Localizing Characteristic Points on a Vertebra Contour by Using Shape Language | SpringerLink
Skip to main content
Springer Nature Link
Log in

Localizing Characteristic Points on a Vertebra Contour by Using Shape Language

  • Conference paper
  • First Online:
Computer Vision and Graphics (ICCVG 2018)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11114))

Included in the following conference series:

  • 1429 Accesses

Abstract

In this paper, X-ray images are analysed by using the shape language. The algorithm combines syntactic and geometric approach. The geometric features of the contour are described by using syntactic approach. The points on the contour, where pathological changes can occur are localised effectively by the algorithm.

The work of the first author was supported by the AGH - University of Science and Technology, Faculty of Geology, Geophysics and Environmental Protection as a part of the statutory project.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
JPY 3498
Price includes VAT (Japan)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
JPY 5719
Price includes VAT (Japan)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
JPY 7149
Price includes VAT (Japan)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Antani, S., Lee, D.J., Long, L.R., Thoma, G.R.: Evaluation of shape similarity measurement methods for spine X-ray images. J. Vis. Commun. Image Represent. 15, 285–302 (2004)

    Article  Google Scholar 

  2. Aydin, S.Z., et al.: Limited reliability of radiographic assessment of spinal progression in ankylosing spondylitis. Rheumatology 56, 2162–2169 (2017)

    Article  Google Scholar 

  3. Baraliakos, X., et al.: Progression of radiographic damage in patients with ankylosing spondylitis: defining the central role of syndesmophytes. Ann. Rheum. Dis. 66, 910–915 (2007)

    Article  Google Scholar 

  4. Bielecka, M., Bielecki, A., Korkosz, M., Skomorowski, M., Wojciechowski, W., Zieliński, B.: Modified Jakubowski shape transducer for detecting osteophytes and erosions in finger joints. In: Dobnikar, A., Lotrič, U., Šter, B. (eds.) ICANNGA 2011. LNCS, vol. 6594, pp. 147–155. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-20267-4_16

    Chapter  Google Scholar 

  5. Bielecka, M., Piórkowski, A.: Optimization of numerical calculations of geometric features of a curve describing preprocessed X-ray images of bones as a starting point for syntactic analysis of finger bone contours. In: Chmielewski, L.J., Datta, A., Kozera, R., Wojciechowski, K. (eds.) ICCVG 2016. LNCS, vol. 9972, pp. 365–376. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46418-3_32

    Chapter  Google Scholar 

  6. Bielecka, M., Korkosz, M.: Generalized shape language application to detection of a specific type of bone erosion in X-ray images. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2016. LNCS (LNAI), vol. 9692, pp. 531–540. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-39378-0_45

    Chapter  Google Scholar 

  7. Bielecki, A., Korkosz, M., Wojciechowski, W., Zieliński, B.: Identifying the borders of the upper and lower metacarpophalangeal joint surfaces on hand radiographs. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2010. LNCS (LNAI), vol. 6113, pp. 589–596. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-13208-7_73

    Chapter  Google Scholar 

  8. Creemers, M., Franssen, M.J., van’t Hof, M.A., Gribnau, F.W., van de Putte, L.B., van Riel, P.L.: Assessment of outcome in ankylosing spondylitis: an extended radiographic scoring system. Ann. Rheum. Dis. 64, 127–129 (2005)

    Article  Google Scholar 

  9. El Maghraoui, A., Bensabbah, R., Bahiri, R., Bezza, A., Guedira, N., Hajjaj-Hassouni, N.: Cervical spine involvement in ankylosing spondylitis. Clin. Rheumatol. 22, 94–98 (2003)

    Article  Google Scholar 

  10. Flasiński, M.: Syntactic pattern recognition: paradigm issues and open problems. In: Chen, C.H. (ed.) Handbook of Pattern Recognition and Computer Vision, pp. 3–25. World Scientific, New Jersey-London-Singapore (2016)

    Google Scholar 

  11. Flasiński, M.: Introduction to Artificial Intelligence. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-40022-8

    Book  MATH  Google Scholar 

  12. Howe, B., Gururajan, A., Sari-Sarraf, A., Long, L.R.: Hierarchical segmentation of cervical and lumbar vertebrae using a customized generalized Hough transform and extensions to active appearance models. In: Proceedings of the 6th IEEE Southwest Symposium on Image Analysis and Interpretation (2004)

