Literature DB >> 21995019

Assessment of bias for MRI diffusion tensor imaging using SIMEX.

Carolyn B Lauzon1, Andrew J Asman, Ciprian Crainiceanu, Brian C Caffo, Bennett A Landman.   

Abstract

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 modem 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.

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Year:  2011        PMID: 21995019      PMCID: PMC3197727          DOI: 10.1007/978-3-642-23629-7_14

Source DB:  PubMed          Journal:  Med Image Comput Comput Assist Interv


  13 in total

1.  Statistical artifacts in diffusion tensor MRI (DT-MRI) caused by background noise.

Authors:  P J Basser; S Pajevic
Journal:  Magn Reson Med       Date:  2000-07       Impact factor: 4.668

2.  From the diffusion coefficient to the diffusion tensor.

Authors:  Denis Le Bihan; Peter van Zijl
Journal:  NMR Biomed       Date:  2002 Nov-Dec       Impact factor: 4.044

3.  Noise measurement from magnitude MRI using local estimates of variance and skewness.

Authors:  Jeny Rajan; Dirk Poot; Jaber Juntu; Jan Sijbers
Journal:  Phys Med Biol       Date:  2010-08-03       Impact factor: 3.609

4.  Multi-parametric neuroimaging reproducibility: a 3-T resource study.

Authors:  Bennett A Landman; Alan J Huang; Aliya Gifford; Deepti S Vikram; Issel Anne L Lim; Jonathan A D Farrell; John A Bogovic; Jun Hua; Min Chen; Samson Jarso; Seth A Smith; Suresh Joel; Susumu Mori; James J Pekar; Peter B Barker; Jerry L Prince; Peter C M van Zijl
Journal:  Neuroimage       Date:  2010-11-20       Impact factor: 6.556

5.  Maximum a posteriori estimation of diffusion tensor parameters using a Rician noise model: why, how and but.

Authors:  Jesper L R Andersson
Journal:  Neuroimage       Date:  2008-06-06       Impact factor: 6.556

6.  Noise estimation in single- and multiple-coil magnetic resonance data based on statistical models.

Authors:  Santiago Aja-Fernández; Antonio Tristán-Vega; Carlos Alberola-López
Journal:  Magn Reson Imaging       Date:  2009-06-30       Impact factor: 2.546

7.  Diffusion tensor imaging at low SNR: nonmonotonic behaviors of tensor contrasts.

Authors:  Bennett A Landman; Jonathan A D Farrell; Hao Huang; Jerry L Prince; Susumu Mori
Journal:  Magn Reson Imaging       Date:  2008-05-21       Impact factor: 2.546

8.  The Rician distribution of noisy MRI data.

Authors:  H Gudbjartsson; S Patz
Journal:  Magn Reson Med       Date:  1995-12       Impact factor: 4.668

9.  "Squashing peanuts and smashing pumpkins": how noise distorts diffusion-weighted MR data.

Authors:  Derek K Jones; Peter J Basser
Journal:  Magn Reson Med       Date:  2004-11       Impact factor: 4.668

10.  Robust estimation of spatially variable noise fields.

Authors:  Bennett A Landman; Pierre-Louis Bazin; Seth A Smith; Jerry L Prince
Journal:  Magn Reson Med       Date:  2009-08       Impact factor: 4.668

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  4 in total

1.  A deep learning approach to estimation of subject-level bias and variance in high angular resolution diffusion imaging.

Authors:  Allison E Hainline; Vishwesh Nath; Prasanna Parvathaneni; Kurt G Schilling; Justin A Blaber; Adam W Anderson; Hakmook Kang; Bennett A Landman
Journal:  Magn Reson Imaging       Date:  2019-03-26       Impact factor: 2.546

2.  Towards Automatic Quantitative Quality Control for MRI.

Authors:  Carolyn B Lauzon; Brian C Caffo; Bennett A Landman
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2012-02-23

3.  Empirical single sample quantification of bias and variance in Q-ball imaging.

Authors:  Allison E Hainline; Vishwesh Nath; Prasanna Parvathaneni; Justin A Blaber; Kurt G Schilling; Adam W Anderson; Hakmook Kang; Bennett A Landman
Journal:  Magn Reson Med       Date:  2018-02-06       Impact factor: 4.668

4.  A hitchhiker's guide to diffusion tensor imaging.

Authors:  José M Soares; Paulo Marques; Victor Alves; Nuno Sousa
Journal:  Front Neurosci       Date:  2013-03-12       Impact factor: 4.677

  4 in total

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