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Application of a Mamdani-Type Fuzzy Rule-Based System to Segment Periventricular Cerebral Veins in Susceptibility-Weighted Images

  • Francesc Xavier AymerichEmail author
  • Pilar Sobrevilla
  • Eduard Montseny
  • Alex Rovira
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 610)

Abstract

This paper presents an algorithm designed to segment veins in the periventricular region of the brain in susceptibility-weighted magnetic resonance images. The proposed algorithm is based on a Mamdani-type fuzzy rule-based system that enables enhancement of veins within periventricular regions of interest as the first step. Segmentation is achieved after determining the cut-off value providing the best trade-off between sensitivity and specificity to establish the suitability of each pixel to belong to a cerebral vein. Performance of the algorithm in susceptibility-weighted images acquired in healthy volunteers showed very good segmentation, with a small number of false positives. The results were not affected by small changes in the size and location of the regions of interest. The algorithm also enabled detection of differences in the visibility of periventricular veins between healthy subjects and multiple sclerosis patients.

Keywords

Brain Fuzzy rule-based systems Image segmentation Magnetic resonance imaging 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Francesc Xavier Aymerich
    • 1
    • 2
    Email author
  • Pilar Sobrevilla
    • 3
  • Eduard Montseny
    • 2
  • Alex Rovira
    • 1
  1. 1.MR Unit, Department of Radiology (IDI), Vall d’Hebron University Hospital, Vall d’Hebron Research Institute (VHIR)Autonomous University of BarcelonaBarcelonaSpain
  2. 2.ESAII DepartmentUniversitat Politècnica de CatalunyaBarcelonaSpain
  3. 3.MAII DepartmentUniversitat Politècnica de CatalunyaBarcelonaSpain

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