A hitchhiker's guide to diffusion tensor imaging

José M Soares, Paulo Marques, Victor Alves, Nuno Sousa, José M Soares, Paulo Marques, Victor Alves, Nuno Sousa

Abstract

Diffusion Tensor Imaging (DTI) studies are increasingly popular among clinicians and researchers as they provide unique insights into brain network connectivity. However, in order to optimize the use of DTI, several technical and methodological aspects must be factored in. These include decisions on: acquisition protocol, artifact handling, data quality control, reconstruction algorithm, and visualization approaches, and quantitative analysis methodology. Furthermore, the researcher and/or clinician also needs to take into account and decide on the most suited software tool(s) for each stage of the DTI analysis pipeline. Herein, we provide a straightforward hitchhiker's guide, covering all of the workflow's major stages. Ultimately, this guide will help newcomers navigate the most critical roadblocks in the analysis and further encourage the use of DTI.

Keywords: acquisition; analysis; diffusion tensor imaging; hitchhiker's guide; processing.

Figures

Figure 1
Figure 1
Typical DTI workflow. In order to perform a DTI study, researchers need to understand its main application fields, recognize the main artifacts (A) and what acquisition protocols can be used (B). The data should undergo quality control, preprocessing, including format conversion (C), distortions and motion correction (D), and skull stripping (E). Before further analysis, tensors need to be estimated (F) and the resulting data can be visualized as glyphs (G), scalar indices such as colored FA (H), FA (I), and MD (J) or as tractography (K). ROI (L), histogram (M), VBA (N), or TBSS (O) analyses may be performed and the results can be incorporated with fMRI (P) or structural MRI (Q) in multimodal analysis. Finally, results interpretation should be made with extreme caution.

References

    1. Abe O., Takao H., Gonoi W., Sasaki H., Murakami M., Kabasawa H., et al. (2010). Voxel-based analysis of the diffusion tensor. Neuroradiology 52, 699–710 10.1007/s00234-010-0716-3
    1. Akers D., Sherbondy A., MacKenzie R., Dougherty R., Wandell B. (2004). Exploration of the brain's white matter pathways with dynamic queries, in Proceedings of the Conference on Visualization ‘04 (Austin, TX: IEEE Computer Society; ).
    1. Alexander A. L., Hasan K. M., Lazar M., Tsuruda J. S., Parker D. L. (2001). Analysis of partial volume effects in diffusion-tensor MRI. Magn. Reson. Med. 45, 770–780 10.1002/mrm.1105
    1. Alexander A. L., Wu Y. C., Venkat P. C. (2006). Hybrid diffusion imaging (HYDI). Conf. Proc. IEEE Eng. Med. Biol. Soc. 1, 2245–2248 10.1109/IEMBS.2006.259453
    1. Assaf Y., Pasternak O. (2008). Diffusion tensor imaging (DTI)-based white matter mapping in brain research: a review. J. Mol. Neurosci. 34, 51–61 10.1007/s12031-007-0029-0
    1. Assemlal H. E., Tschumperle D., Brun L., Siddiqi K. (2011). Recent advances in diffusion MRI modeling: angular and radial reconstruction. Med. Image Anal. 15, 369–396 10.1016/j.media.2011.02.002
    1. Astrakas L. G., Argyropoulou M. I. (2010). Shifting from region of interest (ROI) to voxel-based analysis in human brain mapping. Pediatr. Radiol. 40, 1857–1867 10.1007/s00247-010-1677-8
    1. Bammer R., Auer M., Keeling S. L., Augustin M., Stables L. A., Prokesch R. W., et al. (2002). Diffusion tensor imaging using single-shot SENSE-EPI. Magn. Reson. Med. 48, 128–136 10.1002/mrm.10184
