Retinal Image Segmentation Based on Multifractal Detrended Fluctuation Analysis

被引：0
|
作者：
Zhang S. [1 ]
She L.-H. [1 ]
Wang Y.-F. [1 ]
Su T. [1 ]
机构：
[1] School of Computer Science & Engineering, Northeastern University, Shenyang
来源：
Dongbei Daxue Xuebao/Journal of Northeastern University | 2019年 / 40卷 / 02期
关键词：
Detrended fluctuation analysis; Lesion image; Multifractal; Retina; Segmentation of blood vessel;
D O I：
10.12068/j.issn.1005-3026.2019.02.002
中图分类号：
学科分类号：
摘要：
A method based on multifractal detrended fluctuation analysis(DFA), which is adaptable for unsteady images, is introduced to segment retina images. In this method, histogram equalization is first used to precondition images for the enhancement of blood vessels, and then, the generalized Hurst index of images is calculated by multifractal DFA. The blood vessel index is used to segment the blood vessels. Finally, morphological postprocessing is used to get the final blood vessel images. Experiments based on DIARETDE0 and DIARETDE1 databases show that the proposed method has better integrity and connectivity in the treatment of retinal lesions, and it can extract the main body of blood vessels better, which has a good clinical value. © 2019, Editorial Department of Journal of Northeastern University. All right reserved.
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页码：158 / 163
页数：5
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