advanced
Chun-Yuan Yu, Chia-Jen Chang, Yen-Ju Yao, Shyr-Shen Yu. Automatic Vessel Segmentation on Retinal Images[J]. Journal of Electronic Science and Technology, 2014, 12(4): 400-404. DOI: 10.3969/j.issn.1674-862X.2014.04.011
Citation: Chun-Yuan Yu, Chia-Jen Chang, Yen-Ju Yao, Shyr-Shen Yu. Automatic Vessel Segmentation on Retinal Images[J]. Journal of Electronic Science and Technology, 2014, 12(4): 400-404. DOI: 10.3969/j.issn.1674-862X.2014.04.011
shu

Automatic Vessel Segmentation on Retinal Images

doi: 10.3969/j.issn.1674-862X.2014.04.011
  • 1.

    Department of Digital Living Innovation,Nan Kai University of Technology,Tsaotun;

  • 2.

    Department of Computer Science and Engineering,National Chung-Hsing University,Taichung;

  • 3.

    Department of Ophthalmology,Taichung Veterans General Hospital,Taichung

Funds: 

This work was supported by the NSC under Grant NSC 102-2221-E-005-082.

More Information
  • Author Bio:

    Chun-Yuan Yu research interests focus on medical image processing, programming, and pattern recognition, t112@nkut.edu.tw;
    Shyr-Shen Yu research work focuses on image processing, bioinformatics, pattern recognition, and data mining, pyu@nchu.edu.tw;
    Chia-Jen Chang, capmchang@seed.net.tw;
    Yen-Ju Yao, lisa79517@hotmail.com

    Chun-Yuan Yu research interests focus on medical image processing, programming, and pattern recognition, t112@nkut.edu.tw;
    Shyr-Shen Yu research work focuses on image processing, bioinformatics, pattern recognition, and data mining, pyu@nchu.edu.tw;
    Chia-Jen Chang, capmchang@seed.net.tw;
    Yen-Ju Yao, lisa79517@hotmail.com

    Chun-Yuan Yu research interests focus on medical image processing, programming, and pattern recognition, t112@nkut.edu.tw;
    Shyr-Shen Yu research work focuses on image processing, bioinformatics, pattern recognition, and data mining, pyu@nchu.edu.tw;
    Chia-Jen Chang, capmchang@seed.net.tw;
    Yen-Ju Yao, lisa79517@hotmail.com

    Chun-Yuan Yu research interests focus on medical image processing, programming, and pattern recognition, t112@nkut.edu.tw;
    Shyr-Shen Yu research work focuses on image processing, bioinformatics, pattern recognition, and data mining, pyu@nchu.edu.tw;
    Chia-Jen Chang, capmchang@seed.net.tw;
    Yen-Ju Yao, lisa79517@hotmail.com

  • Authors’ information: Shyr-Shen Yu
  • Received Date: 2013-12-12
  • Rev Recd Date: 2014-03-13
  • Publish Date: 2014-12-24
    Abstract
  • Several features of retinal vessels can be used to monitor the progression of diseases. Changes in vascular structures, for example, vessel caliber, branching angle, and tortuosity, are portents of many diseases such as diabetic retinopathy and arterial hypertension. This paper proposes an automatic retinal vessel segmentation method based on morphological closing and multi-scale line detection. First, an illumination correction is performed on the green band retinal image. Next, the morphological closing and subtraction processing are applied to obtain the crude retinal vessel image. Then, the multi-scale line detection is used to fine the vessel image. Finally, the binary vasculature is extracted by the Otsu algorithm. In this paper, for improving the drawbacks of multi-scale line detection, only the line detectors at 4 scales are used. The experimental results show that the accuracy is 0.939 for DRIVE (digital retinal images for vessel extraction) retinal database, which is much better than other methods.
    • FullText(HTML)
    • References(0)
    • Relative Articles

  • Related Articles

    [1]Zenebe Markos Lonseko, Cheng-Si Luo, Wen-Ju Du, Tao Gan, Lin-Lin Zhu, Prince Ebenezer Adjei, Ni-Ni Rao. Early esophagus cancer segmentation from gastrointestinal endoscopic images based on U-Net++ model[J]. Journal of Electronic Science and Technology, 2023, 21(3): 100205. DOI: 10.1016/j.jnlest.2023.100205
    [2]Tian-Chi Zhang, Jing Zhang, Jian-Pei Zhang, He Wang. Review of Methods of Image Segmentation Based on Quantum Mechanics[J]. Journal of Electronic Science and Technology, 2018, 16(3): 243-252. DOI: 10.11989/JEST.1674-862X.71013122
    [3]Quang-Phuoc Nguyen, Joon-Choul Shin, Cheol-Young Ock. Korean Morphological Analysis for Korean-Vietnamese Statistical Machine Translation[J]. Journal of Electronic Science and Technology, 2017, 15(4): 413-419. DOI: 10.11989/JEST.1674-862X.61005104
    [4]Yung-Chen Chou, Huang-Ching Li. High Payload Reversible Data Hiding Scheme Using Difference Segmentation and Histogram Shifting[J]. Journal of Electronic Science and Technology, 2013, 11(1): 9-14. DOI: 10.3969/j.issn.1674-862X.2013.01.003
    [5]Quang Tung Thieu, Marie Luong, Jean-Marie Rocchisani, Nguyen Linh-Trung, Emmanuel Viennet. Novel Active Contour Model for Image Segmentation Based on Local Fuzzy Gaussian Distribution Fitting[J]. Journal of Electronic Science and Technology, 2012, 10(2): 113-118. DOI: 10.3969/j.issn.1674-862X.2012.02.004
    [6]Xin-Yu Du, Yong-Jie Li, Cheng Luo, De-Zhong Yao. Elitist Reconstruction Genetic Algorithm Based on Markov Random Field for Magnetic Resonance Image Segmentation[J]. Journal of Electronic Science and Technology, 2012, 10(1): 83-87. DOI: 10.3969/j.issn.1674-862X.2012.01.015
    [7]Jin Qi. A Novel Adaptive Approach to Process Binary Fingerprint Images Using Directional Morphological Operations[J]. Journal of Electronic Science and Technology, 2009, 7(2): 129-131.
    [8]Jian-Wei Zhong, Mei Xie. A Fingerprint Minutiae Matching Method Based on Line Segment Vector[J]. Journal of Electronic Science and Technology, 2007, 5(3): 260-263.
    [9]XU Hai-xiang, ZHU Guang-xi, TIAN Jin-wen, ZHANG Xiang, PENG Fu-yuan. Image Segmentation Based on Support Vector Machine[J]. Journal of Electronic Science and Technology, 2005, 3(3): 226-230.
    [10]XU Jie, GUO Xing-ting, ZHAO Ji-dong. A Pre-Segmented Sharing Recovery Scheme for MPLS/GMPLS[J]. Journal of Electronic Science and Technology, 2004, 2(4): 53-59.
    • Supplements (0)

    • Catalog

      Get Citation
      PDF
      XML

      Article Metrics

      Article views (317) PDF downloads (36) Cited by()
      Related
      Proportional views

      Copyright 2008-2016 JEST All Rights Reserved

      Supported by: Beijing Renhe Information Technology Co. Ltd 

      /

      DownLoad:  Full-Size Img  PowerPoint
      Return
      Return