估角膜生物力学。获得的生物力学参数改善了所选眼部疾病的医学诊断。生物力学测量中的一个关键元件是正确的角膜轮廓检测,这是进一步计算的基础。本研究涉及基于来自上述装置的一系列图像的外角膜边缘检测问题。角膜轮廓检测是角膜动态参数采集和分析的第一和极其重要的阶段。 Corvis共有15,400张图片?分析了ST Tonometer从110名患者获得常规眼科检查的患者。基于来自Corvis的一系列图像的外角膜边缘检测方法? ST是提出的。该方法与已知的和常用的边缘探测器进行比较:Sobel,Roberts和Canny运算符,以及文献中已知的其他人。分析在matlab中进行?版本9.0.0.341360(R2016A)使用图像处理工具箱(9.4版)和神经网络工具箱(版本9.0)。本文介绍的方法提供了平均误差(0.16%),稳定性(标准偏差0.19%)和对噪声抗性的最小值,对Corvis的特征?与文献中已知的方法相比,St Tonoxetry测试。误差为5.78?±9.19%,3.43?±6.21%,以及罗伯特,Sobel和Canny方法的1.26?±3.11%。所提出的用于检测外角膜轮廓的新方法增加了眼内压力测量的精度。它可用于分析角膜的动态参数。

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