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Segmentierung von Blutgefäßen in retinalen Fundusbildern

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Book cover Bildverarbeitung für die Medizin 2012

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

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Kurzfassung

Blutgefäßstrukturen im Auge sind bei der Diagnose einer Vielzahl von Krankheiten von herausragender Bedeutung. Arteriosklerose, Retinopathie, Mikroembolien und Makuladegeneration z.B. gehen mit einer Veränderung der Blutgefäßstruktur im Auge einher. Das vorgestellte Verfahren zur Segmentierung von Blutgefäßen nutzt unter anderem eine angepasste Variante der Phasensymmetrie nach Kovesi und einen Hystereseschritt. Der Algorithmus wurde auf Basis der öffentlichen Bilderdatenbanken DRIVE und STARE evaluiert und die Ergebnisse (DRIVE: 94, 92%, Sensitivität 71, 22% und Spezifität 98, 41%, STARE: 95, 65%, Sensitivität 71, 87% und Spezifität 98, 34%) wurden mit anderen Verfahren aus der Literatur verglichen.

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Literaturverzeichnis

  1. Staal J, Abramoff MD, Niemeijer M, et al. Ridge-based vessel segmentation in color images of the retina. IEEE Trans Med Imaging. 2004;23(4):501–9.

    Article  Google Scholar 

  2. Budai A, Michelson G, Hornegger J. Multiscale blood vessel segmentation in retinal fundus images. In: Proc BVM; 2010. p. 261–5.

    Google Scholar 

  3. Wu CH, Agam G, Stanchev P. A hybrid filtering approach to retinal vessel segmentation. In: Proc ISBI; 2007. p. 604–7.

    Google Scholar 

  4. Sofka M, Stewart CV. Retinal vessel centerline extraction using multiscale matched filters, confidence and edge measures. IEEE Trans Med Imaging. 2006;25(12):1531–46.

    Article  Google Scholar 

  5. Sofka M, Stewart CV. Erratum to “Retinal vessel centerline extraction using multiscale matched filters, confidence and edge measures”. IEEE Trans Med Imaging. 2007;26(1):133.

    Article  Google Scholar 

  6. Chaudhuri S, Chatterjee S, Katz N, et al. Detection of blood vessels in retinal images using two-dimensional matched filters. IEEE Trans Med Imaging. 1989;8(3):263–9.

    Article  Google Scholar 

  7. Hoover AD, Kouznetsova V, Goldbaum M. Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response. IEEE Trans Med Imaging. 2000;19(3):203–10.

    Article  Google Scholar 

  8. Rezatofighi SH, Roodaki A, Pourmorteza A, et al. Polar run-length features in segmentation of retinal blood vessels. In: Proc. IDIPC; 2009. p. 72–5.

    Google Scholar 

  9. Ricci E, Perfetti R. Retinal blood vessel segmentation using line operators and support vector classification. IEEE Trans Med Imaging. 2007;26(10):1357–65.

    Article  Google Scholar 

  10. Soares JVB, Leandro JJG, Cesar RM, et al. Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification. IEEE Trans Med Imaging. 2006;25(9):1214–22.

    Article  Google Scholar 

  11. Kovesi P. Symmetry and asymmetry from local phase. In: Proc 10th Australian JCAI; 1997. p. 2–4.

    Google Scholar 

  12. Sethian JA. A fast marching level set method for monotonically advancing fronts. In: Proc Nat Acad Sci; 1995. p. 1591–5.

    Google Scholar 

  13. Niemeijer M, Staal JJ, van Ginneken B, et al. Comparative study of retinal vessel segmentation methods on a new publicly available database. Proc SPIE. 2004;5370:648–56.

    Article  Google Scholar 

  14. Alonso-Montes C, Vilari˜no DL, Dudek P, et al. Fast retinal vessel tree extraction: a pixel parallel approach. Int J Circuit Theory Appl. 2008;36:641–51.

    Article  Google Scholar 

  15. Farzin H, Moghaddam HA, Moin MS. A novel retinal identification system. EURASIP J Adv Sig Proc. 2008.

    Google Scholar 

  16. Fraz MM, Javed MY, Basit A. Evaluation of retinal vessel segmentation methodologies based on combination of vessel centerlines and morphological processing. In: Proc. Emerging Technologies ICET; 2008. p. 232–6.

    Google Scholar 

  17. Lam BSY, Yan H. A novel vessel segmentation algorithm for pathological retina images based on the divergence of vector fields. IEEE Trans Med Imaging. 2008;27(2):237–46.

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Lehrstuhl für Bildverarbeitung, RWTH Aachen University, Aachen, Deutschland

    Sebastian Gross, Monika Klein, Alexander Behrens & Til Aach

Authors
  1. Sebastian Gross
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  2. Monika Klein
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  3. Alexander Behrens
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  4. Til Aach
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Corresponding author

Correspondence to Sebastian Gross .

Editor information

Editors and Affiliations

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

    Thomas Tolxdorff

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

    Thomas Martin Deserno

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

    Heinz Handels

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

    Hans-Peter Meinzer

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© 2012 Springer-Verlag Berlin Heidelberg

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Gross, S., Klein, M., Behrens, A., Aach, T. (2012). Segmentierung von Blutgefäßen in retinalen Fundusbildern. In: Tolxdorff, T., Deserno, T., Handels, H., Meinzer, HP. (eds) Bildverarbeitung für die Medizin 2012. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28502-8_45

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