Cataract Detection and Classification Systems Using Computational Intelligence: A Survey

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.

Automated summary

Computational intelligence is a powerful tool in solving complex problems in image processing, particularly in the detection and grading of cataracts, which can help prevent cataract surgery in the early stages. This study compares different algorithms in cataract grading and classification, providing a guide for researchers and doctors to select suitable methods for improving cataract detection.