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Segmentation of Lumbar Vertebrae Slices from CT Images

  • Hugo Hutt
  • Richard Everson
  • Judith Meakin
Chapter
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 20)

Abstract

We describe a fully automated approach to vertebrae segmentation from CT images which operates on superpixels. The method is based on a conditional random field model incorporating constraints learned from labelled superpixel features. The method is shown to provide consistently accurate segmentations of different vertebrae from a variety of subjects.

Keywords

Support Vector Machine Ground Truth Conditional Random Field Statistical Shape Model Accurate Segmentation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

H. Hutt was funded by the EPSRC. We are grateful to the SpineWeb initiative for making the data available and to the organisers of the CSI2014 competition.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.University of ExeterExeterUK

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