    1. Bammer R., Holdsworth S. J., Veldhuis W. B., Skare S. T. (2009). New methods in diffusion-weighted and diffusion tensor imaging. Magn. Reson. Imaging Clin. N. Am. 17, 175–204 10.1016/j.mric.2009.01.011
    1. Bangera N. B., Schomer D. L., Dehghani N., Ulbert I., Cash S., Papavasiliou S., et al. (2010). Experimental validation of the influence of white matter anisotropy on the intracranial EEG forward solution. J. Comput. Neurosci. 29, 371–387 10.1007/s10827-009-0205-z
    1. Barrick T. R., Clark C. A. (2004). Singularities in diffusion tensor fields and their relevance in white matter fiber tractography. Neuroimage 22, 481–491 10.1016/j.neuroimage.2004.02.001
    1. Basser P. J., Jones D. K. (2002). Diffusion-tensor MRI: theory, experimental design and data analysis– a technical review. NMR Biomed. 15, 456–467 10.1002/nbm.783
    1. Basser P. J., Mattiello J., Lebihan D. (1994a). Estimation of the effective self-diffusion tensor from the NMR spin echo. J. Magn. Reson. B 103, 247–254
    1. Basser P. J., Mattiello J., Lebihan D. (1994b). MR diffusion tensor spectroscopy and imaging. Biophys. J. 66, 259–267 10.1016/S0006-3495(94)80775-1
    1. Basser P. J., Pajevic S., Pierpaoli C., Duda J., Aldroubi A. (2000). In vivo fiber tractography using DT-MRI data. Magn. Reson. Med. 44, 625–632 10.1002/1522-2594(200010)44:4<625::AID-MRM17>;2-O
    1. Basser P. J., Pierpaoli C. (1996). Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. J. Magn. Reson. B 111, 209–219
    1. Basu S., Fletcher T., Whitaker R. (2006). Rician noise removal in diffusion tensor MRI. Med. Image Comput. Comput. Assist. Interv. 9, 117–125
    1. Bazin P. L., Ye C., Bogovic J. A., Shiee N., Reich D. S., Prince J. L., et al. (2011). Direct segmentation of the major white matter tracts in diffusion tensor images. Neuroimage 58, 458–468 10.1016/j.neuroimage.2011.06.020
    1. Beaulieu C. (2002). The basis of anisotropic water diffusion in the nervous system– a technical review. NMR Biomed. 15, 435–455 10.1002/nbm.782
    1. Behrens T. E., Berg H. J., Jbabdi S., Rushworth M. F., Woolrich M. W. (2007). Probabilistic diffusion tractography with multiple fibre orientations: what can we gain? Neuroimage 34, 144–155 10.1016/j.neuroimage.2006.09.018
    1. Brau A. C., Beatty P. J., Skare S., Bammer R. (2008). Comparison of reconstruction accuracy and efficiency among autocalibrating data-driven parallel imaging methods. Magn. Reson. Med. 59, 382–395 10.1002/mrm.21481
    1. Budde M. D., Xie M., Cross A. H., Song S. K. (2009). Axial diffusivity is the primary correlate of axonal injury in the experimental autoimmune encephalomyelitis spinal cord: a quantitative pixelwise analysis. J. Neurosci. 29, 2805–2813 10.1523/JNEUROSCI.4605-08.2009
    1. Burgel U., Madler B., Honey C. R., Thron A., Gilsbach J., Coenen V. A. (2009). Fiber tracking with distinct software tools results in a clear diversity in anatomical fiber tract portrayal. Cent. Eur. Neurosurg. 70, 27–35 10.1055/s-0028-1087212
    1. Cardenes R., Munoz-Moreno E., Tristan-Vega A., Martin-Fernandez M. (2010). Saturn: a software application of tensor utilities for research in neuroimaging. Comput. Methods Programs Biomed. 97, 264–279 10.1016/j.cmpb.2009.09.007
    1. Carvalho Rangel C., Hygino Cruz L. C., Jr., Takayassu T. C., Gasparetto E. L., Domingues R. C. (2011). Diffusion MR imaging in central nervous system. Magn. Reson. Imaging Clin. N. Am. 19, 23–53 10.1016/j.mric.2010.10.006
