Aarhus University Seal

Width-wise vessel bifurcation for improved retinal vessel segmentation

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

  • Tariq M. Khan, University of New South Wales
  • ,
  • Mohammad A.U. Khan, Namal Institute, Effat University
  • ,
  • Naveed Ur Rehman
  • Khuram Naveed
  • Imran Uddin Afridi, COMSATS Institute of Information Technology
  • ,
  • Syed Saud Naqvi, COMSATS Institute of Information Technology
  • ,
  • Imran Raazak, University of New South Wales

Vessel local characteristics such as noise, illumination, and direction vary significantly in a fundus image, making it difficult to segment the vessel tree structure as a whole. To facilitate vessel detection, an alternative procedure proposed here, whereby retinal vessels first classified into two categories, large and small. Then, for its unique characteristics, each group has been processed with its own enhancement and detection filter. The sensitivity of the proposed method is boosted by capturing tiny vessels through a directional filter bank followed by its associated triple-stick filtering. Additionally, the specificity of the proposed method is enhanced through noise suppression attributed largely to the proposed BM3D filtering and multi-scale line detection approach. As a result, the detection accuracy on the DRIVE, STARE, and CHASE DB1 datasets is significantly improved, with scores of 0.9610, 0.9586, and 0.9578, respectively.

Original languageEnglish
Article number103169
JournalBiomedical Signal Processing and Control
IssuePart A
Number of pages11
Publication statusPublished - Jan 2022

Bibliographical note

Publisher Copyright:
© 2021 Elsevier Ltd

    Research areas

  • Diabetic retinopathy, Multiscale line detector, Retinal vessels, Triple stick filter

See relations at Aarhus University Citationformats

ID: 262967938