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Bildverarbeitung für die Medizin 2012 pp 27–32Cite as

Improved Image Segmentation with Prospective Motion Correction in MRI

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

Abstract

Artifacts caused by patient motion during a magnetic resonance imaging (MRI) scan can corrupt the image data, reduce the effective resolution and make further processing difficult or impossible. Long measurements, as required for high resolution imaging, are particularly prone to motion artifacts, as motion is more likely to occur over longer scan periods. These artifacts can lead to problems in the further image processing of the data. Prospective motion correction offers a possibility to correct for patient motion during the measurement and avoid motion artifacts. Image data from comparative brain scans with and without motion correction are presented and analyzed. Segmentation of gray matter (GM) and white matter (WM) was performed on both datasets using the software packages SPM and Freesurfer, which are widely used in neuroscience studies. The results show that motion correction significantly improves the segmentation quality and suggest that it is also useful for other image processing applications performed on MRI data.

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Author information

Authors and Affiliations

  1. Biomedical Magnetic Resonance, IEP, Otto-von-Guericke University Magdeburg, Magdeburg, Deutschland

    Daniel Stucht, Shan Yang, Peter Schulze, Appu Danishad, Ilja Kadashevich & Oliver Speck

  2. Institute for Biometry and Medical Informatics, University Hospital of Magdeburg, Magdeburg, Deutschland

    Johannes Bernarding

  3. Medical Physics, Department of Radiology, University Medical Center Freiburg, Freiburg, Deutschland

    Julian Maclaren & Maxim Zaitsev

Authors
  1. Daniel Stucht
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  2. Shan Yang
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  3. Peter Schulze
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  4. Appu Danishad
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  5. Ilja Kadashevich
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  6. Johannes Bernarding
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  7. Julian Maclaren
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  8. Maxim Zaitsev
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  9. Oliver Speck
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Corresponding author

Correspondence to Daniel Stucht .

Editor information

Editors and Affiliations

  1. Charité Campus Benjamin Franklin, Inst. Medizinische Informatik,, Universitätsklinikum Berlin, Hindenburgdamm 30, Berlin, 12200, Berlin, Germany

    Thomas Tolxdorff

  2. Inst. Medizinische Informatik, RWTH Aachen, Pauwelsstr. 30, Aachen, 52074, Germany

    Thomas Martin Deserno

  3. , Institut für Medizinische Informatik, Universität zu Lübeck, Ratzeburger Allee 160, Lübeck, 23562, Germany

    Heinz Handels

  4. Abt. Med./Biol.Inform./H0100, Deutsches Krebsforschungzentrum (DKFZ), Im Neuenheimer Feld 280, Heidelberg, 69120, Germany

    Hans-Peter Meinzer

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© 2012 Springer-Verlag Berlin Heidelberg

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Stucht, D. et al. (2012). Improved Image Segmentation with Prospective Motion Correction in MRI. In: Tolxdorff, T., Deserno, T., Handels, H., Meinzer, HP. (eds) Bildverarbeitung für die Medizin 2012. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28502-8_7

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