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Analysis on Image Processing Technology-based Diabetic Retinopathy

Received: 10 August 2019    Accepted: 29 August 2019    Published: 16 September 2019
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Abstract

Diabetic retinopathy is a dangerous eye disease which causes the blindness widely in the human society. It arises due to high sugar level in the blood. The eye disease caused due to the diabetes is called diabetic retinopathy. The symptoms of diabetic retinopathy are red lesions such as microaneurysms (MA), intraretinal hemorrhages and bright lesions such as exudates, cotton wool spots and blood vessels. Microaneurysm (MA) is one of the features of the diabetic retinopathy. They are discrete, localized saccular distensions of the weakened capillary walls and appear as small round dark red dots on the retinal surface. According to the medical definition of MA, it is a reddish, circular pattern with a diameter λ is less than 125μm. Microaneurysms are mostly found near thin blood vessels, but cannot actually be located on the blood vessels. According to the number of microaneurysms, the diabetic retinopathy can be classified as mild stage, moderate stage and the severe stage. To detect the microaneurysms, the optic disc and the blood vessels are firstly detected because they are normal features of the image. And also, in the detection of microaneurysms the pre-processing stage is very important. In the pre-processing stage, the filtering techniques and the histogram equalization techniques are applied to reduce the effect of noise and uneven illumination cases. To detect the optic disc, blood vessels and the microaneurysms, the mathematical morphological method is applied. The result of this research can help in the screening of diabetic retinopathy.

Published in International Journal of Biomedical Science and Engineering (Volume 7, Issue 2)
DOI 10.11648/j.ijbse.20190702.13
Page(s) 45-60
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Image Processing Technology, Diabetic Retinopathy, Biomedical Engineering, Life Science, Medical Research

References
[1] Anonymous, “The Berries: Diabetic Retinopathy”, Accessed August 4, 2013, http://www.theberries.ns.ca/ARchives/2006Winter/diabetic_retinopathy.html.
[2] Anonymous, “My Eye World: Eye Structure and function.” Referenced, August 2nd 2013, http://www.myeyeworld.com/files/eye_structure.htm.
[3] SujithKumar S B, and Vipula Singh “Automatic Detection of Diabetic Retinopathy in Non-dilated RGB Retinal Fundus Images” International Journal of Computer Applications (0975-888) Vol 47–19, June 2012.
[4] Diego Marín, Arturo Aquino, Manuel Emilio Gegúndez-Arias, and José Manuel Bravo, “A New Supervised Method for Blood Vessel Segmentation in Retinal Images by Using Gray-Level and Moment Invariants-Based Features”, IEEE transactions on medical imaging, vol. 30, pp. 146-158, 2011.
[5] BálintAntal, IstvánLázár, AndrásHajdu “Novel Approaches to Improve Microaneurysm Detection in Retinal Images” Proceedings of the 8th International Conference on Applied Informatics Eger, Hungary, January 27–30, 2010. Vol. 1. pp. 149–156.
[6] B. Dupas, T. Walter, A. Erginay et al., “Evaluation of automated fundus photograph analysis algorithms for detecting microaneurysms, haemorrhages and exudates, and of a computer-assisted diagnostic system for grading diabetic retinopathy,” Diabetes & Metabolism 36 (3), 2010, pp. 213-220.
[7] B´alintAntal, and Andr´asHajdu “Improving microaneurysms detection in color fundus images by using an optimal combination of preprocessingmethods and candidate extractors” 18th European Signal Processing Conference (EUSIPCO-2010) Aalborg, Denmark, August 23-27, 2010.
[8] S. Jayaraman: Digital Image Processing; 3 edition ISBN(10): 0-07014479-6: 2010.
[9] Lei Zhang, Qin Li, Jane You, and David Zhang, “A Modified Matched Filter With Double-Sided Thresholding for Screening Proliferative Diabetic Retinopathy”, IEEE Transactions On Information Technology In Biomedicine, Vol. 13, No. 4, pp. 528-534, July 2009.
[10] Sight Savers: The structure of the human eye. Accessed, August 2, 2006, from website: http://www.sightwavers.or.uk/html/eyeconditions/huma_eye_detailed.htm.
[11] Xiaohui, Z., and Chutatape, O., “Detection and classification of bright lexions in colour fundus images”, Int. Conference on Image Processing, Vol 1, pp 139-142, Oct 2004.
[12] Vallabha, D., Dorairaj, R., Namuduri K. R., and Thompson, H., "Automated Detection and Classification of Vascular Abnormalities in Diabetic Retinopathy", 38th Asilomar Conference on Signals, Systems and Computers, November 2004.
[13] Joes Staal, Michael D. Abràmoff, MeindertNiemeijer, Max A. Viergever, and Bram van Ginneken, “Ridge-Based Vessel Segmentation in Color Images of the Retina”, IEEE Transactions On Medical Imaging, Vol. 23, No. 4, pp. 501-509, April 2004.
[14] Rafael C. Gonzalez and Richard E. Woods.“Digital Image Processing using MATLAB”, 2nd edition. Prentice Hall, 2002. ISBN 0-201-18075-8.
[15] Junichiro Hayashi, TakamitsuKunieda, Joshua Cole, Ryusuke Soga, Yuji Hatanaka, Miao Lu, Takeshi Hara and Hiroshi Fujita: A development of computer-aided diagnosis system using fundus images. Proceeding of the 7th International Conference on Virtual Systems and MultiMedia (VSMM 2001), pp. 429-438 (2001).
[16] Reza. C, C. Chauduri, “Detection of blood vessels in retinal images using two dimensional Matched filter”, IEEE transactions on medical imaging, vol. 8, pp 263-269, 1989.
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    Hla Myo Tun. (2019). Analysis on Image Processing Technology-based Diabetic Retinopathy. International Journal of Biomedical Science and Engineering, 7(2), 45-60. https://doi.org/10.11648/j.ijbse.20190702.13

