Difference between revisions of "Publications/bloch.05.prl"
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| abstract = Spatial relations play an important role in recognition of structures embedded in a complex environment and for reasoning under imprecision. Several types of relationships can be modeled in a unified way using fuzzy mathematical morphology. Their combination benefits from the powerful framework of fuzzy set theory for fusion tasks and decision making. This paper presents several methods of fusion of information about spatial relationships and illustrates them on the example of model-based recognition of brain structures in 3D magnetic resonance imaging. |
| abstract = Spatial relations play an important role in recognition of structures embedded in a complex environment and for reasoning under imprecision. Several types of relationships can be modeled in a unified way using fuzzy mathematical morphology. Their combination benefits from the powerful framework of fuzzy set theory for fusion tasks and decision making. This paper presents several methods of fusion of information about spatial relationships and illustrates them on the example of model-based recognition of brain structures in 3D magnetic resonance imaging. |
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pages = <nowiki>{</nowiki>449--457<nowiki>}</nowiki>, |
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abstract = <nowiki>{</nowiki>Spatial relations play an important role in recognition of |
abstract = <nowiki>{</nowiki>Spatial relations play an important role in recognition of |
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structures embedded in a complex environment and for |
structures embedded in a complex environment and for |
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Latest revision as of 12:46, 24 November 2020
- Authors
- Isabelle Bloch, Olivier Colliot, Oscar Camara, Thierry Géraud
- Journal
- Pattern Recognition Letters
- Type
- article
- Keywords
- Image
- Date
- 2004-07-09
Abstract
Spatial relations play an important role in recognition of structures embedded in a complex environment and for reasoning under imprecision. Several types of relationships can be modeled in a unified way using fuzzy mathematical morphology. Their combination benefits from the powerful framework of fuzzy set theory for fusion tasks and decision making. This paper presents several methods of fusion of information about spatial relationships and illustrates them on the example of model-based recognition of brain structures in 3D magnetic resonance imaging.
Bibtex (lrde.bib)
@Article{ bloch.05.prl,
author = {Isabelle Bloch and Olivier Colliot and Oscar Camara and
Thierry G\'eraud},
title = {Fusion of spatial relationships for guiding recognition,
example of brain structure recognition in {3D} {MRI}},
journal = {Pattern Recognition Letters},
year = 2005,
volume = 26,
number = 4,
month = mar,
pages = {449--457},
doi = {10.1016/j.patrec.2004.08.009},
abstract = {Spatial relations play an important role in recognition of
structures embedded in a complex environment and for
reasoning under imprecision. Several types of relationships
can be modeled in a unified way using fuzzy mathematical
morphology. Their combination benefits from the powerful
framework of fuzzy set theory for fusion tasks and decision
making. This paper presents several methods of fusion of
information about spatial relationships and illustrates
them on the example of model-based recognition of brain
structures in 3D magnetic resonance imaging.}
}