    1. Catani M., Thiebaut De Schotten M. (2008). A diffusion tensor imaging tractography atlas for virtual in vivo dissections. Cortex 44, 1105–1132 10.1016/j.cortex.2008.05.004
    1. Chang L. C., Jones D. K., Pierpaoli C. (2005). RESTORE: robust estimation of tensors by outlier rejection. Magn. Reson. Med. 53, 1088–1095 10.1002/mrm.20426
    1. Chanraud S., Zahr N., Sullivan E. V., Pfefferbaum A. (2010). MR diffusion tensor imaging: a window into white matter integrity of the working brain. Neuropsychol. Rev. 20, 209–225 10.1007/s11065-010-9129-7
    1. Chavez S., Storey P., Graham S. J. (2009). Robust correction of spike noise: application to diffusion tensor imaging. Magn. Reson. Med. 62, 510–519 10.1002/mrm.22019
    1. Chen B., Guo H., Song A. W. (2006). Correction for direction-dependent distortions in diffusion tensor imaging using matched magnetic field maps. Neuroimage 30, 121–129 10.1016/j.neuroimage.2005.09.008
    1. Chenevert T. L., Brunberg J. A., Pipe J. G. (1990). Anisotropic diffusion in human white matter: demonstration with MR techniques in vivo. Radiology 177, 401–405
    1. Choi S., Cunningham D. T., Aguila F., Corrigan J. D., Bogner J., Mysiw W. J., et al. (2011). DTI at 7 and 3 T: systematic comparison of SNR and its influence on quantitative metrics. Magn. Reson. Imaging 29, 739–751 10.1016/j.mri.2011.02.009
    1. Chung H. W., Chou M. C., Chen C. Y. (2011). Principles and limitations of computational algorithms in clinical diffusion tensor MR tractography. AJNR. Am. J. Neuroradiol. 32, 3–13 10.3174/ajnr.A2041
    1. Ciccarelli O., Catani M., Johansen-Berg H., Clark C., Thompson A. (2008). Diffusion-based tractography in neurological disorders: concepts, applications, and future developments. Lancet Neurol. 7, 715–727 10.1016/S1474-4422(08)70163-7
    1. Conner C. R., Ellmore T. M., Disano M. A., Pieters T. A., Potter A. W., Tandon N. (2011). Anatomic and electro-physiologic connectivity of the language system: a combined DTI-CCEP study. Comput. Biol. Med. 41, 1100–1109 10.1016/j.compbiomed.2011.07.008
    1. Cook P. A., Bai Y., Gilani N., Seunarine K. K., Hall M. G., Parker G. J., et al. (2006). Camino: open-source diffusion-MRI reconstruction and processing, in 14th Scientific Meeting of the International Society for Magnetic Resonance in Medicine (Seattle, WA: ), 2759.
    1. Cox R. W. (2012). AFNI: what a long strange trip it's been. Neuroimage 62, 743–747 10.1016/j.neuroimage.2011.08.056
    1. Della Nave R., Foresti S., Pratesi A., Ginestroni A., Inzitari M., Salvadori E., et al. (2007). Whole-brain histogram and voxel-based analyses of diffusion tensor imaging in patients with leukoaraiosis: correlation with motor and cognitive impairment. AJNR. Am. J. Neuroradiol. 28, 1313–1319 10.3174/ajnr.A0555
    1. Descoteaux M., Deriche R., Knosche T. R., Anwander A. (2009). Deterministic and probabilistic tractography based on complex fibre orientation distributions. IEEE Trans. Med. Imaging 28, 269–286 10.1109/TMI.2008.2004424
    1. Douek P., Turner R., Pekar J., Patronas N., Le Bihan D. (1991). MR color mapping of myelin fiber orientation. J. Comput. Assist. Tomogr. 15, 923–929
    1. Ethofer T., Gschwind M., Vuilleumier P. (2011). Processing social aspects of human gaze: a combined fMRI-DTI study. Neuroimage 55, 411–419 10.1016/j.neuroimage.2010.11.033
    1. Evans A. C., Janke A. L., Collins D. L., Baillet S. (2012). Brain templates and atlases. Neuroimage 62, 911–922 10.1016/j.neuroimage.2012.01.024
