title: Correction strategy for diffusion-weighted images corrupted with motion: application to the DTI evaluation of infants' white matter.
abstract: OBJECTIVE
  Diffusion imaging techniques such as DTI and HARDI are difficult to implement in infants because of their sensitivity to subject motion. A short acquisition time is generally preferred, at the expense of spatial resolution and signal-to-noise ratio. Before estimating the local diffusion model, most pre-processing techniques only register diffusion-weighted volumes, without correcting for intra-slice artifacts due to motion or technical problems. Here, we propose a fully automated strategy, which takes advantage of a high orientation number and is based on spherical-harmonics decomposition of the diffusion signal.
  
  
  METHODS
  The correction strategy is based on two successive steps: 1) automated detection and resampling of corrupted slices; 2) correction for eddy current distortions and realignment of misregistered volumes. It was tested on DTI data from adults and non-sedated healthy infants.
  
  
  RESULTS
  The methodology was validated through simulated motions applied to an uncorrupted dataset and through comparisons with an unmoved reference. Second, we showed that the correction applied to an infant group enabled to improve DTI maps and to increase the reliability of DTI quantification in the immature cortico-spinal tract.
  
  
  CONCLUSIONS
  This automated strategy performed reliably on DTI datasets and can be applied to spherical single- and multiple-shell diffusion imaging.
authors: INSERM, U992, Cognitive Neuroimaging Unit, Gif-sur-Yvette, France; CEA, NeuroSpin Center, UNICOG, Gif-sur-Yvette, France; University Paris Sud, Orsay, France. Electronic address: jessica.dubois@centraliens.net.
authors: Jessica
authors: J
authors: Dubois
authors: CEA, NeuroSpin Center, UNIACT, Gif-sur-Yvette, France; INSERM, U663, Paris, France; University Paris Descartes, Paris, France.
authors: Sofya
authors: S
authors: Kulikova
authors: CEA, NeuroSpin Center, UNIACT, Gif-sur-Yvette, France; INSERM, U663, Paris, France; University Paris Descartes, Paris, France.
authors: Lucie
authors: L
authors: Hertz-Pannier
authors: University Paris Sud, Orsay, France; CEA, NeuroSpin Center, UNATI, Gif-sur-Yvette, France.
authors: Jean-François
authors: JF
authors: Mangin
authors: INSERM, U992, Cognitive Neuroimaging Unit, Gif-sur-Yvette, France; CEA, NeuroSpin Center, UNICOG, Gif-sur-Yvette, France; University Paris Sud, Orsay, France.
authors: Ghislaine
authors: G
authors: Dehaene-Lambertz
authors: University Paris Sud, Orsay, France; CEA, NeuroSpin Center, UNIRS, Gif-sur-Yvette, France.
authors: Cyril
authors: C
authors: Poupon
mesh_terms: D000328:Adult; D000465:Algorithms; D016477:Artifacts; D001331:Automation; D001921:Brain / Q000473:pathology; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D056324:Diffusion Tensor Imaging / Q000379:methods*; D005583:Fourier Analysis; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D007223:Infant; D015233:Models, Statistical; D009068:Movement; D010363:Pattern Recognition, Automated / Q000379:methods; D015203:Reproducibility of Results; D059629:Signal-To-Noise Ratio; D014732:Vibration; D066127:White Matter / Q000473:pathology*
keywords: Artifact; Brain; Diffusion imaging; MRI; Motion; Vibration