Skip to main content

Similarity Retrieval of Angiogram Images BASED on a Flexible Shape Model

  • Conference paper
Functional Imaging and Modeling of the Heart (FIMH 2013)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7945))

  • 2917 Accesses

Abstract

In this paper we address the problem of finding similar coronary angiograms from a database of angiograms using a new constrained nonrigid shape model for the description of coronary arteries. The model captures the non-rigid variations in the artery shapes while still preserving the overall perceptual spatial layout based on the articulation constraints between arteries. Shape matching involves testing for class membership using the constraints specified in the model. The shape similarity method is demonstrated in a similarity retrieval application on a large database of angiogram images.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • 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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Medis medical imaging systems, Inc., http://www.medis.nl/index.htm

  2. Belongie, S., Malik, J., Puzicha, J.: Shape matching and object recognition using shape contexts. IEEE Trans. PAMI 24, 509–522 (2002)

    Article  Google Scholar 

  3. Frangi, A.F., Niessen, W.J., Vincken, K.L., Viergever, M.A.: Multiscale vessel enhancement filtering. In: Wells, W.M., Colchester, A.C.F., Delp, S.L. (eds.) MICCAI 1998. LNCS, vol. 1496, pp. 130–137. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  4. Grauman, K., Darrell, T.: The pyramid match kernel: Efficient learning with sets of features. Journal of Machine Learning Research, 725–760 (2007)

    Google Scholar 

  5. Haris, K., Efstratiadis, S., Maglaveras, N., Pappas, C., Gourassas, J., Louridas, G.: Model-based morphological segmentation and labeling of coronary angiograms. IEEE-TMI 18(10), 1003–1015 (1999)

    Google Scholar 

  6. Perfetti, R., Ricci, E., Casali, D., Costantini, G.: A cnn based algorithm for retinal vessel segmentation. In: ICC 2008: Proceedings of the 12th WSEAS International Conference on Circuits, pp. 152–157 (2008)

    Google Scholar 

  7. Sato, Y., Nakajima, S., Shiraga, N., Atsumi, H., Yoshida, S., Koller, T., Gerig, G., Kikinis, R.: Three-dimensional multi-scale line filter for segmentation and visualization of curvilinear structures in medical images. IEEE Medical Image Analysis, 143–168 (1998)

    Google Scholar 

  8. Syeda-Mahmood, T., Beymer, D., Wang, F.: Shape-based matching of ECG recordings. IEEE EMBC, 2012–2018 (2007)

    Google Scholar 

  9. Syeda-Mahmood, T., Beymer, D., Wang, F., Mahmood, A., Lundstrom, R., Shafee, N., Holve, T.: Automatic selection of keyframes from angiogram videos. In: ICPR, pp. 4008–4011 (2010)

    Google Scholar 

  10. Syeda-Mahmood, T., Turaga, P., Beymer, D., Wang, F., Amir, A., Greenspan, H., Pohl, K.: Shape-based similarity retrieval of doppler images for clinical decision support. In: IEEE CVPR, pp. 855–862 (2010)

    Google Scholar 

  11. Cormen, T., et al.: Introduction to algorithms, p. 1985. MIT Press (1985)

    Google Scholar 

  12. Yeh, M., Cheng, K.T.: A string matching approach for visual retrieval and classification. In: ACM-MIR (2008)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Syeda-Mahmood, T., Compas, C.B., Beymer, D., Kumar, R. (2013). Similarity Retrieval of Angiogram Images BASED on a Flexible Shape Model. In: Ourselin, S., Rueckert, D., Smith, N. (eds) Functional Imaging and Modeling of the Heart. FIMH 2013. Lecture Notes in Computer Science, vol 7945. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38899-6_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-38899-6_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38898-9

  • Online ISBN: 978-3-642-38899-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics