Methods for the computation of templates from quantitative magnetic susceptibility maps (QSM): Toward improved atlas‐ and voxel‐based analyses (VBA)

Purpose To develop and assess a method for the creation of templates for voxel‐based analysis (VBA) and atlas‐based approaches using quantitative magnetic susceptibility mapping (QSM). Materials and Methods We studied four strategies for the creation of magnetic susceptibility brain templates, deriv...

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Published inJournal of magnetic resonance imaging Vol. 46; no. 5; pp. 1474 - 1484
Main Authors Hanspach, Jannis, Dwyer, Michael G., Bergsland, Niels P., Feng, Xiang, Hagemeier, Jesper, Bertolino, Nicola, Polak, Paul, Reichenbach, Jürgen R., Zivadinov, Robert, Schweser, Ferdinand
Format Journal Article
LanguageEnglish
Published United States Wiley Subscription Services, Inc 01.11.2017
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Online AccessGet full text
ISSN1053-1807
1522-2586
1522-2586
DOI10.1002/jmri.25671

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Abstract Purpose To develop and assess a method for the creation of templates for voxel‐based analysis (VBA) and atlas‐based approaches using quantitative magnetic susceptibility mapping (QSM). Materials and Methods We studied four strategies for the creation of magnetic susceptibility brain templates, derived as successive extensions of the conventional template generation (CONV) based on only T1‐weighted (T1w) images. One method that used only T1w images involved a minor improvement of CONV (U‐CONV). One method used only magnetic susceptibility maps as input for template generation (DIRECT), and the other two used a linear combination of susceptibility and T1w images (HYBRID) and an algorithm that directly used both image modalities (MULTI), respectively. The strategies were evaluated in a group of N = 10 healthy human subjects and semiquantitatively assessed by three experienced raters. Template quality was compared statistically via worth estimates (WEs) obtained with a log‐linear Bradley‐Terry model. Results The overall quality of the templates was better for strategies including both susceptibility and T1w contrast (MULTI: WE = 0.62; HYBRID: WE = 0.21), but the best method depended on the anatomical region of interest. While methods using only one modality resulted in lower WEs, lowest overall WEs were obtained when only T1w images were used (DIRECT: WE = 0.12; U‐CONV: WE = 0.05). Conclusion Template generation strategies that employ only magnetic susceptibility contrast or both magnetic susceptibility and T1w contrast produce templates with the highest quality. The optimal approach depends on the anatomical structures of interest. The established approach of using only T1w images (CONV) results in reduced image quality compared to all other approaches studied. Level of Evidence: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1474–1484.
AbstractList To develop and assess a method for the creation of templates for voxel-based analysis (VBA) and atlas-based approaches using quantitative magnetic susceptibility mapping (QSM).PURPOSETo develop and assess a method for the creation of templates for voxel-based analysis (VBA) and atlas-based approaches using quantitative magnetic susceptibility mapping (QSM).We studied four strategies for the creation of magnetic susceptibility brain templates, derived as successive extensions of the conventional template generation (CONV) based on only T1 -weighted (T1 w) images. One method that used only T1 w images involved a minor improvement of CONV (U-CONV). One method used only magnetic susceptibility maps as input for template generation (DIRECT), and the other two used a linear combination of susceptibility and T1 w images (HYBRID) and an algorithm that directly used both image modalities (MULTI), respectively. The strategies were evaluated in a group of N = 10 healthy human subjects and semiquantitatively assessed by three experienced raters. Template quality was compared statistically via worth estimates (WEs) obtained with a log-linear Bradley-Terry model.MATERIALS AND METHODSWe studied four strategies for the creation of magnetic susceptibility brain templates, derived as successive extensions of the conventional template generation (CONV) based on only T1 -weighted (T1 w) images. One method that used only T1 w images involved a minor improvement of CONV (U-CONV). One method used only magnetic susceptibility maps as input for template generation (DIRECT), and the other two used a linear combination of susceptibility and T1 w images (HYBRID) and an algorithm that directly used both image modalities (MULTI), respectively. The strategies were evaluated in a group of N = 10 healthy human subjects and semiquantitatively assessed by three experienced raters. Template quality was compared statistically via worth estimates (WEs) obtained with a log-linear Bradley-Terry model.The overall quality of the templates was better for strategies including both susceptibility and T1 w contrast (MULTI: WE = 0.62; HYBRID: WE = 0.21), but the best method depended on the anatomical