One of the most powerful tools in image processing solving complex problems is computational intelligence. There are several image classification methods but is uncertain which methods are most helpful for analyzing and classify images like ophthalmic. Particularly in the area of cataract, as a leading cause of blindness around the globe, only a few comprehensive reviews have summarized the ongoing efforts of computational intelligence in cataract detection and grading. By timely detection, it is possible to prevent cataract surgery in the initial stage of it. In this work, we compare the main characteristics of different algorithms in grading and classification, going from the classical medical methods to the actuals based on computational intelligence. These methods are explained in a simple manner trying to provide a mean to understand the operating principles and summarizing their relevant applications. This review may be considered as a useful guide for researchers and medicians in selecting a suitable method for improving cataract detection and grading, and to assist them in diagnosing this ophthalmic disease.

解决复杂问题的图像处理最强大的工具之一就是计算智能。有几种图像分类方法，但不确定哪种方法最有助于分析和分类像眼科图像。特别是在白内障方面，作为全球失明的主要原因，只有很少的综合评论总结了在白内障检测和分级中计算智能的持续努力。通过及时发现，可以在白内障手术的初期阶段就进行预防。在这项工作中，我们比较了从经典医学方法到基于计算智能的实际方法在分级和分类中不同算法的主要特征。这些方法以一种简单的方式进行了解释，试图提供一种理解操作原理并总结其相关应用的方法。这篇综述对于研究者和医生选择合适的方法来改善白内障的检测和分级，并帮助他们诊断这种眼科疾病，可被视为有用的指南。