Multi-class brain segmentation using atlas propagation and EM-based refinement

@article{Ledig2012MulticlassBS,
  title={Multi-class brain segmentation using atlas propagation and EM-based refinement},
  author={Christian Ledig and Robin Wolz and Paul Aljabar and Jyrki L{\"o}tj{\"o}nen and Rolf A. Heckemann and Alexander Hammers and Daniel Rueckert},
  journal={2012 9th IEEE International Symposium on Biomedical Imaging (ISBI)},
  year={2012},
  pages={896-899}
}
In recent years, multi-atlas segmentation has emerged as one of the most accurate techniques for the segmentation of brain magnetic resonance (MR) images, especially when combined with intensity-based refinement techniques such as graph-cut or expectation-maximization (EM) optimization. However, most of the work so far has focused on intensity-based refinement strategies for individual anatomical structures such as the hippocampus. In this work we extend a previously proposed framework for… CONTINUE READING
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Segmentation of the ADNI database into 83 anatomical regions using LEAP

  • R. Wolz, D. Rueckert
  • Toronto, Canada, 2011, MICCAI 2011 Workshop on…
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