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Analysis of Retinal Vascular Biomarkers for Early Detection of Diabetes

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VipIMAGE 2017 (ECCOMAS 2017)

Part of the book series: Lecture Notes in Computational Vision and Biomechanics ((LNCVB,volume 27))

Abstract

This paper presents an automated retinal vessel analysis system for the measurement and statistical analysis of vascular biomarkers. The proposed retinal vessel enhancement, segmentation, optic disc and fovea detection algorithms provide fundamental tools for extracting the vascular network within the predefined region of interest (ROI). Based on that, the artery/vein classification, vessel caliber, curvature and fractal dimension measurement tools are used to assess the quantitative vascular biomarkers: width, tortuosity, and fractal dimension. A statistical analysis on the extracted geometric biomarkers is set up using a dataset provided by the Maastricht study with the aim of exploring the associations between different vessel biomarkers and type 2 diabetes mellitus. A linear regression analysis is used to model the relationships between different factors. The results indicate that the vascular biomarker variables have associations with diabetes. These findings demonstrate the possibility of applying the proposed pipeline tools on further analysis of vessel biomarkers for the computer-aided diagnosis.

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Notes

  1. 1.

    http://www.retinacheck.org/.

  2. 2.

    https://www.demaastrichtstudie.nl/research.

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Acknowledgements

This work is part of the NWO-Hé Programme of Innovation Cooperation No. 629.001.003 and the European Foundation for the Study of Diabetes/Chinese Diabetes Society/Lilly project.

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Authors and Affiliations

  1. Department of Biomedical Engineering, Eindhoven University of Technology, 5600MB, Eindhoven, The Netherlands

    Jiong Zhang, Behdad Dashtbozorg, Fan Huang & Bart M. ter Haar Romeny

  2. University Eye Clinic Maastricht, Maastricht, The Netherlands

    Tos T. J. M. Berendschot

  3. Department of Biomedical and Information Engineering, Northeastern University, Shenyang, 110000, China

    Bart M. ter Haar Romeny

Authors
  1. Jiong Zhang
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  2. Behdad Dashtbozorg
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  3. Fan Huang
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  4. Tos T. J. M. Berendschot
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  5. Bart M. ter Haar Romeny
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Corresponding author

Correspondence to Jiong Zhang .

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Editors and Affiliations

  1. Universidade do Porto, Porto, Portugal

    João Manuel R.S. Tavares

  2. Universidade do Porto, Porto, Portugal

    R.M. Natal Jorge

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Zhang, J., Dashtbozorg, B., Huang, F., Berendschot, T.T.J.M., ter Haar Romeny, B.M. (2018). Analysis of Retinal Vascular Biomarkers for Early Detection of Diabetes. In: Tavares, J., Natal Jorge, R. (eds) VipIMAGE 2017. ECCOMAS 2017. Lecture Notes in Computational Vision and Biomechanics, vol 27. Springer, Cham. https://doi.org/10.1007/978-3-319-68195-5_88

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  • DOI: https://doi.org/10.1007/978-3-319-68195-5_88

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68194-8

  • Online ISBN: 978-3-319-68195-5

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