Framelet-Based Algorithm for Segmentation of Tubular Structures

  • Xiaohao Cai
  • Raymond H. Chan
  • Serena Morigi
  • Fiorella Sgallari
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6667)


Framelets have been used successfully in various problems in image processing, including inpainting, impulse noise removal, super-resolution image restoration, etc. Segmentation is the process of identifying object outlines within images. There are quite a few efficient algorithms for segmentation that depend on the partial differential equation modeling. In this paper, we apply the framelet-based approach to identify tube-like structures such as blood vessels in medical images. Our method iteratively refines a region that encloses the possible boundary or surface of the vessels. In each iteration, we apply the framelet-based algorithm to denoise and smooth the possible boundary and sharpen the region. Numerical experiments of real 2D/3D images demonstrate that the proposed method is very efficient and outperforms other existing methods.


Magnetic Resonance Angiography Binary Image Active Contour Tubular Structure Image Restoration 
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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Xiaohao Cai
    • 1
  • Raymond H. Chan
    • 1
  • Serena Morigi
    • 2
  • Fiorella Sgallari
    • 2
  1. 1.Department of MathematicsThe Chinese University of Hong KongShatinHong Kong
  2. 2.Department of Mathematics-CIRAMUniversity of BolognaBolognaItaly

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