Literature DB >> 10930775

Noise considerations in the determination of diffusion tensor anisotropy.

S Skare1, T Li, B Nordell, M Ingvar.   

Abstract

In this study the noise sensitivity of various anisotropy indices has been investigated by Monte-Carlo computer simulations and magnetic resonance imaging (MRI) measurements in a phantom and 5 healthy volunteers. Particularly, we compared the noise performance of indices defined solely in terms of eigenvalues and those based on both the eigenvalues and eigenvectors. It is found that anisotropy indices based on both eigenvalues and eigenvectors are less sensitive to noise, and spatial averaging with neighboring pixels can further reduce the standard deviation. To reduce the partial volume effect caused by the spatial averaging with neighboring voxels, an averaging method in the time domain based on the orientation coherence of eigenvectors in repeated experiments has been proposed.

Mesh:

Year:  2000        PMID: 10930775     DOI: 10.1016/s0730-725x(00)00153-3

Source DB:  PubMed          Journal:  Magn Reson Imaging        ISSN: 0730-725X            Impact factor:   2.546


  31 in total

1.  A statistical framework for the classification of tensor morphologies in diffusion tensor images.

Authors:  Hongtu Zhu; Dongrong Xu; Amir Raz; Xuejun Hao; Heping Zhang; Alayar Kangarlu; Ravi Bansal; Bradley S Peterson
Journal:  Magn Reson Imaging       Date:  2006-03-20       Impact factor: 2.546

2.  Whole brain voxel-wise analysis of single-subject serial DTI by permutation testing.

Authors:  Sungwon Chung; Daniel Pelletier; Michael Sdika; Ying Lu; Jeffrey I Berman; Roland G Henry
Journal:  Neuroimage       Date:  2007-11-07       Impact factor: 6.556

3.  Using the wild bootstrap to quantify uncertainty in diffusion tensor imaging.

Authors:  Brandon Whitcher; David S Tuch; Jonathan J Wisco; A Gregory Sorensen; Liqun Wang
Journal:  Hum Brain Mapp       Date:  2008-03       Impact factor: 5.038

4.  On diffusion tensor estimation.

Authors:  Marc Niethammer; Raul San Jose Estepar; Sylvain Bouix; Martha Shenton; Carl-Fredrik Westin
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2006

5.  Assessing and minimizing the effects of noise and motion in clinical DTI at 3 T.

Authors:  Rob H N Tijssen; Jacobus F A Jansen; Walter H Backes
Journal:  Hum Brain Mapp       Date:  2009-08       Impact factor: 5.038

6.  How background noise shifts eigenvectors and increases eigenvalues in DTI.

Authors:  Frederik Bernd Laun; Lothar Rudi Schad; Jan Klein; Bram Stieltjes
Journal:  MAGMA       Date:  2008-12-09       Impact factor: 2.310

7.  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

8.  On the averaging of cardiac diffusion tensor MRI data: the effect of distance function selection.

Authors:  Archontis Giannakidis; Gerd Melkus; Guang Yang; Grant T Gullberg
Journal:  Phys Med Biol       Date:  2016-10-18       Impact factor: 3.609

9.  Human brain functional MRI and DTI visualization with virtual reality.

Authors:  Bin Chen; John Moreland; Jingyu Zhang
Journal:  Quant Imaging Med Surg       Date:  2011-12

10.  A VARIATIONAL MODEL FOR DENOISING HIGH ANGULAR RESOLUTION DIFFUSION IMAGING.

Authors:  M Tong; Y Kim; L Zhan; G Sapiro; C Lenglet; B A Mueller; P M Thompson; L A Vese
Journal:  Proc IEEE Int Symp Biomed Imaging       Date:  2012
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