A Scalable Framework For Segmenting Magnetic Resonance Images

@article{Hore2009ASF,
  title={A Scalable Framework For Segmenting Magnetic Resonance Images},
  author={Prodip Hore and Lawrence O. Hall and Dmitry B. Goldgof and Yuhua Gu and Andrew Maudsley and Ammar Darkazanli},
  journal={Journal of signal processing systems},
  year={2009},
  volume={54 1-3},
  pages={183-203}
}
A fast, accurate and fully automatic method of segmenting magnetic resonance images of the human brain is introduced. The approach scales well allowing fast segmentations of fine resolution images. The approach is based on modifications of the soft clustering algorithm, fuzzy c-means, that enable it to scale to large data sets. Two types of modifications to create incremental versions of fuzzy c-means are discussed. They are much faster when compared to fuzzy c-means for medium to extremely… CONTINUE READING
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