    1. Farrell J. A., Landman B. A., Jones C. K., Smith S. A., Prince J. L., van Zijl P. C., et al. (2007). 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. J. Magn. Reson. Imaging 26, 756–767 10.1002/jmri.21053
    1. Farzaneh F., Riederer S. J., Pelc N. J. (1990). Analysis of T2 limitations and off-resonance effects on spatial resolution and artifacts in echo-planar imaging. Magn. Reson. Med. 14, 123–139
    1. Fernandez A., Rios-Lago M., Abasolo D., Hornero R., Alvarez-Linera J., Paul N., et al. (2011). The correlation between white-matter microstructure and the complexity of spontaneous brain activity: a difussion tensor imaging-MEG study. Neuroimage 57, 1300–1307 10.1016/j.neuroimage.2011.05.079
    1. Figueiredo E. H., Borgonovi A. F., Doring T. M. (2011). Basic concepts of MR imaging, diffusion MR imaging, and diffusion tensor imaging. Magn. Reson. Imaging Clin. N. Am. 19, 1–22 10.1016/j.mric.2010.10.005
    1. Fillard P., Descoteaux M., Goh A., Gouttard S., Jeurissen B., Malcolm J., et al. (2011). Quantitative evaluation of 10 tractography algorithms on a realistic diffusion MR phantom. Neuroimage 56, 220–234 10.1016/j.neuroimage.2011.01.032
    1. Fischl B. (2012). FreeSurfer. Neuroimage 62, 774–781 10.1016/j.neuroimage.2012.01.021
    1. Fjell A. M., Westlye L. T., Greve D. N., Fischl B., Benner T., van der Kouwe A. J., et al. (2008). The relationship between diffusion tensor imaging and volumetry as measures of white matter properties. Neuroimage 42, 1654–1668 10.1016/j.neuroimage.2008.06.005
    1. Friman O., Farneback G., Westin C. F. (2006). A Bayesian approach for stochastic white matter tractography. IEEE Trans. Med. Imaging 25, 965–978
    1. Friston K. J., Ashburner J. T., Kiebel S. J., Nichols T. E., Penny W. D. (2007). Statistical Parametric Mapping: The Analysis of Functional Brain Images. London: Academic Press
    1. Fung S. H., Roccatagliata L., Gonzalez R. G., Schaefer P. W. (2011). MR diffusion imaging in ischemic stroke. Neuroimaging Clin. N. Am. 21, 345–377 10.1016/j.nic.2011.03.001
    1. Gallichan D., Scholz J., Bartsch A., Behrens T. E., Robson M. D., Miller K. L. (2010). Addressing a systematic vibration artifact in diffusion-weighted MRI. Hum. Brain Mapp. 31, 193–202 10.1002/hbm.20856
    1. Garyfallidis E., Brett M., Amirbekian B., Nguyen C., Yeh F.-C., Olivetti E., et al. (2011). Dipy – a novel software library for diffusion MR and tractography, in 17th Annual Meeting of the Organization for Human Brain Mapping (Québec, QC: ).
    1. Goebel R. (2012). BrainVoyager– past, present, future. Neuroimage 62, 748–756 10.1016/j.neuroimage.2012.01.083
    1. Greicius M. D., Supekar K., Menon V., Dougherty R. F. (2009). Resting-state functional connectivity reflects structural connectivity in the default mode network. Cereb. Cortex 19, 72–78 10.1093/cercor/bhn059
    1. Griswold M. A., Jakob P. M., Heidemann R. M., Nittka M., Jellus V., Wang J., et al. (2002). Generalized autocalibrating partially parallel acquisitions (GRAPPA). Magn. Reson. Med. 47, 1202–1210 10.1002/mrm.10171
    1. Gudbjartsson H., Maier S. E., Mulkern R. V., Morocz I. A., Patz S., Jolesz F. A. (1996). Line scan diffusion imaging. Magn. Reson. Med. 36, 509–519
    1. Gullmar D., Haueisen J., Reichenbach J. R. (2010). Influence of anisotropic electrical conductivity in white matter tissue on the EEG/MEG forward and inverse solution. A high-resolution whole head simulation study. Neuroimage 51, 145–163 10.1016/j.neuroimage.2010.02.014
