Nicolas Widynski

Speckle spot detection in ultrasound images: Application to speckle reduction and speckle tracking

By Nicolas Widynski, Thierry Géraud, Damien Garcia

2014-09-10

In Proceedings of the IEEE international ultrasonics symposium (IUS)

Abstract

This paper investigates the speckle spot detection task in ultrasound images. Speckle spots are described by structural criteria: dimensions, shape, and topology. We propose to represent the image using a morphological inclusion tree, from which speckle spots are detected using their structural appearance. This makes the method independent of contrast, and hence robusts to intensity correction. The detection was applied to speckle reduction and speckle tracking, and experiments showed that this approach performs well compared to state-of-the-art methods.

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Algorithme de calcul de l’arbre des composantes avec applications à la reconnaissance des formes en imagerie satellitaire

By Anthony Baillard, Christophe Berger, Emmanuel Bertin, Thierry Géraud, Roland Levillain, Nicolas Widynski

2007-05-11

In Proceedings of the 21st symposium on signal and image processing (GRETSI)

Abstract

In this paper a new algorithm to compute the component tree is presented. As compared to the state-of-the-art, this algorithm does not use excessive memory and is able to work efficiently on images whose values are highly quantized or even with images having floating values. We also describe how it can be applied to astronomical data to identify relevant objects.

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Effective component tree computation with application to pattern recognition in astronomical imaging

By Christophe Berger, Thierry Géraud, Roland Levillain, Nicolas Widynski, Anthony Baillard, Emmanuel Bertin

2007-05-03

In Proceedings of the IEEE international conference on image processing (ICIP)

Abstract

In this paper a new algorithm to compute the component tree is presented. As compared to the state of the art, this algorithm does not use excessive memory and is able to work efficiently on images whose values are highly quantized or even with images having floating values. We also describe how it can be applied to astronomical data to identify relevant objects.

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