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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Somasundaram, K. Kalaiselvi, T. |
| Copyright Year | 2010 |
| Description | Author affiliation: Dept. of Comput. Sci. & Applic., Deemed Univ., Gandhigram, India (Somasundaram, K.; Kalaiselvi, T.) |
| Abstract | In this paper we propose a brain extraction method that solely depends on the brain anatomy and its intensity characteristics. Using an adaptive intensity thresholding method on the MRI head scans, a binary image is obtained. The binary image is labeled using the anatomical facts that the scalp is the boundary between head and background, and the skull is the boundary separating brain and scalp. A run length scheme is employed on the labeled image to get the rough brain portion. Morphological operations are then performed to obtain the fine brain on the assumption that brain is the largest connected component. But this concept failed to work on some slices where brain is composed of more than one connected component. To solve this problem a 3-D approach is introduced in the proposed BEM. Experimental results on 47 sets of T1 scans taken from MRI scan centre and neuroimage web services showed that our method gives better results than the popular methods BET, BSE and MLS. |
| Starting Page | 1 |
| Ending Page | 5 |
| File Size | 255862 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424471379 |
| e-ISBN | 9781424471386 |
| DOI | 10.1109/SPCOM.2010.5560513 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-07-18 |
| Publisher Place | India |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Brain region labeling Magnetic resonance imaging Scalp brain anatomy Skull segmentation Classification algorithms brain extraction T1-weighted MRI scans intensity thresholding Pixel |
| Content Type | Text |
| Resource Type | Article |
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