    1. Gupta R. K., Trivedi R., Awasthi R., Paliwal V. K., Prasad K. N., Rathore R. K. (2012). Understanding changes in DTI metrics in patients with different stages of neurocysticercosis. Magn. Reson. Imaging 30, 104–111 10.1016/j.mri.2011.07.027
    1. Hagmann P., Jonasson L., Maeder P., Thiran J. P., Wedeen V. J., Meuli R. (2006). Understanding diffusion MR imaging techniques: from scalar diffusion-weighted imaging to diffusion tensor imaging and beyond. Radiographics 26Suppl. 1, S205–S223 10.1148/rg.26si065510
    1. Hasan K. M., Walimuni I. S., Abid H., Hahn K. R. (2011). A review of diffusion tensor magnetic resonance imaging computational methods and software tools. Comput. Biol. Med. 41, 1062–1072 10.1016/j.compbiomed.2010.10.008
    1. Hattingen E., Rathert J., Jurcoane A., Weidauer S., Szelenyi A., Ogrezeanu G., et al. (2009). A standardised evaluation of pre-surgical imaging of the corticospinal tract: where to place the seed ROI. Neurosurg. Rev. 32, 445–456 10.1007/s10143-009-0197-1
    1. Hoeft F., Barnea-Goraly N., Haas B. W., Golarai G., Ng D., Mills D., et al. (2007). More is not always better: increased fractional anisotropy of superior longitudinal fasciculus associated with poor visuospatial abilities in Williams syndrome. J. Neurosci. 27, 11960–11965 10.1523/JNEUROSCI.3591-07.2007
    1. Holdsworth S. J., Skare S., Newbould R. D., Bammer R. (2009). Robust GRAPPA-accelerated diffusion-weighted readout-segmented (RS)-EPI. Magn. Reson. Med. 62, 1629–1640 10.1002/mrm.22122
    1. Huang H., Ceritoglu C., Li X., Qiu A., Miller M. I., Van Zijl P. C., et al. (2008). Correction of B0 susceptibility induced distortion in diffusion-weighted images using large-deformation diffeomorphic metric mapping. Magn. Reson. Imaging 26, 1294–1302 10.1016/j.mri.2008.03.005
    1. Hubers A., Klein J. C., Kang J. S., Hilker R., Ziemann U. (2012). The relationship between TMS measures of functional properties and DTI measures of microstructure of the corticospinal tract. Brain Stimul. 5, 297–304 10.1016/j.brs.2011.03.008
    1. Hygino Da Cruz L.C., Jr., Vieira I. G., Domingues R. C. (2011). Diffusion MR imaging: an important tool in the assessment of brain tumors. Neuroimaging Clin. N. Am. 21, 27–49 10.1016/j.nic.2011.01.010
    1. Imfeld A., Oechslin M. S., Meyer M., Loenneker T., Jancke L. (2009). White matter plasticity in the corticospinal tract of musicians: a diffusion tensor imaging study. Neuroimage 46, 600–607 10.1016/j.neuroimage.2009.02.025
    1. Jaermann T., Pruessmann K. P., Valavanis A., Kollias S., Boesiger P. (2006). Influence of SENSE on image properties in high-resolution single-shot echo-planar DTI. Magn. Reson. Med. 55, 335–342 10.1002/mrm.20769
    1. Jansons K. M., Alexander D. C. (2003). Persistent Angular Structure: new insights from diffusion MRI data. Dummy version. Inf. Process. Med. Imaging 18, 672–683
    1. Jellison B. J., Field A. S., Medow J., Lazar M., Salamat M. S., Alexander A. L. (2004). Diffusion tensor imaging of cerebral white matter: a pictorial review of physics, fiber tract anatomy, and tumor imaging patterns. AJNR. Am. J. Neuroradiol. 25, 356–369
    1. Jiang H., Chou M.-C., Van Zijl P., Mori S. (2009). Outlier detection for diffusion tensor imaging by testing for ADC consistency, in Proceedings of the International Society for Magnetic Resonance in Medicine (Honolulu, HI: ), 17.
