Title :
Brain extraction method for T1-weighted magnetic resonance scans
Author :
Somasundaram, K. ; Kalaiselvi, T.
Author_Institution :
Dept. of Comput. Sci. & Applic., Deemed Univ., Gandhigram, India
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.
Keywords :
biomedical MRI; brain; image segmentation; medical image processing; MRI head scans; T1 weighted magnetic resonance scans; adaptive intensity thresholding method; binary image; brain MRI intensity characteristics; brain anatomy; brain extraction method; run length scheme; Brain; Classification algorithms; Magnetic resonance imaging; Pixel; Scalp; Skull; T1-weighted MRI scans; brain anatomy; brain extraction; intensity thresholding; region labeling; segmentation;
Conference_Titel :
Signal Processing and Communications (SPCOM), 2010 International Conference on
Conference_Location :
Bangalore
Print_ISBN :
978-1-4244-7137-9
DOI :
10.1109/SPCOM.2010.5560513