@inproceedings{f593ac5da4c74066b221bd478caf5260,
title = "A new brain MRI image segmentation strategy based on wavelet transform and K-means clustering",
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, K-means clustering, wavelet tranform",
author = "Jianwei Liu and Lei Guo",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 5th IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2015 ; Conference date: 19-09-2015 Through 22-09-2015",
year = "2015",
month = nov,
day = "25",
doi = "10.1109/ICSPCC.2015.7338884",
language = "英语",
series = "2015 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2015 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2015",
}