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Vertebral Column Localization, Labeling, and Segmentation

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Spinal Imaging and Image Analysis

Part of the book series: Lecture Notes in Computational Vision and Biomechanics ((LNCVB,volume 18))

Abstract

The vertebral column consists of interconnected bone structures that extend from the neck down to the pelvis. In addition to its crucial functionality in spinal cord protection, it provides the necessary flexibility and support for the whole body. Worldwide interest in spine related research has been increasing due to the widely spread of related abnormalities in the developed countries which accounts for over $100 billion annually in the diagnosis, treatment, and associated loss of wages. Our specific interest in this chapter is in the medical image analysis of the vertebral column. In this chapter, we aim at providing a broader review of the available literature in vertebral column image analysis. Moreover, we focus on providing an understanding of the localization, labeling, and segmentation problems for the various vertebral column structures from the available medical imaging modalities. Additionally, we describe the general challenges facing the various solutions for these problems. Our taxonomy is based on the target imaging modality to simplify the understanding of the broad research in this area.

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Acknowledgments

This work was partially supported by grants from NYSTAR and NSF.

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Authors and Affiliations

  1. The University of Jordan, Amman, Jordan

    Raja S. Alomari

  2. The University at Buffalo SUNY, Buffalo, NY, USA

    Subarna Ghosh & Vipin Chaudhary

  3. Samsung Inc., Suwon, South Korea

    Jaehan Koh

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  1. Raja S. Alomari
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  2. Subarna Ghosh
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Correspondence to Raja S. Alomari .

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Editors and Affiliations

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

    Shuo Li

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

    Jianhua Yao

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Alomari, R.S., Ghosh, S., Koh, J., Chaudhary, V. (2015). Vertebral Column Localization, Labeling, and Segmentation. In: Li, S., Yao, J. (eds) Spinal Imaging and Image Analysis. Lecture Notes in Computational Vision and Biomechanics, vol 18. Springer, Cham. https://doi.org/10.1007/978-3-319-12508-4_7

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