Locating vessel centerlines in retinal images using wavelet transform: a multilevel approach

  • Authors:
  • Xinge You;Bin Fang;Yuan Yan Tang;Zhenyu He;Jian Huang

  • Affiliations:
  • Faculty of Mathematics and Computer Science, Hubei University, P.R. China;Faculty of Mathematics and Computer Science, Hubei University, P.R. China;Faculty of Mathematics and Computer Science, Hubei University, P.R. China;Department of Computer Science, Hong Kong Baptist University;Department of Computer Science, Hong Kong Baptist University

  • Venue:
  • ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part I
  • Year:
  • 2005

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Abstract

Identifying centerlines of vessels in the retinal image is helpful to provide useful information in diagnosis of eye diseases and early signs of systemic disease. This paper presents a novel thinning method based on the wavelet transform with a multilevel scheme. The development of the method is inspired by the favorable characteristics of wavelet transform moduli. Mathematical analysis is given to show that the vessel edge and centerline can be detected efficiently by computing the maxima and minima of wavelet transform moduli. The implementation is performed by applying various scale sizes of the wavelet transform to thin the multiple-pixel-wide ribbon-like vessel gradually to be one-pixel-wide centerline. Experiment results show that the identified centerline of vascular trees are accurate by visual inspection and are useful for further applications.