Difference between revisions of "Publications/widynski.14.ius"
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| 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. |
| 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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| id = widynski.14.ius |
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| bibtex = |
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and speckle tracking, and experiments showed that this |
and speckle tracking, and experiments showed that this |
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approach performs well compared to state-of-the-art |
approach performs well compared to state-of-the-art |
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| + | doi = <nowiki>{</nowiki>10.1109/ULTSYM.2014.0430<nowiki>}</nowiki> |
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<nowiki>}</nowiki> |
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Latest revision as of 17:01, 27 May 2021
- Authors
- Nicolas Widynski, Thierry Géraud, Damien Garcia
- Where
- Proceedings of the IEEE International Ultrasonics Symposium (IUS)
- Place
- Chicago, IL, USA
- Type
- inproceedings
- Keywords
- Image
- Date
- 2014-09-10
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}
}