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Publication Detail
Multi Atlas Segmentation applied to in vivo mouse brain MRI
  • Publication Type:
  • Authors:
    Ma D, Cardoso M, Modat M, Powell N, Holmes H, Lythgoe M, Ourselin S
  • Publisher:
    MICCAI 2012 Workshop on Multi-Atlas Labeling
  • Publication date:
  • Place of publication:
  • Pagination:
    134, 143
  • Published proceedings:
    MICCAI 2012 Workshop on Multi-Atlas Labeling
  • Editors:
    Landman BA,Warfield SK
  • Status:
  • Name of conference:
    15th International Conference on Medical Image Computing and Computer Assisted Intervention
  • Conference place:
    Nice, France
  • Conference start date:
  • Conference finish date:
  • Notes:
    file: :D$$:/Sync/Dropbox/Documents/Mendeley Desktop/Ma et al. - 2012 - Multi Atlas Segmentation applied to in vivo mouse brain MRI.pdf:pdf
Multi-atlas segmentation propagation has evolved quickly in recent years, becoming a state-of-the-art method for automatic struc- tural parcellation for brain MRI. However, few studies have applied these methods to preclinical research. In this study, we present a fully auto- matic multi-atlas segmentation pipeline for mouse brain MRI tissue par- cellation. The pipeline adopts the Multi-STEPS multi-atlas segmentation algorithm, which utilises a locally normalised cross correlation (LNCC) similarity metric for atlas selection and an extended STAPLE frame- work for multi-label fusion. The segmentation accuracy of the pipeline was evaluated using an in vivo mouse brain atlas with pre-segmented manual labels as gold standard, and optimised parameters were obtained. Results show a mean Dice similarity coefficient of 0.839 over all the struc- tures and for all the samples in the database, significantly higher than in a single atlas propagation strategy, and also generally higher than STAPLE strategy, although the improvement is not significant.
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