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A Global-to-Local Matching Strategy for Registering Retinal Fundus Images

  • Xinge You
  • Bin Fang
  • Zhenyu He
  • Yuan Yan Tang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3522)

Abstract

In this paper, a multi-resolution rigid-model-based global matching algorithm is employed to register tree structures of blood vessels extracted from retinal fundus images. To further improve alignment of the vessels, a local structure-deformed elastic matching algorithm is proposed to eliminate the existence of ‘ghost vessels’ for accurate registration. The matching methods are tested on 268 pairs of retinal fundus images. Experiment results show that our global-to-local registration strategy is able to achieve an average centreline mapping errors of 1.85 pixels with average execution time of 207 seconds. The registration results have also been visually validated by corresponding fusion maps.

Keywords

Retinal Image Match Strategy Average Execution Time Fundus Image Registration Result 
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 2005

Authors and Affiliations

  • Xinge You
    • 1
    • 2
  • Bin Fang
    • 1
  • Zhenyu He
    • 1
  • Yuan Yan Tang
    • 1
  1. 1.Department of Computer ScienceHong Kong Baptist University 
  2. 2.Faculty of Mathematics and Computer ScienceHubei UniversityChina

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