Hyperelastic Susceptibility Artifact Correction of DTI in SPM

  • Lars Ruthotto
  • Siawoosh Mohammadi
  • Constantin Heck
  • Jan Modersitzki
  • Nikolaus Weiskopf
Conference paper

DOI: 10.1007/978-3-642-36480-8_60

Part of the Informatik aktuell book series (INFORMAT)
Cite this paper as:
Ruthotto L., Mohammadi S., Heck C., Modersitzki J., Weiskopf N. (2013) Hyperelastic Susceptibility Artifact Correction of DTI in SPM. In: Meinzer HP., Deserno T., Handels H., Tolxdorff T. (eds) Bildverarbeitung für die Medizin 2013. Informatik aktuell. Springer, Berlin, Heidelberg

Zusammenfassung

Echo Planar Imaging (EPI) is a MRI acquisition technique that is the backbone of widely used investigation techniques in neuroscience like, e.g., Diffusion Tensor Imaging (DTI). While EPI offers considerable reduction of the acquisition time one major drawback is its high sensitivity to susceptibility artifacts. Susceptibility differences between soft tissue, bone and air cause geometrical distortions and intensity modulations of the EPI data. These susceptibility artifacts severely complicate the fusion of micro-structural information acquired with EPI and conventionally acquired structural information. In this paper, we introduce a new tool for hyperelastic susceptibility correction of DTI data (HySCO) that is integrated into the Statistical Parametric Mapping (SPM) software as a toolbox. Our new correction pipeline is based on two datasets acquired with reversed phase encoding gradients. For the correction, we integrated the variational image registration approach by Ruthotto et al. 2007 into the SPM batch mode. We briefly review the model, discuss involved parameter settings and exemplarily demonstrate the effectiveness of HySCO on a human brain DTI dataset.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Lars Ruthotto
    • 1
  • Siawoosh Mohammadi
    • 2
  • Constantin Heck
    • 1
  • Jan Modersitzki
    • 1
  • Nikolaus Weiskopf
    • 2
  1. 1.Institute of Mathematics and Image ComputingUniversität zu LübeckLübeckDeutschland
  2. 2.Wellcome Trust Center for NeuroimagingUniversity College LondonLondonUK

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