Skip to main content
Springer Nature Link
Log in

Analysis of the Hand’s Small Vessels Based on MR Angiography and Level-Set Approach

  • Conference paper
Computer Vision and Graphics (ICCVG 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8671))

Included in the following conference series:

Abstract

The article describes a method for segmentation and analysis of small blood hand vessels in 3D magnetic resonance contrast angiography data obtained with collaboration of Department of Diagnostic Imaging, Medical University of Lodz. The main algorithm used for vasculature extraction implements a 3D version of level-set method based on Chan-Vese mathematical model. The image analysis was performed for two different contrast agents. Preliminary segmentation results were presented and discussed, along with further research plans.

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
$34.99 /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
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

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.

Similar content being viewed by others

References

  1. Corot, C., Violas, X., Robert, P., Gagneur, G., Port, M.: Comparison of different types of blood pool agents (P792, MS325, USPIO) in a rabbit MR angiography-like protocol. Invest. Radiol. 38(6), 311–319 (2003)

    Google Scholar 

  2. Gutzeit, A., et al.: Clinical experience in timed arterial compression contrast-enhanced magnetic resonance angiography of the hand. CA Radiologist Journal 61, 206–216 (2010)

    Article  Google Scholar 

  3. Kassamali, R.H., Hoey, E., Ganeshan, A., Littlehales, T.: A comparative analysis of noncontrast flow-spoiled versus contrast-enhanced magnetic resonance angiography for evaluation of peripheral arterial disease. Diagnostic and Interventional Radiology 19(2), 119–125 (2013)

    Google Scholar 

  4. Nikolaou, K., Kramer, H., Grosse, C., Clevert, D., Dietrich, O., Hartmann, M.: High-spatial-resolution multistation MR angiography with parallel imaging and blood pool contrast agent: initial experience. Radiology 241(3), 861–872 (2006)

    Article  Google Scholar 

  5. Wang, A.S., Bech, F., Lee, J., Taylor, C.A., Liang, D.H.: Developing an arterial bleed detection algorithm for diagnostic ultrasound. In: Proc. of IEEE International Ultrasonics Symposium, IUS 2008, Beijing, China, November 2-5, pp. 1627–1630 (2008)

    Google Scholar 

  6. Strzelecki, M., Szczypinski, P., Materka, A., Klepaczko, A.: A software tool for automatic classification and segmentation of 2D/3D medical images. Nuclear Instruments & Methods in Physics Research A 702, 137–140 (2013)

    Article  Google Scholar 

  7. Lesage, D., Angelini, E., Bloch, I., Funka-Lea, G.: A review of 3D vessel lumen segmentation techniques: Models, features and extraction schemes. Medical Image Analysis 13, 819–845 (2009)

    Article  Google Scholar 

  8. Strzelecki, M., Szczypinski, P., Materka, A., Kocinski, M., Sankowski, A.: Level-set segmentation of noisy 3D images of numerically simulated blood vessels and vascular trees. In: Proceedings of 6th International Symposium on Image and Signal Processing and Analysis, Salzburg, Austria, September 16-18, pp. 742–747 (2009)

    Google Scholar 

  9. Chan, T.F., Vese, L.A.: Active Contours Without Edges. IEEE Transaction on Image Processing 10(2), 266–277 (2001)

    Article  MATH  Google Scholar 

  10. Getreuer, P.: Chan-Vese Segmentation. Image Processing on Line 2, 214–224 (2012)

    Article  Google Scholar 

  11. Suri, J.S., Liu, K., Singh, S., Laxminarayan, S.N., Zeng, X., Reden, L.: Shape Recovery Algorithms Using Level Sets in 2-D/3-D Medical Imagery: A State-of-the-Art Review. IEEE Transactions on Information Technology in Biomedicine 6(1), 8–28 (2002)

    Article  Google Scholar 

  12. ImageJ official website, http://imagej.nih.gov/ij/ (visited April 10, 2014)

  13. Forkert, N.D., Schmidt-Richberg, A., Fiehler, J., Illies, T., Möller, D., Säring, D., Handels, H., Ehrhardt, J.: 3D cerebrovascular segmentation combining fuzzy vessel enhancement and level-sets with anisotropic energy weights. Magnetic Resonance Imaging 31, 262–271 (2013)

    Article  Google Scholar 

  14. Klepaczko, A., Szczypinski, P., Dwojakowski, G., Strzelecki, M., Materka, A.: Computer Simulation of Magnetic Resonance Angiography Imaging. Model Description and Validation 9(4) (April 2014), doi:10.1371/journal.pone.0093689

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Electronics, Lodz University of Technology, Wólczańska 211/215, 90-924, Łódź, Poland

    Michał Strzelecki, Tomasz Woźniak, Marek Olszycki, Konrad Szymczyk & Ludomir Stefańczyk

  2. Department of Diagnostic Imaging, Medical University of Lodz, Kopcińskiego 22, 90-154, Łódź, Poland

    Michał Strzelecki, Tomasz Woźniak, Marek Olszycki, Konrad Szymczyk & Ludomir Stefańczyk

Authors
  1. Michał Strzelecki
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tomasz Woźniak
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Marek Olszycki
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Konrad Szymczyk
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ludomir Stefańczyk
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

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

    Leszek J. Chmielewski

  2. Faculty of Applied Informatics and Mathematics, Warsaw University of Life Sciences - SGGW, Nowoursynowska str. 159, 02-776, Warsaw, Poland

    Ryszard Kozera

  3. The .enpeda.. Project, The University of Auckland, New Zealand

    Bok-Suk Shin

  4. Institute of Computer Science, Silesian University of Technology, Akademicka 16, 44-100, Gliwice, Poland

    Konrad Wojciechowski

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Strzelecki, M., Woźniak, T., Olszycki, M., Szymczyk, K., Stefańczyk, L. (2014). Analysis of the Hand’s Small Vessels Based on MR Angiography and Level-Set Approach. In: Chmielewski, L.J., Kozera, R., Shin, BS., Wojciechowski, K. (eds) Computer Vision and Graphics. ICCVG 2014. Lecture Notes in Computer Science, vol 8671. Springer, Cham. https://doi.org/10.1007/978-3-319-11331-9_74

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-11331-9_74

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11330-2

  • Online ISBN: 978-3-319-11331-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics