Difference between revisions of "Publications/widynski.14.ius"

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| type = inproceedings
 
| type = inproceedings
 
| id = widynski.14.ius
 
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| identifier = doi:10.1109/ULTSYM.2014.0430
 
| bibtex =
 
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@InProceedings<nowiki>{</nowiki> widynski.14.ius,
 
@InProceedings<nowiki>{</nowiki> widynski.14.ius,
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and speckle tracking, and experiments showed that this
 
and speckle tracking, and experiments showed that this
 
approach performs well compared to state-of-the-art
 
approach performs well compared to state-of-the-art
methods.<nowiki>}</nowiki>
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methods.<nowiki>}</nowiki>,
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doi = <nowiki>{</nowiki>10.1109/ULTSYM.2014.0430<nowiki>}</nowiki>
 
<nowiki>}</nowiki>
 
<nowiki>}</nowiki>
   

Latest revision as of 17:01, 27 May 2021

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.

Documents

Bibtex (lrde.bib)

@InProceedings{	  widynski.14.ius,
  author	= {Nicolas Widynski and Thierry G\'eraud and Damien Garcia},
  title		= {Speckle Spot Detection in Ultrasound Images: Application
		  to Speckle Reduction and Speckle Tracking},
  booktitle	= {Proceedings of the IEEE International Ultrasonics
		  Symposium (IUS)},
  year		= {2014},
  pages		= {1734--1737},
  address	= {Chicago, IL, USA},
  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.},
  doi		= {10.1109/ULTSYM.2014.0430}
}