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Interactive Browsing Systems for Large Image Collections Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Analysis of Retinal Vascular Biomarkers for Early Detection of Diabetes

Authors : Jiong Zhang, Behdad Dashtbozorg, Fan Huang, Tos T. J. M. Berendschot, Bart M. ter Haar Romeny

Published in: VipIMAGE 2017

Publisher: Springer International Publishing

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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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previous chapter Automated Blood Vessel Extraction Based on High-Order Local Autocorrelation Features on Retinal Images
next chapter Validation Study on Retinal Vessel Caliber Measurement Technique
Footnotes
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Metadata
Title
Analysis of Retinal Vascular Biomarkers for Early Detection of Diabetes
Authors
Jiong Zhang
Behdad Dashtbozorg
Fan Huang
Tos T. J. M. Berendschot
Bart M. ter Haar Romeny
Copyright Year
2018
Book
VipIMAGE 2017

Print ISBN: 978-3-319-68194-8

Electronic ISBN: 978-3-319-68195-5

Copyright Year: 2018

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