2011 | OriginalPaper | Chapter
Quantitative Body DW-MRI Biomarkers Uncertainty Estimation Using Unscented Wild-Bootstrap
Authors : M. Freiman, S. D. Voss, R. V. Mulkern, J. M. Perez-Rossello, S. K. Warfield
Published in: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2011
Publisher: Springer Berlin Heidelberg
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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.