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Texture Analysis Using Gabor Filter Based on Transcranial Sonography Image

Lei Chen, Johann Hagenah, Alfred Mertins

Abstract

Transcranial sonography (TCS) is a new tool for the diagnosis of Parkinson's disease (PD) at a very early state. The TCS image of the mesencephalon shows a distinct hyperechogenic pattern in about 90% PD patients. This pattern is usually manually segmented and the substantia nigra (SN) region can be used as an early PD indicator. However this method is based on manual evaluation of examined images. We propose a texture analysis method using Gabor filters for the early PD risk assessment. The features are based on the local spectrum, which is obtained by a bank of Gabor filters, and the performance of these features is evaluated by feature selection method. The results show that the accuracy of the classification with the feature subset is reaching 92.73%.
Original languageEnglish
Title of host publicationBildverarbeitung für die Medizin 2011: Algorithmen - Systeme - Anwendungen Proceedings des Workshops vom 20. - 22. März 2011 in Lübeck
EditorsHeinz Handels, Jan Ehrhardt, Thomas M. Deserno, Hans-Peter Meinzer, Thomas Tolxdorff
Number of pages5
Place of PublicationBerlin, Heidelberg
PublisherSpringer Berlin Heidelberg
Publication date13.03.2011
Pages249-253
ISBN (Print)978-3-642-19334-7
ISBN (Electronic)978-3-642-19335-4
DOIs
Publication statusPublished - 13.03.2011
EventWorkshops Bildverarbeitung fur die Medizin 2011 - Lübeck, Germany
Duration: 20.03.201122.03.2011
Conference number: 99531

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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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