High-Precision Computer-Assisted Segmentation of Multispectral MRI Data Sets in Patients with Multiple Sclerosis by a Flexible Machine Learning Image Analysis Approach

  • Axel Wismüller
  • Johannes Behrends
  • Oliver Lange
  • Miriana Jukic
  • Klaus Hahn
  • Maximilian Reiser
  • Dorothee Auer
Conference paper

DOI: 10.1007/978-3-642-18993-7_82

Part of the Informatik aktuell book series (INFORMAT)
Cite this paper as:
Wismüller A. et al. (2003) High-Precision Computer-Assisted Segmentation of Multispectral MRI Data Sets in Patients with Multiple Sclerosis by a Flexible Machine Learning Image Analysis Approach. In: Wittenberg T., Hastreiter P., Hoppe U., Handels H., Horsch A., Meinzer HP. (eds) Bildverarbeitung für die Medizin 2003. Informatik aktuell. Springer, Berlin, Heidelberg

Abstract

Automatic brain segmentation is an issue of specific clinical relevance in both diagnosis and therapy control of patients with demyelinating diseases such as Multiple Sclerosis (MS). We present a complete system for high-precision computer-assisted image analysis of multispectral MRI data based on a flexible machine learning approach. Careful quality evaluation shows that the system outperforms conventional threshold-based techniques w.r.t. inter-observer agreement levels for the quantification of relevant clinical parameters, such as white matter lesion load and brain parenchyma volume.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Axel Wismüller
    • 1
  • Johannes Behrends
    • 1
  • Oliver Lange
    • 1
  • Miriana Jukic
    • 1
  • Klaus Hahn
    • 2
  • Maximilian Reiser
    • 1
  • Dorothee Auer
    • 3
  1. 1.Institut für Klinische Radiologie, Klinikum der Universität MünchenLudwig-Maximilians-Universität MünchenMünchen
  2. 2.Klinik und Poliklinik für Nuklearmedizin, Klinikum der Universität MünchenLudwig-Maximilians-Universität MünchenMünchen
  3. 3.Max-Planck-Institut für PsychiatrieMünchen

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