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Multi-structure Atlas-Based Segmentation Using Anatomical Regions of Interest

  • Óscar Alfonso Jiménez del ToroEmail author
  • Henning Müller
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8331)

Abstract

The Visceral project organizes a benchmark on multiple anatomical structure segmentation. A training set is provided to the participants that includes a sample of the manual annotations of these structures. To evaluate different segmentation approaches a testing set of volumes must be segmented automatically in a limited period of time. A multi-atlas based segmentation approach is proposed. This technique can be implemented automatically and applied to different anatomical structures with a large enough training set. The addition of a hierarchical local alignment based on anatomical knowledge and local contrast is explained in the approach. An initial experiment to evaluate the impact of using a local alignment and its results show a higher overlap (\({>}9.7\,\%\)) of the structures measured with the Jaccard coefficient. The approach is an effective and easy to implement method that adjusts well to the Visceral benchmark.

Keywords

Visceral Atlas-based segmentation Image registration 

Notes

Acknowledgments

This work was supported by the EU/FP7 through VISCERAL (318068).

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Óscar Alfonso Jiménez del Toro
    • 1
    Email author
  • Henning Müller
    • 1
    • 2
  1. 1.University of Applied Sciences Western Switzerland (HES-SO)SierreSwitzerland
  2. 2.University Hospitals and University of GenevaGenevaSwitzerland

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