title: Impact of outliers on diffusion tensor and Q-ball imaging: clinical implications and correction strategies.
abstract: OBJECTIVE
  To measure the impact of corrupted images often found to occur in diffusion-weighted magnetic resonance imaging (DW-MRI). To propose a robust method for the correction of outliers, applicable to diffusion tensor imaging (DTI) and q-ball imaging (QBI).
  
  
  METHODS
  Monte Carlo simulations were carried out to measure the impact of outliers on DTI and QBI reconstruction in a single voxel. Methods to correct outliers based on q-space interpolation and direction removal were then implemented and validated in real image data.
  
  
  RESULTS
  Corruption in a single voxel led to clear variations in DTI and QBI metrics. In real data, the method of q-space interpolation was successful in identifying corrupted voxels and restoring them to values consistent with those of uncorrupted images.
  
  
  CONCLUSIONS
  For images containing few gradient directions, where outlier removal was either impossible due to limited volumes or resulted in large changes in DTI/QBI metrics, q-space interpolation proved to be the method of choice for image restoration. A simple decision support system is proposed to assist clinicians in the correction of their corrupted DW data.
authors: UMR-S975, CRICM-INSERM-UPMC, Paris, Île-de-France, France. michael.sharman@etu.upmc.fr
authors: Michael A
authors: MA
authors: Sharman
authors: Julien
authors: J
authors: Cohen-Adad
authors: Maxime
authors: M
authors: Descoteaux
authors: Arnaud
authors: A
authors: Messé
authors: Habib
authors: H
authors: Benali
authors: Stéphane
authors: S
authors: Lehericy