doi:

DOI: 10.3724/SP.J.1249.2017.03290

Journal of Shenzhen University Science and Engineering (深圳大学学报理工版) 2017/34:3 PP.290-299

Classification methods for diabetic retinopathy fromretinal images


Abstract:
This paper reviews the existing automatic classification methods of diabetic retinopathy (DR). There are two kinds of methods for DR fundus image classification. One is based on local lesions, and the other is based on global image information. The former mainly detects some specific lesions, such as exudation, hemorrhage and microaneurysm, and then performs image classification according to the type, location and number of these lesions. The latter classifies fundus images using global image features. Besides, this paper summarizes commonly used public datasets, advantages and disadvantages of some classification algorithms and their performances. Although many research works have been focused on developing algorithms for automatically classifying DR fundus images, there are still many challenges to develop a universal computer-aided diagnosis system for automatic DR classification. The challenges include acquiring lots of high-quality DR fundus images, designing robust algorithms and improving the total performance of the system.

Key words:image processing,fundus images,diabetic retinopathy (DR),computer-aided diagnosis,automatic detection,image classification

ReleaseDate:2017-06-16 14:08:44



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