Multi-organ Abdominal CT Segmentation Using Hierarchically Weighted Subject-Specific Atlases

  • Robin Wolz
  • Chengwen Chu
  • Kazunari Misawa
  • Kensaku Mori
  • Daniel Rueckert
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7510)

Abstract

A robust automated segmentation of abdominal organs can be crucial for computer aided diagnosis and laparoscopic surgery assistance. Many existing methods are specialised to the segmentation of individual organs or struggle to deal with the variability of the shape and position of abdominal organs. We present a general, fully-automated method for multi-organ segmentation of abdominal CT scans. The method is based on a hierarchical atlas registration and weighting scheme that generates target specific priors from an atlas database by combining aspects from multi-atlas registration and patch-based segmentation, two widely used methods in brain segmentation. This approach allows to deal with high inter-subject variation while being flexible enough to be applied to different organs. Our results on a dataset of 100 CT scans compare favourable to the state-of-the-art with Dice overlap values of 94%, 91%, 66% and 94% for liver, spleen, pancreas and kidney respectively.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Robin Wolz
    • 1
  • Chengwen Chu
    • 2
  • Kazunari Misawa
    • 3
  • Kensaku Mori
    • 2
    • 4
  • Daniel Rueckert
    • 1
  1. 1.Imperial College LondonLondonUK
  2. 2.Department of Media ScienceNagoya UniversityNagoyaJapan
  3. 3.Aichi Cancer CenterNagoyaJapan
  4. 4.Information and Communications HeadquartersNagoya UniversityJapan

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