Title :
A new brain MRI image segmentation strategy based on wavelet transform and K-means clustering
Author :
Jianwei Liu;Lei Guo
Author_Institution :
School of Automation, Northwestern Polytechnical University, Xi´an, China
Abstract :
For the problem of low accuracy using K-means clustering algorithm to segment noisy brain magnetic resonance imaging (MRI) images, this paper proposed a strategy to improve segmentation accuracy. Firstly, the strategy uses wavelet transform to brain MRI image denoising, secondly, brain MRI image is segmented by k-means clustering algorithm. Experimental results show that the proposed strategy can effectively improve the segmentation accuracy of the noisy MRI brain image and is universal to some extent.
Keywords :
"Image segmentation","Magnetic resonance imaging","Clustering algorithms","Wavelet transforms","Brain","Noise reduction"
Conference_Titel :
Signal Processing, Communications and Computing (ICSPCC), 2015 IEEE International Conference on
Print_ISBN :
978-1-4799-8918-8
DOI :
10.1109/ICSPCC.2015.7338884