title: Automatic skull stripping in MRI based on morphological filters and fuzzy c-means segmentation.
abstract: In this paper a new automatic skull stripping method for T1-weighted MR image of human brain is presented. Skull stripping is a process that allows to separate the brain from the rest of tissues. The proposed method is based on a 2D brain extraction making use of fuzzy c-means segmentation and morphological operators applied on transversal slices. The approach is extended to the 3D case, taking into account the result obtained from the preceding slice to solve the organ splitting problem. The proposed approach is compared with BET (Brain Extraction Tool) implemented in MRIcro software.
authors.affiliation: Department of Computer Science, University of Palermo, Viale delle Scienze, 90128 Palermo, Italy. gambino@dinfo.unipa.it
authors.forename: Orazio
authors.initials: O
authors.lastname: Gambino
authors.forename: Enrico
authors.initials: E
authors.lastname: Daidone
authors.forename: Matteo
authors.initials: M
authors.lastname: Sciortino
authors.forename: Roberto
authors.initials: R
authors.lastname: Pirrone
authors.forename: Edoardo
authors.initials: E
authors.lastname: Ardizzone
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D017143:Fuzzy Logic; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012886:Skull / Q000033:anatomy & histology*; D013382:Subtraction Technique