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2D Vessel Segmentation Using Local Adaptive Contrast Enhancement

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Bildverarbeitung für die Medizin 2011

Part of the book series: Informatik aktuell ((INFORMAT))

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Abstract

2D vessel segmentation algorithms working on 2D digital subtraction angiography (DSA) images suffer from inhomogeneous contrast agent distributions within the vessels. In this work, we present a novel semi-automatic vessel segmentation method based on local adaptive contrast enhancement. Either a forward projected 3D centerline or a set of manual selected seed points define the vessel branches to be segmented on the image. The algorithm uses bilateral filtering followed by local contrast enhancement to eliminate intensity inhomogeneity within the vessel region that is caused by unequally distributed contrast agent. Our segmentation algorithm is extensively evaluated on 45 different DSA images and exhibits an average Hausdorff distance of 22 pixels and sensitivity of 89 %.

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References

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Author information

Authors and Affiliations

  1. Pattern Recognition Lab, University Erlangen-Nuremberg, Erlangen-Nuremberg, Germany

    Dominik Schuldhaus, Martin Spiegel, Maria Polyanskaya & Joachim Hornegger

  2. Department of Neuroradiology, University Erlangen-Nuremberg, Erlangen-Nuremberg, Germany

    Dominik Schuldhaus, Martin Spiegel, Tobias Struffert & Arnd Doerfler

  3. Siemens AG Healthcare Sector, Forchheim, Germany

    Martin Spiegel, Thomas Redel & Maria Polyanskaya

  4. Erlangen Graduate School in Advanced Optical Technologies, SAOT, Erlangen, Germany

    Martin Spiegel & Joachim Hornegger

Authors
  1. Dominik Schuldhaus
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  2. Martin Spiegel
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  3. Thomas Redel
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  4. Maria Polyanskaya
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  5. Tobias Struffert
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  6. Joachim Hornegger
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  7. Arnd Doerfler
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Corresponding author

Correspondence to Martin Spiegel .

Editor information

Editors and Affiliations

  1. , Institut für Medizinische Informatik, Universität zu Lübeck, Ratzeburger Allee 160, Lübeck, 23562, Germany

    Heinz Handels

  2. , Institut für Medizinische Informatik, Universität Lübeck, Ratzeburger Allee 160, Lübeck, 23538, Germany

    Jan Ehrhardt

  3. Inst. Medizinische Informatik, RWTH Aachen, Pauwelsstr. 30, Aachen, 52074, Germany

    Thomas M. Deserno

  4. Abt. Med./Biol.Inform./H0100, Deutsches Krebsforschungzentrum (DKFZ), Im Neuenheimer Feld 280, Heidelberg, 69120, Germany

    Hans-Peter Meinzer

  5. Charité Campus Benjamin Franklin, Inst. Medizinische Informatik,, Universitätsklinikum Berlin, Hindenburgdamm 30, Berlin, 12200, Berlin, Germany

    Thomas Tolxdorff

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© 2011 Springer-Verlag Berlin Heidelberg

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Schuldhaus, D. et al. (2011). 2D Vessel Segmentation Using Local Adaptive Contrast Enhancement. In: Handels, H., Ehrhardt, J., Deserno, T., Meinzer, HP., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2011. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19335-4_24

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