region of interest. While methods using only one modality resulted in lower WEs, lowest overall WEs were obtained when only T1 w images were used (DIRECT: WE = 0.12; U-CONV: WE = 0.05).RESULTSThe overall quality of the templates was better for strategies including both susceptibility and T1 w contrast (MULTI: WE = 0.62; HYBRID: WE = 0.21), but the best method depended on the anatomical region of interest. While methods using only one modality resulted in lower WEs, lowest overall WEs were obtained when only T1 w images were used (DIRECT: WE = 0.12; U-CONV: WE = 0.05).Template generation strategies that employ only magnetic susceptibility contrast or both magnetic susceptibility and T1 w contrast produce templates with the highest quality. The optimal approach depends on the anatomical structures of interest. The established approach of using only T1 w images (CONV) results in reduced image quality compared to all other approaches studied.CONCLUSIONTemplate generation strategies that employ only magnetic susceptibility contrast or both magnetic susceptibility and T1 w contrast produce templates with the highest quality. The optimal approach depends on the anatomical structures of interest. The established approach of using only T1 w images (CONV) results in reduced image quality compared to all other approaches studied.2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1474-1484.LEVEL OF EVIDENCE2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1474-1484.
To develop and assess a method for the creation of templates for voxel-based analysis (VBA) and atlas-based approaches using quantitative magnetic susceptibility mapping (QSM). We studied four strategies for the creation of magnetic susceptibility brain templates, derived as successive extensions of the conventional template generation (CONV) based on only T -weighted (T w) images. One method that used only T w images involved a minor improvement of CONV (U-CONV). One method used only magnetic susceptibility maps as input for template generation (DIRECT), and the other two used a linear combination of susceptibility and T w images (HYBRID) and an algorithm that directly used both image modalities (MULTI), respectively. The strategies were evaluated in a group of N = 10 healthy human subjects and semiquantitatively assessed by three experienced raters. Template quality was compared statistically via worth estimates (WEs) obtained with a log-linear Bradley-Terry model. The overall quality of the templates was better for strategies including both susceptibility and T w contrast (MULTI: WE = 0.62; HYBRID: WE = 0.21), but the best method depended on the anatomical region of interest. While methods using only one modality resulted in lower WEs, lowest overall WEs were obtained when only T w images were used (DIRECT: WE = 0.12; U-CONV: WE = 0.05). Template generation strategies that employ only magnetic susceptibility contrast or both magnetic susceptibility and T w contrast produce templates with the highest quality. The optimal approach depends on the anatomical structures of interest. The established approach of using only T w images (CONV) results in reduced image quality compared to all other approaches studied. 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1474-1484.
Purpose To develop and assess a method for the creation of templates for voxel‐based analysis (VBA) and atlas‐based approaches using quantitative magnetic susceptibility mapping (QSM). Materials and Methods We studied four strategies for the creation of magnetic susceptibility brain templates, derived as successive extensions of the conventional template generation (CONV) based on only T1‐weighted (T1w) images. One method that used only T1w images involved a minor improvement of CONV (U‐CONV). One method used only magnetic susceptibility maps as input for template generation (DIRECT), and the other two used a linear combination of susceptibility and T1w images (HYBRID) and an algorithm that directly used both image modalities (MULTI), respectively. The strategies were evaluated in a group of N = 10 healthy human subjects and semiquantitatively assessed by three experienced raters. Template quality was compared statistically via worth estimates (WEs) obtained with a log‐linear Bradley‐Terry model. Results The overall quality of the templates was better for strategies including both susceptibility and T1w contrast (MULTI: WE = 0.62; HYBRID: WE = 0.21), but the best method depended on the anatomical region of interest. While methods using only one modality resulted in lower WEs, lowest overall WEs were obtained when only T1w images were used (DIRECT: WE = 0.12; U‐CONV: WE = 0.05). Conclusion Template generation strategies that employ only magnetic susceptibility contrast or both magnetic susceptibility and T1w contrast produce templates with the highest quality. The optimal approach depends on the anatomical structures of interest. The established approach of using only T1w images (CONV) results in reduced image quality compared to all other approaches studied. Level of Evidence: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1474–1484.
