Robust and Fast Vessel Segmentation via Gaussian Derivatives in Orientation Scores

  • Jiong ZhangEmail author
  • Erik Bekkers
  • Samaneh Abbasi
  • Behdad Dashtbozorg
  • Bart ter Haar Romeny
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9279)


We propose a robust and fully automatic matched filter-based method for retinal vessel segmentation. Different from conventional filters in 2D image domains, we construct a new matched filter based on second-order Gaussian derivatives in so-called orientation scores, functions on the coupled space of position and orientations \(\mathbb {R}^2 \rtimes S^1\). We lift 2D images to 3D orientation scores by means of a wavelet-type transform using an anisotropic wavelet. In the domain \(\mathbb {R}^2 \rtimes S^1\), we set up rotation and translation invariant second-order Gaussian derivatives. By locally matching the multi-scale second order Gaussian derivative filters with data in orientation scores, we are able to enhance vessel-like structures located in different orientation planes accordingly. Both crossings and tiny vessels are well-preserved due to the proposed multi-scale and multi-orientation filtering method. The proposed method is validated on public databases DRIVE and STARE, and we show that the method is both fast and reliable. With respectively a sensitivity and specificity of 0.7744 and 0.9708 on DRIVE, and 0.7940 and 0.9707 on STARE, our method gives improved performance compared to state-of-the-art algorithms.


Retinal vessel segmentation Matched filter Gaussian derivatives Orientation scores Crossing preservation Micro-vasculature 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Jiong Zhang
    • 1
    Email author
  • Erik Bekkers
    • 1
  • Samaneh Abbasi
    • 1
  • Behdad Dashtbozorg
    • 1
  • Bart ter Haar Romeny
    • 1
    • 2
  1. 1.Department of Biomedical EngineeringEindhoven University of TechnologyEindhovenThe Netherlands
  2. 2.Department of Biomedical and Information EngineeringNortheastern UniversityShenyangChina

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