Koprowski Robert, Lyssek-Boron Anita, Nowinska Anna, Wylegala Edward, Kasprzak Henryk, Wrobel Zygmunt
Department of Biomedical Computer Systems, University of Silesia, Faculty of Computer Science and Materials Science, Institute of Computer Science, ul, Będzińska 39, Sosnowiec 41-200, Poland.
Biomed Eng Online. 2014 May 3;13:55. doi: 10.1186/1475-925X-13-55.
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.
Images with an M × N × I resolution of 200 × 576 × 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.
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.
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 papers.
当代眼科有许多测量眼压的方法,即非接触式和压陷式眼压测量法。在非接触式眼压计中,例如Corvis眼压计,角膜变平是由气流引起的。眼压计对角膜偏转进行图像记录,能够确定眼睛的其他有趣的生物力学参数,而这些参数在眼压计中是无法获得的。本文介绍了对新选定参数的测量。
以源记录格式*.cst从Corvis设备获取分辨率为200×576×140像素的M×N×I图像。按照《赫尔辛基宣言》对波兰卡托维兹地区铁路医院眼科临床科室常规检查的13400例患者的二维图像进行了分析。提出了一种新的方法,利用Canny边缘检测法、数学形态学方法和上下文无关运算来分析Corvis眼压计中的角膜偏转图像。
所得的图像分析工具能够确定角膜和整个眼球对气流的反应。本文介绍了一种能够测量150至500赫兹频率范围内曲率变化幅度并自动确定眼球运动方向的方法。对这些数据的分析得出了眼睛对气流反应动力学的3个新特征。对这些特征进行分类后提出了4种变形类别。所提出的算法能够在使用酷睿i5 CPU M460 @ 2.5GHz、4GB内存的情况下,以每位患者5秒的时间完全自动地获得可重复的结果。
本文介绍了使用作者提出的图像分析轮廓算法来测量额外角膜变形参数的可能性。这种新工具在使用Corvis眼压计时能够自动测量额外的新参数。后续论文将介绍基于该方法的详细临床检查。