Assessment of bias for MRI diffusion tensor imaging using SIMEX

Carolyn B. Lauzon, Andrew J. Asman, Ciprian Crainiceanu, Brian C. Caffo, Bennett A. Landman

Research output: Contribution to journalConference articlepeer-review

4 Scopus citations


Diffusion Tensor Imaging (DTI) is a Magnetic Resonance Imaging method for measuring water diffusion in vivo. One powerful DTI contrast is fractional anisotropy (FA). FA reflects the strength of water's diffusion directional preference and is a primary metric for neuronal fiber tracking. As with other DTI contrasts, FA measurements are obscured by the well established presence of bias. DTI bias has been challenging to assess because it is a multivariable problem including SNR, six tensor parameters, and the DTI collection and processing method used. SIMEX is a modern statistical technique that estimates bias by tracking measurement error as a function of added noise. Here, we use SIMEX to assess bias in FA measurements and show the method provides; i) accurate FA bias estimates, ii) representation of FA bias that is data set specific and accessible to non-statisticians, and iii) a first time possibility for incorporation of bias into DTI data analysis.

Original languageEnglish (US)
Pages (from-to)107-115
Number of pages9
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6892 LNCS
Issue numberPART 2
StatePublished - 2011
Event14th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2011 - Toronto, ON, Canada
Duration: Sep 18 2011Sep 22 2011


  • DTI
  • FA
  • bias
  • bias correction
  • diffusion
  • imaging
  • parameter estimation
  • tensor

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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