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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.
Original languageEnglish
Title of host publicationBildverarbeitung für die Medizin 2007
EditorsAlexander Horsch, Thomas M. Deserno, Heinz Handels, Hans-Peter Meinzer, Thomas Tolxdorff
Number of pages5
Place of PublicationBerlin, Heidelberg
PublisherSpringer Berlin Heidelberg
Publication date2007
Pages414-418
ISBN (Print)978-3-540-71090-5
ISBN (Electronic)978-3-540-71091-2
DOIs
Publication statusPublished - 2007
EventWorkshop on Bildverarbeitung fur die Medizin 2007 - Munich, Germany
Duration: 25.03.200727.03.2007
Conference number: 97564

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure
  3. SDG 10 - Reduced Inequalities
    SDG 10 Reduced Inequalities

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