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    ACS Style

    Hla Myo Tun. Analysis on Image Processing Technology-based Diabetic Retinopathy. Int. J. Biomed. Sci. Eng. 2019, 7(2), 45-60. doi: 10.11648/j.ijbse.20190702.13

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    AMA Style

    Hla Myo Tun. Analysis on Image Processing Technology-based Diabetic Retinopathy. Int J Biomed Sci Eng. 2019;7(2):45-60. doi: 10.11648/j.ijbse.20190702.13

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  • @article{10.11648/j.ijbse.20190702.13,
      author = {Hla Myo Tun},
      title = {Analysis on Image Processing Technology-based Diabetic Retinopathy},
      journal = {International Journal of Biomedical Science and Engineering},
      volume = {7},
      number = {2},
      pages = {45-60},
      doi = {10.11648/j.ijbse.20190702.13},
      url = {https://doi.org/10.11648/j.ijbse.20190702.13},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijbse.20190702.13},
      abstract = {Diabetic retinopathy is a dangerous eye disease which causes the blindness widely in the human society. It arises due to high sugar level in the blood. The eye disease caused due to the diabetes is called diabetic retinopathy. The symptoms of diabetic retinopathy are red lesions such as microaneurysms (MA), intraretinal hemorrhages and bright lesions such as exudates, cotton wool spots and blood vessels. Microaneurysm (MA) is one of the features of the diabetic retinopathy. They are discrete, localized saccular distensions of the weakened capillary walls and appear as small round dark red dots on the retinal surface. According to the medical definition of MA, it is a reddish, circular pattern with a diameter λ is less than 125μm. Microaneurysms are mostly found near thin blood vessels, but cannot actually be located on the blood vessels. According to the number of microaneurysms, the diabetic retinopathy can be classified as mild stage, moderate stage and the severe stage. To detect the microaneurysms, the optic disc and the blood vessels are firstly detected because they are normal features of the image. And also, in the detection of microaneurysms the pre-processing stage is very important. In the pre-processing stage, the filtering techniques and the histogram equalization techniques are applied to reduce the effect of noise and uneven illumination cases. To detect the optic disc, blood vessels and the microaneurysms, the mathematical morphological method is applied. The result of this research can help in the screening of diabetic retinopathy.},
     year = {2019}
    }
    

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  • TY  - JOUR
    T1  - Analysis on Image Processing Technology-based Diabetic Retinopathy
    AU  - Hla Myo Tun
    Y1  - 2019/09/16
    PY  - 2019
    N1  - https://doi.org/10.11648/j.ijbse.20190702.13
    DO  - 10.11648/j.ijbse.20190702.13
    T2  - International Journal of Biomedical Science and Engineering
    JF  - International Journal of Biomedical Science and Engineering
    JO  - International Journal of Biomedical Science and Engineering
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    PB  - Science Publishing Group
    SN  - 2376-7235
    UR  - https://doi.org/10.11648/j.ijbse.20190702.13
    AB  - Diabetic retinopathy is a dangerous eye disease which causes the blindness widely in the human society. It arises due to high sugar level in the blood. The eye disease caused due to the diabetes is called diabetic retinopathy. The symptoms of diabetic retinopathy are red lesions such as microaneurysms (MA), intraretinal hemorrhages and bright lesions such as exudates, cotton wool spots and blood vessels. Microaneurysm (MA) is one of the features of the diabetic retinopathy. They are discrete, localized saccular distensions of the weakened capillary walls and appear as small round dark red dots on the retinal surface. According to the medical definition of MA, it is a reddish, circular pattern with a diameter λ is less than 125μm. Microaneurysms are mostly found near thin blood vessels, but cannot actually be located on the blood vessels. According to the number of microaneurysms, the diabetic retinopathy can be classified as mild stage, moderate stage and the severe stage. To detect the microaneurysms, the optic disc and the blood vessels are firstly detected because they are normal features of the image. And also, in the detection of microaneurysms the pre-processing stage is very important. In the pre-processing stage, the filtering techniques and the histogram equalization techniques are applied to reduce the effect of noise and uneven illumination cases. To detect the optic disc, blood vessels and the microaneurysms, the mathematical morphological method is applied. The result of this research can help in the screening of diabetic retinopathy.
    VL  - 7
    IS  - 2
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Author Information
  • Department of Electronic Engineering, Yangon Technological University, Yangon, Myanmar

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