Advertisement

Efficient Method for Locating Optic Disc in Diabetic Retinopathy Images

  • Aili Han
  • Anran Yang
  • Feilin Han
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10996)

Abstract

Diabetic retinopathy has no obvious symptoms at early stage, which leads to missing the best time for treatment. We apply image processing techniques to early diagnosis of diabetic retinopathy and present an efficient method of locating optic disc in fundus images. We first normalize the images in color, brightness, and exposure distribution to weaken the interference of pigment difference, uneven brightness and low contrast, and then extract the regions of interest in fundus images by the convolution of fundus images with a binary mask template to eliminate the influence of background on the accuracy of locating OD and decrease the computation amount. Next, we convert ROI into three grayscale images, in which the grayscale one from G channel is selected to locate OD since it is with the highest contrast and most original information. Finally, we create a universal template of optic disc for diabetic retinopathy images and design a fast method of locating OD in fundus images based on the OD template. The similarity between the OD template and the overlaid patch in fundus images is computed by means of correlation matching or standard correlation matching, and the position with maximal similarity is regarded as the center of OD. Experimental results demonstrate that our method is efficient and has a certain prospect of clinical application.

Keywords

Image processing Image detection Computer-aided diagnose Diabetic retinopathy 

Notes

Acknowledgments

This work is supported by the Natural Science Foundation of Shandong Province of China under Grant No. ZR2016FM20.

References

  1. 1.
    Zheng, S., Chen, J., Pan, L., et al.: A novel automatic detection method for macula center and optic disk in retinal images. J. Electron. Inf. Technol. 36(11), 2586–2592 (2014)Google Scholar
  2. 2.
    Ke, X., Jiang, W., Zhu, J.: Fast locating and segmentation of optic disk in fundus image based on visual attention. Sci. Technol. Eng. 15(35), 47–53 (2015)Google Scholar
  3. 3.
    Xiao, Z., Shao, Y., Zhang, F., et al.: Optic disc localization in color fundus images based on fundus structure feature. Chin. J. Biomed. Eng. 35(3), 257–263 (2016)Google Scholar
  4. 4.
    Salazar-Gonzalez, A.G., Kaba, D., Li, Y.M., et al.: Segmentation of the blood vessels and optic disk in retinal images. IEEE J. Biomed. Health Inform. 18(6), 1874–1886 (2014)Google Scholar
  5. 5.
    Foracchia, M., Grisan, E., Ruggeri, A.: Detection of optic disc in retinal images by means of a geometrical model of vessel structure. IEEE Trans. Med. Imaging 23(10), 1189–1195 (2004)CrossRefGoogle Scholar
  6. 6.
    Lalonde, M., Beaulieu, M., Gagnon, L.: Fast and robust optic disc detection using pyramidal decomposition and Hausdorff-based template matching. IEEE Trans. Med. Imaging 20(11), 1193–1200 (2001)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Department of Computer Science and TechnologyShandong UniversityWeihaiChina
  2. 2.College of Computer Science and TechnologyZhejiang UniversityHangzhouChina

Personalised recommendations