title: 3D multi-object segmentation of cardiac MSCT imaging by using a multi-agent approach.
abstract: We propose a new technique for general purpose, semi-interactive and multi-object segmentation in N-dimensional images, applied to the extraction of cardiac structures in MultiSlice Computed Tomography (MSCT) imaging. The proposed approach makes use of a multi-agent scheme combined with a supervised classification methodology allowing the introduction of a priori information and presenting fast computing times. The multi-agent system is organised around a communicating agent which manages a population of situated agents which segment the image through cooperative and competitive interactions. The proposed technique has been tested on several patient data sets. Some typical results are finally presented and discussed.
authors.affiliation: INSERM, U642, Rennes, Université de Rennes 1, LTSI, Rennes, F-35000, France. julien.fleureau@univ-rennes1.fr
authors.forename: Julien
authors.initials: J
authors.lastname: Fleureau
authors.forename: Mireille
authors.initials: M
authors.lastname: Garreau
authors.forename: Dominique
authors.initials: D
authors.lastname: Boulmier
authors.forename: Alfredo
authors.initials: A
authors.lastname: Hernández
mesh_terms: D000465:Algorithms; D005103:Expert Systems; D006321:Heart / Q000000981:diagnostic imaging*; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000295:instrumentation / Q000379:methods*