    1. Jiang H., Van Zijl P. C., Kim J., Pearlson G. D., Mori S. (2006). DtiStudio: resource program for diffusion tensor computation and fiber bundle tracking. Comput. Methods Programs Biomed. 81, 106–116 10.1016/j.cmpb.2005.08.004
    1. Johansen-Berg H., Behrens T. E. J. (2009). Diffusion MRI: From Quantitative Measurement to In-Vivo Neuroanatomy. London: Academic Press
    1. Jones D. K. (2004). The effect of gradient sampling schemes on measures derived from diffusion tensor MRI: a Monte Carlo study. Magn. Reson. Med. 51, 807–815 10.1002/mrm.20033
    1. Jones D. K. (2008). Studying connections in the living human brain with diffusion MRI. Cortex 44, 936–952 10.1016/j.cortex.2008.05.002
    1. Jones D. K. (2010a). Challenges and limitations of quantifying brain connectivity in vivo with diffusion MRI. Imaging Med. 2, 341–355
    1. Jones D. K. (2010b). Diffusion MRI: Theory, Methods, and Applications. New York, NY: Oxford University Press
    1. Jones D. K. (2010c). Precision and accuracy in diffusion tensor magnetic resonance imaging. Top. Magn. Reson. Imaging 21, 87–99 10.1097/RMR.0b013e31821e56ac
    1. Jones D. K., Cercignani M. (2010). Twenty-five pitfalls in the analysis of diffusion MRI data. NMR Biomed. 23, 803–820 10.1002/nbm.1543
    1. Jones D. K., Griffin L. D., Alexander D. C., Catani M., Horsfield M. A., Howard R., et al. (2002). Spatial normalization and averaging of diffusion tensor MRI data sets. Neuroimage 17, 592–617 10.1006/nimg.2002.1148
    1. Jones D. K., Horsfield M. A., Simmons A. (1999a). Optimal strategies for measuring diffusion in anisotropic systems by magnetic resonance imaging. Magn. Reson. Med. 42, 515–525 10.1002/(SICI)1522-2594(199909)42:3<515::AID-MRM14>;2-Q
    1. Jones D. K., Knosche T. R., Turner R. (2012). White matter integrity, fiber count, and other fallacies: the do's and don'ts of diffusion MRI. Neuroimage. [Epub ahead of print]. 10.1016/j.neuroimage.2012.06.081
    1. Jones D. K., Simmons A., Williams S. C., Horsfield M. A. (1999b). Non-invasive assessment of axonal fiber connectivity in the human brain via diffusion tensor MRI. Magn. Reson. Med. 42, 37–41 10.1002/(SICI)1522-2594(199907)42:1<37::AID-MRM7>;2-O
    1. Kaur P., Senthil Kumaran S., Tripathi R. P., Khushu S., Kaushik S. (2007). Protocol error artifacts in MRI: sources and remedies revisited. Radiography 13, 291–306
    1. Kennedy S. D., Zhong J. (2004). Diffusion measurements free of motion artifacts using intermolecular dipole-dipole interactions. Magn. Reson. Med. 52, 1–6 10.1002/mrm.20134
    1. Kindlmann G. (2006). Superquadric tensor glyphs, in Proceeding of The Joint Eurographics – IEEE TCVG Symposium on Visualization (Konstanz: ), 147–154
    1. Kindlmann G., Westin C. F. (2006). Diffusion tensor visualization with glyph packing. IEEE. Trans. Vis. Comput. Graph. 12, 1329–1335
    1. Koay C. G., Carew J. D., Alexander A. L., Basser P. J., Meyerand M. E. (2006). Investigation of anomalous estimates of tensor-derived quantities in diffusion tensor imaging. Magn. Reson. Med. 55, 930–936 10.1002/mrm.20832
    1. Kober T., Gruetter R., Krueger G. (2012). Prospective and retrospective motion correction in diffusion magnetic resonance imaging of the human brain. Neuroimage 59, 389–398 10.1016/j.neuroimage.2011.07.004
    1. Kochunov P., Glahn D. C., Lancaster J., Thompson P. M., Kochunov V., Rogers B., et al. (2011). Fractional anisotropy of cerebral white matter and thickness of cortical gray matter across the lifespan. Neuroimage 58, 41–49 10.1016/j.neuroimage.2011.05.050
    1. Lagana M., Rovaris M., Ceccarelli A., Venturelli C., Marini S., Baselli G. (2010). DTI parameter optimisation for acquisition at 1.5T: SNR analysis and clinical application. Comput. Intell. Neurosci. 2010:254032 10.1155/2010/254032
    1. Landman B. A., Bogovic J. A., Wan H., Elshahaby Fel Z., Bazin P. L., Prince J. L. (2012). Resolution of crossing fibers with constrained compressed sensing using diffusion tensor MRI. Neuroimage 59, 2175–2186 10.1016/j.neuroimage.2011.10.011
