DocumentCode :
2573623
Title :
Population intensity outliers or a new model for brain WM abnormalities
Author :
Tomas-Fernandez, Xavier ; Warfield, Simon K.
Author_Institution :
Comput. Radiol. Lab., Childrens´ Hosp. Boston, Boston, MA, USA
fYear :
2012
fDate :
2-5 May 2012
Firstpage :
1543
Lastpage :
1546
Abstract :
We present a new automatic method for segmentation of Multiple Sclerosis (MS) lesions in Magnetic Resonance Images. The algorithm performs tissue classification combining a within subject global tissue intensity model and a local tissue intensity model derived from an aligned set of healthy reference subjects. MS lesions are detected as outliers towards the proposed coupled global/local intensity model. Evaluation using BrainWeb synthetic, show our new coupled local/global intensity GMM model to be sensitive towards MS lesions, as well to be robust to noise and intensity inhomogeneity artifacts found MRI scans.
Keywords :
biological tissues; biomedical MRI; brain; cellular biophysics; diseases; image denoising; image segmentation; medical disorders; medical image processing; neurophysiology; physiological models; MRI scans; automatic method; brain WM abnormalities; brainWeb synthetic; global tissue intensity model; intensity inhomogeneity artifacts; local tissue intensity model; local-global intensity GMM model; magnetic resonance image segmentation; multiple sclerosis lesions; noise; population intensity outliers; tissue classification; Brain modeling; Image segmentation; Lesions; Magnetic resonance imaging; Noise; Nonhomogeneous media; Bayesian; Magnetic Resonance Imaging; Multiple Sclerosis; Segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on
Conference_Location :
Barcelona
ISSN :
1945-7928
Print_ISBN :
978-1-4577-1857-1
Type :
conf
DOI :
10.1109/ISBI.2012.6235867
Filename :
6235867
Link To Document :
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