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Towards Automated OCT-based Identification of White Brain Matter

  • Conference paper
Bildverarbeitung für die Medizin 2007

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

Abstract

A novel model-based identification of white brain matter in OCT A-scans is proposed. Based on nonlinear energy operators used in the classification of neural activity, candidates for white matter structures are extracted from a baseline-corrected signal. Validation of candidates is done by evaluating the correspondence to a simplified intensity model which is parametrized beforehand. Results for identification of white matter in rat brain in vitro show the capability of the proposed algorithm.

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References

  1. Bouma BE, Tearney GJ. Handbook Of Optical Coherence Tomography. Marcel Dekker, Inc.; 2002.

    Google Scholar 

  2. Boehringer HJ, Boller D, Leppert J, et al. Time-domain and spectral-domain optical coherence tomography in the analysis of brain tumor tissue. Lasers in Surgery and Medicine 2006;38:588–597.

    Article  Google Scholar 

  3. Jeon SW, Shure MA, Baker KB, etal. Optical coherence tomography and optical coherence domain reflectometry for deep brain stimulation probe guidance. Procs SPIE 2005;5686:487–494.

    Article  Google Scholar 

  4. Safri MS, Farhang S, Tang RS, et al. Optical coherence tomography in the diagnosis and treatment of neurological disorders. J Biomed Opt 2005;10(5):1–11.

    Google Scholar 

  5. Kim KW, Kim SJ. Neural spike sorting under nearly 0-dB signal-to-noise ratio using nonlinear energy operator and artificial neural-network classifier. IEEE Trans Biomed Eng 2000;47:1406–1411.

    Article  Google Scholar 

  6. Menne KL. Computerassistenz zur Implantation von Tiefenhirnstimulatoren. Ph.D. thesis. University of Luebeck; 2005.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Institut für Robotik und Kognitive Systeme, Deutschland

    Lukas Ramrath & Achim Schweikard

  2. Institut für Signalverarbeitung und Prozessrechentechnik, Deutschland

    Ulrich G. Hofmann

  3. Institut für Biomedizinische Optik, Deutschland

    Gereon Huettmann

  4. Klinik für Neurologie, UK-SH, Campus Lübeck, 23538, Lübeck

    Andreas Moser

Authors
  1. Lukas Ramrath
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  2. Ulrich G. Hofmann
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  3. Gereon Huettmann
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  4. Andreas Moser
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  5. Achim Schweikard
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Editor information

Editors and Affiliations

  1. Klinikum rechts der Isar Institut für Medizinische Statistik und Epidemiologie, Technische Universität München, Ismaninger Strasse 22, 81675, München

    Alexander Horsch

  2. Institut für Medizinische Informatik, Rheinisch-Westfälische Technische Hochschule Aachen, Pauwelsstrasse 30, 52057, Aachen

    Thomas M. Deserno

  3. Institut für Medizinische Informatik, Universitätsklinikum Hamburg-Eppendorf, Martinistrasse 52, 20246, Hamburg

    Heinz Handels

  4. Abt. für Medizinische und Biologische Informatik / H0100, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, 69120, Heidelberg

    Hans-Peter Meinzer

  5. Institut für Medizinische Informatik, Universitätsmedizin Berlin, Campus Benjamin Franklin Hindenburgdamm 30, 12200, Berlin

    Thomas Tolxdorff (Charité) (Charité)

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© 2007 Springer-Verlag Berlin Heidelberg

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Ramrath, L., Hofmann, U.G., Huettmann, G., Moser, A., Schweikard, A. (2007). Towards Automated OCT-based Identification of White Brain Matter. In: Horsch, A., Deserno, T.M., Handels, H., Meinzer, HP., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2007. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71091-2_83

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