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Spatio-temporal Speckle Reduction in Ultrasound Sequences

  • Noura Azzabou
  • Nikos Paragios
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5241)

Abstract

In this paper we will be concerned with speckle removal in ultrasound images. To this end, we introduce a new spatio-temporal denoising method based on a variational formulation. The regularization relies on a non parametric image model that describes the observed image structure and express inter-dependencies between pixels in space and time. Furthermore, we introduce a new data term adapted to the Rayleigh distribution of the speckle. The interaction between pixels is determined through the definition of new measure of similarity between them to better reflect image content. To compute this similarity measure, we take into consideration the spatial aspect as well as the temporal one. Experiments were carried on both synthetic and real data and the results show the potential of our method.

Keywords

Multiplicative Noise Data Term Rayleigh Distribution Medical Ultrasound Image Large Neighborhood Size 
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.

Supplementary material

978-3-540-85988-8_113_MOESM1_ESM.avi (16.7 mb)
Supplementary Material (17,109 KB)
978-3-540-85988-8_113_MOESM2_ESM.avi (16.7 mb)
Supplementary Material (17,109 KB)

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Noura Azzabou
    • 1
  • Nikos Paragios
    • 1
    • 2
  1. 1.Laboratoire MAS Ecole Centrale de Paris France
  2. 2.GALEN Group, INRIA Saclay, Ile-de-FranceFrance

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