title: Information fusion: application to data and model fusion for ultrasound image segmentation.
abstract: Nowadays, information fusion constitutes a challenging research topic. Our study proposes to achieve the fusion of several knowledge sources. This, in order to detect the esophagus inner wall from ultrasound medical images. After a brief description of information fusion concepts, we propose a system architecture including both model and data fusion. The data fusion is accomplished using fuzzy modeling, which can be seen as a monosensor/multiple sources data fusion system. The model fusion is performed using a full-adapted snake theory, which projects the fuzzy decision into the binary decision space.
authors.affiliation: ENST Bretagne, Département Image et Traitement de l'Information, Brest, France. basel.solaiman@enst-bretagne.fr
authors.forename: B
authors.initials: B
authors.lastname: Solaiman
authors.forename: R
authors.initials: R
authors.lastname: Debon
authors.forename: F
authors.initials: F
authors.lastname: Pipelier
authors.forename: J M
authors.initials: JM
authors.lastname: Cauvin
authors.forename: C
authors.initials: C
authors.lastname: Roux
mesh_terms: D003198:Computer Simulation; D019723:Endoscopes; D019160:Endosonography / Q000295:instrumentation / Q000379:methods*; D004867:Equipment Design; D004938:Esophageal Neoplasms / Q000000981:diagnostic imaging; D004947:Esophagus / Q000000981:diagnostic imaging*; D017143:Fuzzy Logic; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D014159:Transducers