Purpose To develop and assess a method for the creation of templates for voxel-based analysis (VBA) and atlas-based approaches using quantitative magnetic susceptibility mapping (QSM). Materials and Methods We studied four strategies for the creation of magnetic susceptibility brain templates, derived as successive extensions of the conventional template generation (CONV) based on only T1-weighted (T1w) images. One method that used only T1w images involved a minor improvement of CONV (U-CONV). One method used only magnetic susceptibility maps as input for template generation (DIRECT), and the other two used a linear combination of susceptibility and T1w images (HYBRID) and an algorithm that directly used both image modalities (MULTI), respectively. The strategies were evaluated in a group of N=10 healthy human subjects and semiquantitatively assessed by three experienced raters. Template quality was compared statistically via worth estimates (WEs) obtained with a log-linear Bradley-Terry model. Results The overall quality of the templates was better for strategies including both susceptibility and T1w contrast (MULTI: WE=0.62; HYBRID: WE=0.21), but the best method depended on the anatomical region of interest. While methods using only one modality resulted in lower WEs, lowest overall WEs were obtained when only T1w images were used (DIRECT: WE=0.12; U-CONV: WE=0.05). Conclusion Template generation strategies that employ only magnetic susceptibility contrast or both magnetic susceptibility and T1w contrast produce templates with the highest quality. The optimal approach depends on the anatomical structures of interest. The established approach of using only T1w images (CONV) results in reduced image quality compared to all other approaches studied. Level of Evidence: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1474-1484.
Author Reichenbach, Jürgen R.
Dwyer, Michael G.
Zivadinov, Robert
Feng, Xiang
Bertolino, Nicola
Polak, Paul
Hanspach, Jannis
Hagemeier, Jesper
Schweser, Ferdinand
Bergsland, Niels P.
AuthorAffiliation 2 Magnetic Resonance Laboratory, IRCCS Don Gnocchi Foundation, Milan, Italy
3 Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital, Friedrich Schiller University Jena, Jena, TH, Germany
1 Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA
4 Michael Stifel Center for Data-driven and Simulation Science Jena, Friedrich Schiller University Jena, Jena, TH, Germany
5 MRI Clinical and Translational Research Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, USA
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Cites_doi 10.1016/j.neuroimage.2015.10.013
10.1016/j.neuroimage.2007.10.037
10.3390/ijms17010100
10.1002/jmri.24951
10.1109/TMI.2010.2046908
10.1097/RLI.0000000000000159
10.1016/j.neuroimage.2016.02.028
10.18383/j.tom.2015.00136
10.1364/AO.46.006623
10.1093/biomet/63.2.245
10.1016/j.neuroimage.2010.05.029
10.1002/hbm.10062
10.1016/j.neuroimage.2014.10.009
10.1111/j.1471-4159.1958.tb12607.x
10.1016/j.neuroimage.2013.05.127
10.1523/JNEUROSCI.1907-15.2016
10.1002/mrm.23000
10.1016/j.neuroimage.2010.10.070
10.1109/42.836373
10.1097/01.rmr.0000245461.90406.ad
10.1007/s00330-014-3472-7
10.1148/radiol.14132475
10.1002/hbm.22423
10.1016/j.mri.2014.09.004
10.1016/j.neuroimage.2012.05.067
10.18637/jss.v048.i10
10.1016/j.acra.2008.07.007
10.1177/1352458514531085
10.1016/j.neuroimage.2016.04.065
10.1016/j.neuroimage.2012.09.055
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Keywords magnetic resonance imaging (MRI)
template
voxel-based analysis (VBA)
quantitative susceptibility mapping (QSM)
T1-weighted imaging
normalization
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References 2015; 1
2002; 17
1976; 63
2013; 65
2015; 105
2015; 50
2006; 17
2015; 33
2008; 39
2008; 15
2011; 54
2014; 272
2016; 125
2016; 17
2007; 10
2016; 36
2014; 20
2015; 25
2000; 19
2010; 29
2015; 42
2013; 82
2016; 132
2014; 35
2016
2015
2014
1981
2012; 48
2013
2016; 136
1958; 3
2009; 2
2012; 67
2010; 52
2007; 46
2012; 62
e_1_2_6_32_1
e_1_2_6_10_1
e_1_2_6_31_1
e_1_2_6_30_1
Fleiss JL (e_1_2_6_28_1) 1981
Avants BB (e_1_2_6_24_1) 2007; 10
e_1_2_6_19_1
e_1_2_6_13_1
e_1_2_6_36_1
e_1_2_6_35_1
e_1_2_6_11_1
e_1_2_6_12_1
e_1_2_6_33_1
e_1_2_6_17_1
e_1_2_6_18_1
e_1_2_6_15_1
R Core Team (e_1_2_6_26_1) 2013
Lauzon ML (e_1_2_6_34_1) 2016
e_1_2_6_38_1
e_1_2_6_16_1
e_1_2_6_37_1
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20378467 - IEEE Trans Med Imaging. 2010 Jun;29(6):1310-20
26899787 - Neuroimage. 2016 May 15;132:167-174
21040794 - Neuroimage. 2011 Feb 14;54(4):2789-807
23769915 - Neuroimage. 2013 Nov 15;82:449-69
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26477650 - Neuroimage. 2016 Jan 15;125:479-497
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13611557 - J Neurochem. 1958 Oct;3(1):41-51
24828000 - Radiology. 2014 Sep;272(3):851-64
25900085 - Invest Radiol. 2015 Aug;50(8):522-30
23036448 - Neuroimage. 2013 Jan 15;65:299-314
26758829 - J Neurosci. 2016 Jan 13;36(2):364-74
25315786 - Neuroimage. 2015 Jan 15;105:45-52
26887659 - NMR Biomed. 2017 Apr;30(4):null
17846656 - Appl Opt. 2007 Sep 10;46(26):6623-35
References_xml – volume: 105
  start-page: 45
  year: 2015
  end-page: 52
  article-title: Association between increased magnetic susceptibility of deep gray matter nuclei and decreased motor function in healthy adults
  publication-title: NeuroImage
– year: 1981
– volume: 25
  start-page: 710
  year: 2015
  end-page: 718
  article-title: Internal structures of the globus pallidus in patients with Parkinson's disease: evaluation with quantitative susceptibility mapping (QSM)
  publication-title: Eur Radiol
– volume: 67
  start-page: 137
  year: 2012
  end-page: 147
  article-title: Whole brain susceptibility mapping using compressed sensing
  publication-title: Magn Reson Med
– volume: 82
  start-page: 449
  year: 2013
  end-page: 469
  article-title: Human brain atlas for automated region of interest selection in quantitative susceptibility mapping: Application to determine iron content in deep gray matter structures
  publication-title: NeuroImage
– volume: 15
  start-page: 1360
  year: 2008
  end-page: 1375
  article-title: Multivariate analysis of structural and diffusion imaging in traumatic brain injury
  publication-title: Acad Radiol
– volume: 36
  start-page: 364
  year: 2016
  end-page: 374
  article-title: In vivo MRI mapping of brain iron deposition across the adult lifespan
  publication-title: J Neurosci
– volume: 1
  start-page: 3
  year: 2015
  end-page: 17
  article-title: Quantitative susceptibility mapping: contrast mechanisms and clinical applications
  publication-title: Tomogr J Imaging Res
– volume: 63
  start-page: 245
  year: 1976
  end-page: 254
  article-title: Log linear representation for paired and multiple comparisons models
  publication-title: Biometrika
– volume: 65
  start-page: 299
  year: 2013
  end-page: 314
  article-title: Toward in vivo histology: A comparison of quantitative susceptibility mapping (QSM) with magnitude‐, phase‐, and R2*‐imaging at ultra‐high magnetic field strength
  publication-title: NeuroImage
– start-page: 23
  year: 2015
– volume: 19
  start-page: 143
  year: 2000
  end-page: 150
  article-title: New variants of a method of MRI scale standardization
  publication-title: IEEE Trans Med Imaging
– volume: 33
  start-page: 1
  year: 2015
  end-page: 25
  article-title: Quantitative susceptibility mapping: current status and future directions
  publication-title: Magn Reson Imaging
– volume: 10
  start-page: 359
  issue: Pt 1
  year: 2007
  end-page: 366
  article-title: Multivariate normalization with symmetric diffeomorphisms for multivariate studies
  publication-title: Med Image Comput Comput‐Assist Interv MICCAI Int Conf Med Image Comput Comput‐Assist Interv
– volume: 17
  start-page: 5
  year: 2006
  end-page: 17
  article-title: Role of iron in neurodegenerative disorders
  publication-title: Top Magn Reson Imaging TMRI
– volume: 132
  start-page: 167
  year: 2016
  end-page: 174
  article-title: Magnetic susceptibility of brain iron is associated with childhood spatial IQ
  publication-title: NeuroImage
– volume: 62
  start-page: 2083
  year: 2012
  end-page: 2100
  article-title: Quantitative susceptibility mapping for investigating subtle susceptibility variations in the human brain
  publication-title: NeuroImage
– volume: 17
  start-page: 143
  year: 2002
  end-page: 155
  article-title: Fast robust automated brain extraction
  publication-title: Hum Brain Mapp
– volume: 50
  start-page: 522
  year: 2015
  end-page: 530
  article-title: Quantitative susceptibility mapping at 3 T and 1.5 T: evaluation of consistency and reproducibility
  publication-title: Invest Radiol
– volume: 46
  start-page: 6623
  year: 2007
  end-page: 6635
  article-title: Fast and robust three‐dimensional best path phase unwrapping algorithm
  publication-title: Appl Opt
– volume: 29
  start-page: 1310
  year: 2010
  end-page: 1320
  article-title: N4ITK: Improved N3 bias correction
  publication-title: IEEE Trans Med Imaging
– year: 2016
  article-title: Quantitative susceptibility mapping at 3 T: comparison of acquisition methodologies
  publication-title: NMR Biomed
– volume: 136
  start-page: 208
  year: 2016
  end-page: 214
  article-title: Quantitative susceptibility mapping of striatum in children and adults, and its association with working memory performance
  publication-title: NeuroImage
– volume: 17
  start-page: 100
  year: 2016
  article-title: Iron in multiple sclerosis and its noninvasive imaging with quantitative susceptibility mapping
  publication-title: Int J Mol Sci
– volume: 52
  start-page: 1261
  year: 2010
  end-page: 1267
  article-title: Evaluation of automated techniques for the quantification of grey matter atrophy in patients with multiple sclerosis
  publication-title: NeuroImage
– volume: 3
  start-page: 41
  year: 1958
  end-page: 51
  article-title: The effect of age on the non‐haemin iron in the human brain
  publication-title: J Neurochem
– volume: 2
  start-page: 1
  year: 2009
  end-page: 35
  article-title: Advanced normalization tools (ANTS)
  publication-title: Insight J
– volume: 39
  start-page: 1682
  year: 2008
  end-page: 1692
  article-title: Development of a robust method for generating 7.0 T multichannel phase images of the brain with application to normal volunteers and patients with neurological diseases
  publication-title: NeuroImage
– volume: 54
  start-page: 2789
  year: 2011
  end-page: 2807
  article-title: Quantitative imaging of intrinsic magnetic tissue properties using MRI signal phase: An approach to in vivo brain iron metabolism?
