Koprowski Robert
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 Nov 19;13:150. doi: 10.1186/1475-925X-13-150.
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.
The images subjected to processing had a resolution of 200 × 576 × 140 pixels. They were acquired from the Corvis tonometer and simulation. In total 14,000 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.
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.
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.
使用Corvis眼压计测量眼压的方法可提供一系列角膜变形图像。角膜变形通过超高速Scheimpflug相机进行记录。本文提出了一种全新且可重复的角膜变形图像分析方法,该方法能够自动测量新的特征,即原始软件中无法获取的三个新参数。
用于处理的图像分辨率为200×576×140像素。这些图像来自Corvis眼压计及模拟。总共分析了14000张二维图像。作者提出的图像分析方法可自动检测角膜和巩膜碎片的边缘。为此,使用了作者提出的以及诸如Canny滤波器、二值化、中值滤波等知名的图像分析与处理新方法。所展示的算法在Matlab(版本7.11.0.584 - R2010b)及图像处理工具箱(版本7.1 - R2010b)中实现,同时使用了已知的图像分析与处理算法以及作者提出的算法。
由于所提出的算法,可以确定三个参数:(1)角膜相对于静态位置的反应程度;(2)角膜长度变化;(3)振幅变化与角膜变形长度的比值。与静态位置相比,角膜反应小约30.40%。变形过程中角膜长度的变化非常小,约为其原始长度的1%。参数(3)能够确定压平点,与计算角膜压平面积的传统方法相比,相关性为92%。所提出的算法使用酷睿i7处理器,能在几秒内为每位患者完全自动地提供可重复的结果。
使用所提出的算法,可以测量原始软件中无法获取的新的、额外的角膜变形参数。所展示的分析方法提供了角膜反应的三个新参数。基于此方法的详细临床研究将在后续论文中呈现。