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Automatic Segmentation of Vertebrae from Radiographs: A Sample-Driven Active Shape Model Approach

  • Peter Mysling
  • Kersten Petersen
  • Mads Nielsen
  • Martin Lillholm
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7009)

Abstract

Segmentation of vertebral contours is an essential task in the design of automatic tools for vertebral fracture assessment. In this paper, we propose a novel segmentation technique which does not require operator interaction. The proposed technique solves the segmentation problem in a hierarchical manner. In a first phase, a coarse estimate of the overall spine alignment and the vertebra locations is computed using a shape model sampling scheme. These samples are used to initialize a second phase of active shape model search, under a nonlinear model of vertebra appearance. The search is constrained by a conditional shape model, based on the variability of the coarse spine location estimates. The technique is evaluated on a data set of manually annotated lumbar radiographs. The results compare favorably to the previous work in automatic vertebra segmentation, in terms of both segmentation accuracy and failure rate.

Keywords

Fracture Vertebra Random Forest Automatic Segmentation Segmentation Accuracy Vertebral Fracture Assessment 
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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Peter Mysling
    • 1
  • Kersten Petersen
    • 1
  • Mads Nielsen
    • 1
    • 2
  • Martin Lillholm
    • 2
  1. 1.DIKU, University of CopenhagenDenmark
  2. 2.BiomedIQRødovreDenmark

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