  publication-title: NeuroImage
– volume: 125
  start-page: 479
  year: 2016
  end-page: 497
  article-title: Automatic segmentation of the striatum and globus pallidus using MIST: Multimodal Image Segmentation Tool
  publication-title: NeuroImage
– volume: 272
  start-page: 851
  year: 2014
  end-page: 864
  article-title: Multiple sclerosis: improved identification of disease‐relevant changes in gray and white matter by using susceptibility‐based MR imaging
  publication-title: Radiology
– volume: 35
  start-page: 3588
  year: 2014
  end-page: 3601
  article-title: In vivo normative atlas of the hippocampal subfields using multi‐echo susceptibility imaging at 7 Tesla: susceptibility atlas of the hippocampus at 7 T
  publication-title: Hum Brain Mapp
– volume: 20
  start-page: 1692
  year: 2014
  end-page: 1698
  article-title: Determinants of iron accumulation in deep grey matter of multiple sclerosis patients
  publication-title: Mult Scler J
– start-page: 1787
  year: 2014
– volume: 48
  start-page: 1
  year: 2012
  end-page: 31
  article-title: Prefmod: An R package for modeling preferences based on paired comparisons, rankings, or ratings
  publication-title: J Stat Softw
– volume: 42
  start-page: 1601
  year: 2015
  end-page: 1610
  article-title: Subcortical gray matter segmentation and voxel‐based analysis using transverse relaxation and quantitative susceptibility mapping with application to multiple sclerosis: Voxel‐based QSM and in MS
  publication-title: J Magn Reson Imaging
– year: 2013
– ident: e_1_2_6_23_1
  doi: 10.1016/j.neuroimage.2015.10.013
– volume: 2
  start-page: 1
  year: 2009
  ident: e_1_2_6_14_1
  article-title: Advanced normalization tools (ANTS)
  publication-title: Insight J
– ident: e_1_2_6_15_1
  doi: 10.1016/j.neuroimage.2007.10.037
– ident: e_1_2_6_5_1
  doi: 10.3390/ijms17010100
– volume: 10
  start-page: 359
  issue: 1
  year: 2007
  ident: e_1_2_6_24_1
  article-title: Multivariate normalization with symmetric diffeomorphisms for multivariate studies
  publication-title: Med Image Comput Comput‐Assist Interv MICCAI Int Conf Med Image Comput Comput‐Assist Interv
– volume-title: Statistical methods for rates and proportions
  year: 1981
  ident: e_1_2_6_28_1
– ident: e_1_2_6_37_1
  doi: 10.1002/jmri.24951
– ident: e_1_2_6_20_1
  doi: 10.1109/TMI.2010.2046908
– ident: e_1_2_6_11_1
– year: 2016
  ident: e_1_2_6_34_1
  article-title: Quantitative susceptibility mapping at 3 T: comparison of acquisition methodologies
  publication-title: NMR Biomed
– ident: e_1_2_6_32_1
  doi: 10.1097/RLI.0000000000000159
– ident: e_1_2_6_35_1
  doi: 10.1016/j.neuroimage.2016.02.028
– ident: e_1_2_6_3_1
  doi: 10.18383/j.tom.2015.00136
– ident: e_1_2_6_17_1
  doi: 10.1364/AO.46.006623
– ident: e_1_2_6_27_1
  doi: 10.1093/biomet/63.2.245
– ident: e_1_2_6_8_1
  doi: 10.1016/j.neuroimage.2010.05.029
– ident: e_1_2_6_22_1
  doi: 10.1002/hbm.10062
– ident: e_1_2_6_33_1
  doi: 10.1016/j.neuroimage.2014.10.009
– ident: e_1_2_6_13_1
  doi: 10.1111/j.1471-4159.1958.tb12607.x
– ident: e_1_2_6_38_1
  doi: 10.1016/j.neuroimage.2013.05.127
– ident: e_1_2_6_30_1
  doi: 10.1523/JNEUROSCI.1907-15.2016
– ident: e_1_2_6_18_1
  doi: 10.1002/mrm.23000
– ident: e_1_2_6_4_1
  doi: 10.1016/j.neuroimage.2010.10.070
– ident: e_1_2_6_21_1
  doi: 10.1109/42.836373
– ident: e_1_2_6_6_1
  doi: 10.1097/01.rmr.0000245461.90406.ad
– ident: e_1_2_6_16_1
– ident: e_1_2_6_10_1
  doi: 10.1007/s00330-014-3472-7
– volume-title: R: A language and environment for statistical computing
  year: 2013
  ident: e_1_2_6_26_1
– ident: e_1_2_6_29_1
  doi: 10.1148/radiol.14132475
– ident: e_1_2_6_36_1
  doi: 10.1002/hbm.22423
– ident: e_1_2_6_2_1
  doi: 10.1016/j.mri.2014.09.004
– ident: e_1_2_6_19_1
  doi: 10.1016/j.neuroimage.2012.05.067
– ident: e_1_2_6_25_1
  doi: 10.18637/jss.v048.i10
– ident: e_1_2_6_12_1
