Quantitative body DW-MRI biomarkers uncertainty estimation using unscented wild-bootstrap

Med Image Comput Comput Assist Interv. 2011;14(Pt 2):74-81. doi: 10.1007/978-3-642-23629-7_10.


We present a new method for the uncertainty estimation of diffusion parameters for quantitative body DW-MRI assessment. Diffusion parameters uncertainty estimation from DW-MRI is necessary for clinical applications that use these parameters to assess pathology. However, uncertainty estimation using traditional techniques requires repeated acquisitions, which is undesirable in routine clinical use. Model-based bootstrap techniques, for example, assume an underlying linear model for residuals rescaling and cannot be utilized directly for body diffusion parameters uncertainty estimation due to the non-linearity of the body diffusion model. To offset this limitation, our method uses the Unscented transform to compute the residuals rescaling parameters from the non-linear body diffusion model, and then applies the wild-bootstrap method to infer the body diffusion parameters uncertainty. Validation through phantom and human subject experiments shows that our method identify the regions with higher uncertainty in body DWI-MRI model parameters correctly with realtive error of -36% in the uncertainty values.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms
  • Artifacts
  • Biomarkers / metabolism*
  • Diffusion
  • Diffusion Magnetic Resonance Imaging / methods*
  • Human Body
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Magnetic Resonance Imaging / methods
  • Models, Statistical
  • Phantoms, Imaging
  • Reproducibility of Results
  • Uncertainty


  • Biomarkers