, Volume 9, Issue 4, pp 381–400 | Cite as

An Open Source Multivariate Framework for n-Tissue Segmentation with Evaluation on Public Data

  • Brian B. AvantsEmail author
  • Nicholas J. Tustison
  • Jue Wu
  • Philip A. Cook
  • James C. Gee
Original Article


We introduce Atropos, an ITK-based multivariate n-class open source segmentation algorithm distributed with ANTs ( The Bayesian formulation of the segmentation problem is solved using the Expectation Maximization (EM) algorithm with the modeling of the class intensities based on either parametric or non-parametric finite mixtures. Atropos is capable of incorporating spatial prior probability maps (sparse), prior label maps and/or Markov Random Field (MRF) modeling. Atropos has also been efficiently implemented to handle large quantities of possible labelings (in the experimental section, we use up to 69 classes) with a minimal memory footprint. This work describes the technical and implementation aspects of Atropos and evaluates its performance on two different ground-truth datasets. First, we use the BrainWeb dataset from Montreal Neurological Institute to evaluate three-tissue segmentation performance via (1) K-means segmentation without use of template data; (2) MRF segmentation with initialization by prior probability maps derived from a group template; (3) Prior-based segmentation with use of spatial prior probability maps derived from a group template. We also evaluate Atropos performance by using spatial priors to drive a 69-class EM segmentation problem derived from the Hammers atlas from University College London. These evaluation studies, combined with illustrative examples that exercise Atropos options, demonstrate both performance and wide applicability of this new platform-independent open source segmentation tool.


Image segmentation Open source Multivariate Cortical parcellation Evaluation BrainWeb ITK 



This work was supported in part by NIH (AG17586, AG15116, NS44266, and NS53488).


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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Brian B. Avants
    • 1
    Email author
  • Nicholas J. Tustison
    • 2
  • Jue Wu
    • 1
  • Philip A. Cook
    • 1
  • James C. Gee
    • 1
  1. 1.Penn Image Computing and Science LaboratoryUniversity of PennsylvaniaPhiladelphiaUSA
  2. 2.Department of Radiology and Medical ImagingUniversity of VirginiaCharlottesvilleUSA

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