  doi: 10.1016/j.acra.2008.07.007
– ident: e_1_2_6_7_1
  doi: 10.1177/1352458514531085
– ident: e_1_2_6_31_1
  doi: 10.1016/j.neuroimage.2016.04.065
– ident: e_1_2_6_9_1
  doi: 10.1016/j.neuroimage.2012.09.055
– reference: 26477650 - Neuroimage. 2016 Jan 15;125:479-497
– reference: 23036448 - Neuroimage. 2013 Jan 15;65:299-314
– reference: 21040794 - Neuroimage. 2011 Feb 14;54(4):2789-807
– reference: 22659482 - Neuroimage. 2012 Sep;62(3):2083-100
– reference: 25900085 - Invest Radiol. 2015 Aug;50(8):522-30
– reference: 23769915 - Neuroimage. 2013 Nov 15;82:449-69
– reference: 18051079 - Med Image Comput Comput Assist Interv. 2007;10(Pt 1):359-66
– reference: 25980643 - J Magn Reson Imaging. 2015 Dec;42(6):1601-10
– reference: 18096412 - Neuroimage. 2008 Feb 15;39(4):1682-92
– reference: 17179893 - Top Magn Reson Imaging. 2006 Feb;17(1):5-17
– reference: 25315786 - Neuroimage. 2015 Jan 15;105:45-52
– reference: 21671269 - Magn Reson Med. 2012 Jan;67(1):137-47
– reference: 20378467 - IEEE Trans Med Imaging. 2010 Jun;29(6):1310-20
– reference: 24339427 - Hum Brain Mapp. 2014 Aug;35(8):3588-601
– reference: 20483380 - Neuroimage. 2010 Oct 1;52(4):1261-7
– reference: 26758829 - J Neurosci. 2016 Jan 13;36(2):364-74
– reference: 27132546 - Neuroimage. 2016 Aug 1;136:208-14
– reference: 26887659 - NMR Biomed. 2017 Apr;30(4):null
– reference: 24787429 - Mult Scler. 2014 Nov;20(13):1692-8
– reference: 10784285 - IEEE Trans Med Imaging. 2000 Feb;19(2):143-50
– reference: 24828000 - Radiology. 2014 Sep;272(3):851-64
– reference: 12391568 - Hum Brain Mapp. 2002 Nov;17(3):143-55
– reference: 18995188 - Acad Radiol. 2008 Nov;15(11):1360-75
– reference: 26844301 - Tomography. 2015 Sep;1(1):3-17
– reference: 25267705 - Magn Reson Imaging. 2015 Jan;33(1):1-25
– reference: 26784172 - Int J Mol Sci. 2016 Jan 14;17 (1):null
– reference: 17846656 - Appl Opt. 2007 Sep 10;46(26):6623-35
– reference: 26899787 - Neuroimage. 2016 May 15;132:167-174
– reference: 13611557 - J Neurochem. 1958 Oct;3(1):41-51
– reference: 25361824 - Eur Radiol. 2015 Mar;25(3):710-8
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Snippet Purpose To develop and assess a method for the creation of templates for voxel‐based analysis (VBA) and atlas‐based approaches using quantitative magnetic...
To develop and assess a method for the creation of templates for voxel-based analysis (VBA) and atlas-based approaches using quantitative magnetic...
Purpose To develop and assess a method for the creation of templates for voxel-based analysis (VBA) and atlas-based approaches using quantitative magnetic...
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proquest
pubmed
crossref
wiley
SourceType Open Access Repository
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Index Database
Enrichment Source
Publisher
StartPage 1474
SubjectTerms Adult
Aged
Algorithms
Brain
Brain - diagnostic imaging
Brain Mapping - methods
Computer Simulation
Female
Healthy Volunteers
Humans
Image Interpretation, Computer-Assisted - methods
Image processing
Image Processing, Computer-Assisted - methods
Image quality
Magnetic permeability
Magnetic resonance imaging
magnetic resonance imaging (MRI)
Magnetic Resonance Imaging - methods
Magnetic susceptibility
Magnetism
Male
Methods
Middle Aged
Neuroimaging
normalization
quantitative susceptibility mapping (QSM)
T1‐weighted imaging
template
voxel‐based analysis (VBA)
Young Adult
Title Methods for the computation of templates from quantitative magnetic susceptibility maps (QSM): Toward improved atlas‐ and voxel‐based analyses (VBA)
URI https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fjmri.25671
https://www.ncbi.nlm.nih.gov/pubmed/28263417
https://www.proquest.com/docview/1950301871
https://www.proquest.com/docview/1874787336
https://pubmed.ncbi.nlm.nih.gov/PMC5587351
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