title: From MIP image to MRA segmentation using fuzzy set theory.
abstract: The aim of this paper is to describe a semi-automatic method of segmentation in magnetic resonance angiography (MRA). This method, based on fuzzy set theory, uses the information (gray levels) contained in the maximum intensity projection (MIP) image to segment the 3D vascular structure from slices. Tests have been carried out on vascular phantom and on clinical MRA images. This 3D segmentation method has proved to be satisfactory for the detection of vascular structures even for very complex shapes. Finally, this MIP-based approach is semi-automatic and produces a robust segmentation thanks to the contrast-to-noise ratio and to the slice profile which are taken into account to determine the membership of a voxel to the vascular structure.
authors.affiliation: Inserm, U703, ThIAIS, Lille, France. m-vermandel@chru-lille.fr
authors.forename: Maximilien
authors.initials: M
authors.lastname: Vermandel
authors.forename: Nacim
authors.initials: N
authors.lastname: Betrouni
authors.forename: Christian
authors.initials: C
authors.lastname: Taschner
authors.forename: Christian
authors.initials: C
authors.lastname: Vasseur
authors.forename: Jean
authors.initials: J
authors.lastname: Rousseau
mesh_terms: D005602:France; D017143:Fuzzy Logic; D007089:Image Enhancement / Q000379:methods*; D021621:Imaging, Three-Dimensional; D018810:Magnetic Resonance Angiography