DocumentCode :
629255
Title :
A novel efficient kernelized fuzzy C-means with additive bias field for brain image segmentation
Author :
Thamaraichelvi, B. ; Yamuna, G. Yamuna
Author_Institution :
Dept. of Electr. Eng., Annamalai Univ., Chidambaram, India
fYear :
2013
fDate :
3-5 April 2013
Firstpage :
68
Lastpage :
72
Abstract :
In this paper, a suitable novel algorithm has been proposed for segmenting the brain magnetic resonance imaging (MRI) data using an efficient kernelized fuzzy c-means (EKFCM) with spatial constraints. In this proposed algorithm, the Euclidean distance in the standard fuzzy c-means (FCM) is replaced by a Gaussian radial basis function with additive bias. The proposed method will segment the given MRI data automatically, by considering the effects of intensity inhomogeneity, partial volume and noise. The neighbourhood effect acts as a regularizer, and the regularization term is useful in segmenting the MR Imaging corrupted by noise and intensity inhomogeneity. Experimental results on both real and simulated images, prove that the proposed algorithm has higher segmenting accuracy than other segmenting techniques.
Keywords :
Gaussian processes; biomedical MRI; constraint handling; fuzzy set theory; image segmentation; medical image processing; pattern clustering; radial basis function networks; EKFCM; Euclidean distance; Gaussian radial basis function; additive bias field; brain image segmentation; efficient kernelized fuzzy c-means; intensity inhomogeneity; magnetic resonance imaging; neighbourhood effect; noise inhomogeneity; partial volume; regularization; spatial constraint; Additives; Biomedical imaging; Clustering algorithms; Image segmentation; Kernel; Linear programming; Magnetic resonance imaging; Additive bias; Brain magnetic resonance Image; FCM-Fuzzy c-means; Gaussian radial basis Kernel function; Image segmentation; Partial volume (PV);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications and Signal Processing (ICCSP), 2013 International Conference on
Conference_Location :
Melmaruvathur
Print_ISBN :
978-1-4673-4865-2
Type :
conf
DOI :
10.1109/iccsp.2013.6577017
Filename :
6577017
Link To Document :
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