Brain Magnetic Resonance Images Segmentation Based on Wavelet Method

Author

Zhenyu, Zhou ; Zongcai, Ruan

Author_Institution

Dept. of Biomed. Eng., Southeast Univ., Nanjing

fYear

2006

Firstpage

3078

Lastpage

3081

Abstract

This paper focused on the brain magnetic resonance (MR) images, which is one of the key problems in image processing. A novel segmentation method based on watershed transform and wavelets transform is presented for white matter in thin sliced single-channel brain magnetic resonance scans. The original image is smoothed by using anisotropic filter and over-segmented by the watershed algorithm. Finally, the brain MR image is segmented automatically by using the multicontext wavelets-based thresholding (MCWT) method. The result of the experiment indicates that the algorithm can obtain segmentation result fast and accurately

Keywords

biomedical MRI; brain; image segmentation; medical image processing; smoothing methods; wavelet transforms; anisotropic filter; image oversegmentation; image processing; image segmentation; multicontext wavelets-based thresholding; smoothing method; thin sliced single-channel brain magnetic resonance scans; watershed transform; wavelets transform; white matter; Anatomy; Anisotropic filters; Biomedical imaging; Brain; Humans; Image segmentation; Magnetic resonance; Magnetic resonance imaging; Signal processing algorithms; Wavelet transforms; brain imaging; image segmentation; watershed transform; wavelets; white matter;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the

Conference_Location

Shanghai

Print_ISBN

0-7803-8741-4

Type

conf

DOI

10.1109/IEMBS.2005.1617125

Filename

1617125