Title :
Automatic skull stripping in MRI based on morphological filters and fuzzy c-means segmentation
Author :
Gambino, Orazio ; Daidone, Enrico ; Sciortino, Matteo ; Pirrone, Roberto ; Ardizzone, Edoardo
Author_Institution :
Dept. of Comput. Sci., Univ. of Palermo, Palermo, Italy
fDate :
Aug. 30 2011-Sept. 3 2011
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.
Keywords :
biological tissues; biomedical MRI; brain; filters; image segmentation; medical image processing; 2D brain extraction; MRI; T1-weighted MR image; automatic skull stripping method; biological tissues; fuzzy c-means segmentation; human brain; morphological filters; organ splitting problem; transversal slices; Brain modeling; Image segmentation; Magnetic resonance imaging; Software; Surface morphology; Three dimensional displays; Algorithms; Brain; Fuzzy Logic; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Magnetic Resonance Imaging; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Skull; Subtraction Technique;
Conference_Titel :
Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4244-4121-1
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2011.6091248
