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Atlas-Based Registration for Accurate Segmentation of Thoracic and Lumbar Vertebrae in CT Data

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Recent Advances in Computational Methods and Clinical Applications for Spine Imaging

Part of the book series: Lecture Notes in Computational Vision and Biomechanics ((LNCVB,volume 20))

Abstract

Segmentation of the vertebrae in the spine is of relevance to many medical applications related to the spine. This paper describes a method based upon atlas-based registration for achieving an accurate segmentation of the thoracic and the lumbar vertebrae in the spine as imaged by computed tomography. The method has been evaluated on ten data sets provided as a part of the segmentation challenge hosted by the 2nd MICCAI workshop on Computational Methods and Clinical Applications for Spine Imaging. An average point-to-surface error of \(1.05\,\pm \,0.65\) mm and a mean DICE coefficient of \(0.94\,\pm \,0.03\) were obtained when comparing the computed segmentations with ground truth segmentations. These results are highly competitive when compared to the results of earlier presented methods.

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Authors and Affiliations

  1. Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping University Hospital, SE-581 85, Linköping, Sweden

    Daniel Forsberg

  2. Sectra, Teknikringen 20, SE-583 30, Linköping, Sweden

    Daniel Forsberg

Authors
  1. Daniel Forsberg
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Correspondence to Daniel Forsberg .

Editor information

Editors and Affiliations

  1. Clinical Center, National Institutes of Health, Bethesda, Maryland, USA

    Jianhua Yao

  2. Department of Computing, Imperial College, London, United Kingdom

    Ben Glocker

  3. Innovative Technologies, Philips Research, Hamburg, Germany

    Tobias Klinder

  4. GE Healthcare and University of Western Ontario, London, Ontario, Canada

    Shuo Li

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Forsberg, D. (2015). Atlas-Based Registration for Accurate Segmentation of Thoracic and Lumbar Vertebrae in CT Data. In: Yao, J., Glocker, B., Klinder, T., Li, S. (eds) Recent Advances in Computational Methods and Clinical Applications for Spine Imaging. Lecture Notes in Computational Vision and Biomechanics, vol 20. Springer, Cham. https://doi.org/10.1007/978-3-319-14148-0_5

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  • DOI: https://doi.org/10.1007/978-3-319-14148-0_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14147-3

  • Online ISBN: 978-3-319-14148-0

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