An Overview of Retinal Blood Vessels Segmentation

  • Fatimatufaridah Jusoh
  • Habibollah HaronEmail author
  • Roliana Ibrahim
  • Mohd Zulfaezal Che Azemin
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 362)


In the recent past, the application of image processing in the fields of medicine and ophthalmology was widely used. Retina blood vessels are the only part of the human body that can be directly visualized non-invasively in vivo. Retina segmentation is important to help ophthalmologists detect various eyes diseases such as diabetic retinopathy, glaucoma, and age macular degeneration. Consequently, vessel segmentation is an important step in image analysis used to assess retinal abnormality. Vessel segmentation must be completed accurately to obtain good results for further image analysis. This paper reviews the algorithms used in previous studies on retinal vessel segmentation and discusses the problems associated with retina analysis.


Unsupervised Method Vessel Segmentation Retinal Blood Vessel Bifurcation Angle Vessel Tracking 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This material is based upon work supported by Fundamental Research Grant Scheme (FRGS), under Vote No. R.J130000.7828.4F537 and Ministry of Higher Education (MOHE). Any opinions, findings, and conclusions or recommendations expressed in this material are those from the authors and do not necessarily reflect the views of the Universiti Teknologi Malaysia.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Fatimatufaridah Jusoh
    • 1
  • Habibollah Haron
    • 1
    Email author
  • Roliana Ibrahim
    • 1
  • Mohd Zulfaezal Che Azemin
    • 2
  1. 1.Faculty of ComputingUniversity of Technology MalaysiaSkudaiMalaysia
  2. 2.Kulliyyah of Allied Health SciencesInternational Islamic University MalaysiaKuantanMalaysia

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