Representation and fusion of heterogeneous fuzzy information in the 3D space for model-based structural recognition—application to 3D brain imaging

From LRDE

Abstract

We present a novel approach of model-based pattern recognition where structural information and spatial relationships have a most important role. It is illustrated in the domain of 3D brain structure recognition using an anatomical atlas. Our approach performs simultaneously segmentation and recognition of the scene and the solution of the recognition task is progressive, processing successively different objects, using different of knowledge about the object and about relationships between objects. Therefore the core of the approach is the representation part, and constitutes the main contribution of this paper. We make use of a spatial representation of each piece of information, as a spatial set representing a constraint to be satisfied by the searched object, thanks in particular to fuzzy mathematical operations. Fusion of these constraints allows to, segment and recognize the desired object.


Bibtex (lrde.bib)

@Article{	  bloch.03.ai,
  author	= {Isabelle Bloch and Thierry G\'eraud and Henri Ma\^itre},
  title		= {Representation and fusion of heterogeneous fuzzy
		  information in the {3D} space for model-based structural
		  recognition---application to {3D} brain imaging},
  journal	= {Artificial Intelligence},
  month		= aug,
  year		= 2003,
  volume	= 148,
  number	= {1-2},
  pages		= {141--175},
  abstract	= {We present a novel approach of model-based pattern
		  recognition where structural information and spatial
		  relationships have a most important role. It is illustrated
		  in the domain of 3D brain structure recognition using an
		  anatomical atlas. Our approach performs simultaneously
		  segmentation and recognition of the scene and the solution
		  of the recognition task is progressive, processing
		  successively different objects, using different of
		  knowledge about the object and about relationships between
		  objects. Therefore the core of the approach is the
		  representation part, and constitutes the main contribution
		  of this paper. We make use of a spatial representation of
		  each piece of information, as a spatial set representing a
		  constraint to be satisfied by the searched object, thanks
		  in particular to fuzzy mathematical operations. Fusion of
		  these constraints allows to, segment and recognize the
		  desired object.}
}