Vivino M A, Mahurkar A, Trus B, Lopez M L, Datiles M
Computational Bioscience and Engineering Laboratory, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Eye (Lond). 1995;9 ( Pt 1):77-84. doi: 10.1038/eye.1995.12.
We have developed a semi-automated image processing system for analysis and evaluation of retroillumination images. This paper describes methods used to compensate for illumination variations in the images, separation of data into cataractous and non-cataractous portions, how quantitative measurements are made and how they assess the pathological condition. In addition to the traditional area measurement, this system computes the net integral of density and several measurements involving the location of the opacity in relation to the pupillary margin. The computer measures of area, integral of density, area centrality, weighted area, density centrality and weighted density provide more data than previously described systems. Data produced by this interactive and automated system can be used in studies of posterior subcapsular and cortical cataracts, and to study the effect of these opacities on vision.
我们开发了一种用于分析和评估视网膜图像的半自动图像处理系统。本文描述了用于补偿图像中光照变化的方法、将数据分离为白内障部分和非白内障部分的方法、如何进行定量测量以及这些测量如何评估病理状况。除了传统的面积测量外，该系统还计算密度的净积分以及涉及不透明度相对于瞳孔边缘位置的几个测量值。面积、密度积分、面积中心度、加权面积、密度中心度和加权密度的计算机测量提供了比先前描述的系统更多的数据。这个交互式自动化系统产生的数据可用于后囊下和皮质性白内障的研究，以及研究这些不透明度对视力的影响。