    Google Scholar 

  13. Jakubowski, R.: A structural representation of shape and its features. Inf. Sci. 39, 129–151 (1986)

    Article  MathSciNet  Google Scholar 

  14. Long, L.R., Thoma, G.R.: Use of shape models to search digitized spine X-rays. In: Proceedings of the 13th IEEE Symposium on Computer-Based Medical Systems, pp. 255–260 (2000)

    Google Scholar 

  15. Ogiela, M.R., Tadeusiewicz, R., Ogiela, L.: Image languages in intelligent radiological palm diagnostics. Pattern Recogn. 39, 2157–2165 (2006)

    Article  Google Scholar 

  16. Piórkowski, A.: A statistical dominance algorithm for edge detection and segmentation of medical images. In: Piętka, E., Badura, P., Kawa, J., Wieclawek, W. (eds.) Information Technologies in Medicine. AISC, vol. 471, pp. 3–14. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-39796-2_1

    Chapter  Google Scholar 

  17. Sharp, J., Gardner, J., Bennett, E.: Computer-based methods for measuring joint space and estimating erosion volume in the finger and wrist joints of patients with rheumatoid arthritis. Arthritis Rheum. 43, 1378–1386 (2000)

    Article  Google Scholar 

  18. Tadeusiewicz, R., Ogiela, M.R.: Medical Image Understanding Technology: Artificial Intelligence and Soft Computing for Image Understanding. Studies in Fuzziness and Soft Computing, vol. 156. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-40997-7

    Book  MATH  Google Scholar 

  19. Tan, S., Wang, R., Ward, M.M.: Syndesmophyte growth in ankylosing spondylitis. Curr. Opin. Rheumatol. 27, 326–332 (2015)

    Article  Google Scholar 

  20. Xu, X., Lee, D.J., Antani, S., Long, L.R.: A spine X-ray image retrieval system using partial shape matching. IEEE Trans. Inf. Technol. Biomed. 12, 100–108 (2008)

    Article  Google Scholar 

  21. Xu, X., Lee, D.J., Antani, S., Long, L.R.: Localizing contour points for indexing an X-ray image retrieval system. In: Proceedings of the 16th IEEE Symposium on Computer-Based Medical Systems, New York, pp. 169–174, 26–27 June 2003

    Google Scholar 

  22. Zamora, G., Sari-Sarraf, H., Long, R.: Hierarchical segmentation of vertebrae from X-ray images. In: Proceedings of SPIE, Medical Imaging 2003: Image Processing, vol. 5032, p. 631 (2003)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Chair of Geoinformatics and Applied Computer Science, Faculty of Geology, Geophysics and Environmental Protection, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059, Kraków, Poland

    Marzena Bielecka

  2. Chair of Applied Computer Science, Faculty of Electrical Engineering, Automation, Computer Science and Biomedical Engineering, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059, Kraków, Poland

    Andrzej Bielecki

Authors
  1. Marzena Bielecka
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Andrzej Bielecki
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Marzena Bielecka .

Editor information

Editors and Affiliations

  1. Faculty of Applied Informatics and Mathematics, Warsaw University of Life Sciences, Warsaw, Poland

    Leszek J. Chmielewski

  2. Faculty of Applied Informatics and Mathematics, Warsaw University of Life Sciences, Warsaw, Poland

    Ryszard Kozera

  3. Faculty of Applied Informatics and Mathematics, Warsaw University of Life Sciences, Warsaw, Poland

    Arkadiusz Orłowski

  4. Institute of Computer Science, Silesian University of Technology, Gliwice, Poland

    Konrad Wojciechowski

  5. Technion, Israel Institute of Technology, Haifa, Israel

    Alfred M. Bruckstein

  6. University of Groningen, Groningen, The Netherlands

    Nicolai Petkov

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Bielecka, M., Bielecki, A. (2018). Localizing Characteristic Points on a Vertebra Contour by Using Shape Language. In: Chmielewski, L., Kozera, R., Orłowski, A., Wojciechowski, K., Bruckstein, A., Petkov, N. (eds) Computer Vision and Graphics. ICCVG 2018. Lecture Notes in Computer Science(), vol 11114. Springer, Cham. https://doi.org/10.1007/978-3-030-00692-1_30

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-00692-1_30

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00691-4

  • Online ISBN: 978-3-030-00692-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation