DocumentCode :
2836215
Title :
Skull stripping of MRI brain images using mathematical morphology
Author :
Roslan, Rosniza ; Jamil, Nursuriati ; Mahmud, Rozi
Author_Institution :
Fac. of Comput. & Math. Sci., MARA Univ. of Technol., Shah Alam, Malaysia
fYear :
2010
fDate :
Nov. 30 2010-Dec. 2 2010
Firstpage :
26
Lastpage :
31
Abstract :
Skull stripping is a major phase in MRI brain imaging applications and it refers to the removal of its non-cerebral tissues. The main problem in skull-stripping is the segmentation of the non-cerebral and the intracranial tissues due to their homogeneity intensities. As morphology requires prior binarization of the image, this paper proposed mathematical morphology segmentation using double and Otsu´s thresholding. The purpose is to identify robust threshold values to remove the non-cerebral tissue from MRI brain images. Ninety collected samples of T1-weighted, T2-weighted and FLAIR MRI brain images are used in the experiments. The results showed promising use of double threholding as a robust threshold value in handling intensity inhomogeneities compared to Otsu´s thresholding.
Keywords :
biological tissues; biomedical MRI; brain; image segmentation; mathematical morphology; medical image processing; FLAIR MRI brain images; MRI brain images; Otsu thresholding; T1-weighted images; T2-weighted images; double thresholding; homogeneity intensities; image segmentation; mathematical morphology; noncerebral tissues; skull stripping; Brain; Image segmentation; Image sequences; Magnetic resonance imaging; Morphology; Robustness; Skull; MRI; Mathematical Morphology; Skull Stripping; Thresholding;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Engineering and Sciences (IECBES), 2010 IEEE EMBS Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-7599-5
Type :
conf
DOI :
10.1109/IECBES.2010.5742193
Filename :
5742193
Link To Document :
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