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

fYear

2011

fDate

Aug. 30 2011-Sept. 3 2011

Firstpage

5040

Lastpage

5043

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE

Conference_Location

Boston, MA

ISSN

1557-170X

Print_ISBN

978-1-4244-4121-1

Electronic_ISBN

1557-170X

Type

conf

DOI

10.1109/IEMBS.2011.6091248

Filename

6091248