Literature DB >> 11378884

Utilizing the diffusion-to-noise ratio to optimize magnetic resonance diffusion tensor acquisition strategies for improving measurements of diffusion anisotropy.

P A Armitage1, M E Bastin.   

Abstract

It is well known that quantitative anisotropy measurements derived from the diffusion tensor are extremely sensitive to noise contamination. The level of noise in the diffusion tensor imaging (DTI) experiment is usually measured from some estimate of the signal-to-noise ratio (SNR) in the component diffusion-weighted (DW) images. This measure is, however, highly dependent on experimental parameters, such as the diffusion attenuation b-value and the diffusion coefficient of the subject. Conversely, the diffusion-to-noise ratio (DNR), defined as the SNR of the calculated diffusion tensor trace map, provides a reliable estimate of noise contamination, which is largely independent of such parameters. In this work it is demonstrated how reliable anisotropy measurements can be obtained using an image acquisition strategy that optimizes the DNR of the DTI experiment. This acquisition scheme is shown to provide noise-independent measurements of typical diffusion anisotropy values found in the human brain. Copyright 2001 Wiley-Liss, Inc.

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Mesh:

Year:  2001        PMID: 11378884     DOI: 10.1002/mrm.1140

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  12 in total

1.  Voxel-based analysis of the diffusion tensor.

Authors:  Osamu Abe; Hidemasa Takao; Wataru Gonoi; Hiroki Sasaki; Mizuho Murakami; Hiroyuki Kabasawa; Hiroshi Kawaguchi; Masami Goto; Haruyasu Yamada; Hidenori Yamasue; Kiyoto Kasai; Shigeki Aoki; Kuni Ohtomo
Journal:  Neuroradiology       Date:  2010-05-14       Impact factor: 2.804

Review 2.  Diffusion tensor MR imaging and fiber tractography: technical considerations.

Authors:  P Mukherjee; S W Chung; J I Berman; C P Hess; R G Henry
Journal:  AJNR Am J Neuroradiol       Date:  2008-03-13       Impact factor: 3.825

3.  Effects of signal-to-noise ratio on the accuracy and reproducibility of diffusion tensor imaging-derived fractional anisotropy, mean diffusivity, and principal eigenvector measurements at 1.5 T.

Authors:  Jonathan A D Farrell; Bennett A Landman; Craig K Jones; Seth A Smith; Jerry L Prince; Peter C M van Zijl; Susumu Mori
Journal:  J Magn Reson Imaging       Date:  2007-09       Impact factor: 4.813

4.  Decoupling of imaging and diffusion gradients in DTI.

Authors:  Alpay Ozcan
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2009

5.  Test-retest reliability of high angular resolution diffusion imaging acquisition within medial temporal lobe connections assessed via tract based spatial statistics, probabilistic tractography and a novel graph theory metric.

Authors:  T Kuhn; J M Gullett; P Nguyen; A E Boutzoukas; A Ford; L M Colon-Perez; W Triplett; P R Carney; T H Mareci; C C Price; R M Bauer
Journal:  Brain Imaging Behav       Date:  2016-06       Impact factor: 3.978

6.  Minimization of imaging gradient effects in diffusion tensor imaging.

Authors:  Alpay Özcan
Journal:  IEEE Trans Med Imaging       Date:  2011-03       Impact factor: 10.048

7.  High-resolution reduced field of view diffusion tensor imaging using spatially selective RF pulses.

Authors:  Wolfgang Gaggl; Andrzej Jesmanowicz; Robert W Prost
Journal:  Magn Reson Med       Date:  2014-01-07       Impact factor: 4.668

8.  Geometric analysis of the b-dependent effects of Rician signal noise on diffusion tensor imaging estimates and determining an optimal b value.

Authors:  Paul A Taylor; Bharat Biswal
Journal:  Magn Reson Imaging       Date:  2011-05-08       Impact factor: 2.546

Review 9.  Diffusion tensor imaging and beyond.

Authors:  Jacques-Donald Tournier; Susumu Mori; Alexander Leemans
Journal:  Magn Reson Med       Date:  2011-04-05       Impact factor: 4.668

10.  The impact of quality assurance assessment on diffusion tensor imaging outcomes in a large-scale population-based cohort.

Authors:  David R Roalf; Megan Quarmley; Mark A Elliott; Theodore D Satterthwaite; Simon N Vandekar; Kosha Ruparel; Efstathios D Gennatas; Monica E Calkins; Tyler M Moore; Ryan Hopson; Karthik Prabhakaran; Chad T Jackson; Ragini Verma; Hakon Hakonarson; Ruben C Gur; Raquel E Gur
Journal:  Neuroimage       Date:  2015-10-28       Impact factor: 6.556

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