    1. Lauzon C. B., Asman A. J., Crainiceanu C., Caffo B. C., Landman B. A. (2011). Assessment of bias for MRI diffusion tensor imaging using SIMEX. Med. Image Comput. Comput. Assist. Interv. 14, 107–115
    1. Lawes I. N., Barrick T. R., Murugam V., Spierings N., Evans D. R., Song M., et al. (2008). Atlas-based segmentation of white matter tracts of the human brain using diffusion tensor tractography and comparison with classical dissection. Neuroimage 39, 62–79 10.1016/j.neuroimage.2007.06.041
    1. Lazar M., Weinstein D. M., Tsuruda J. S., Hasan K. M., Arfanakis K., Meyerand M. E., et al. (2003). White matter tractography using diffusion tensor deflection. Hum. Brain Mapp. 18, 306–321 10.1002/hbm.10102
    1. Le Bihan B., Breton E. (1985). Imagerie de diffusion in vivo par résonance magnétique nucléaire. C. R. Acad. Sci. 301, 1109–1112
    1. Le Bihan D. (2012). Diffusion, confusion and functional MRI. Neuroimage 62, 1131–1136 10.1016/j.neuroimage.2011.09.058
    1. Le Bihan D., Breton E., Lallemand D., Grenier P., Cabanis E., Laval-Jeantet M. (1986). MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders. Radiology 161, 401–407
    1. Le Bihan D., Mangin J. F., Poupon C., Clark C. A., Pappata S., Molko N., et al. (2001). Diffusion tensor imaging: concepts and applications. J. Magn. Reson. Imaging 13, 534–546 10.1002/jmri.1076
    1. Le Bihan D., Poupon C., Amadon A., Lethimonnier F. (2006). Artifacts and pitfalls in diffusion MRI. J. Magn. Reson. Imaging 24, 478–488 10.1002/jmri.20683
    1. Lebel C., Benner T., Beaulieu C. (2012). Six is enough? Comparison of diffusion parameters measured using six or more diffusion-encoding gradient directions with deterministic tractography. Magn. Reson. Med. 68, 474–483 10.1002/mrm.23254
    1. Leemans A., Jeurissen B., Sijbers J., Jones D. K. (2009). ExploreDTI: a graphical toolbox for processing, analyzing, and visualizing diffusion MR data, in 17th Annual Meeting of Intl. Soc. Mag. Reson. Med. (Hawaii: ), 3537.
    1. Leemans A., Jones D. K. (2009). The B-matrix must be rotated when correcting for subject motion in DTI data. Magn. Reson. Med. 61, 1336–1349 10.1002/mrm.21890
    1. Li K., Guo L., Zhu D., Hu X., Han J., Liu T. (2012). Individual functional ROI optimization via maximization of group-wise consistency of structural and functional profiles. Neuroinformatics 10, 225–242 10.1007/s12021-012-9142-5
    1. Liao W., Deserno T., Spitzer K. (2008). Evaluation of free non-diagnostic DICOM software tools. Proc. SPIE 6919, 691903
    1. Ling J., Merideth F., Caprihan A., Pena A., Teshiba T., Mayer A. R. (2012). Head injury or head motion? Assessment and quantification of motion artifacts in diffusion tensor imaging studies. Hum. Brain Mapp. 33, 50–62 10.1002/hbm.21192
    1. Liu G., Yao L., Zhao X. (2010a). Optimization of image preprocessing for diffusion tensor magnetic resonance imaging, in Sixth International Conference on Natural Computation (ICNC) (Yantai: ).
    1. Liu Z., Wang Y., Gerig G., Gouttard S., Tao R., Fletcher T., et al. (2010b). Quality control of diffusion weighted images. Proc. SPIE 7628:76280J 10.1117/12.844748
    1. Lucas B. C., Bogovic J. A., Carass A., Bazin P. L., Prince J. L., Pham D. L., et al. (2010). The Java Image Science Toolkit (JIST) for rapid prototyping and publishing of neuroimaging software. Neuroinformatics 8, 5–17 10.1007/s12021-009-9061-2
    1. Madden D. J., Bennett I. J., Song A. W. (2009). Cerebral white matter integrity and cognitive aging: contributions from diffusion tensor imaging. Neuropsychol. Rev. 19, 415–435 10.1007/s11065-009-9113-2
    1. Mansfield P. (1977). Multi-planar image formation using NMR spin echoes. J. Phys. C 10, L55–L58
    1. Merboldt K.-D., Hanicke W., Frahm J. (1985). Self-diffusion NMR imaging using stimulated echoes. J. Magn. Reson. 64, 479–486
    1. Millman K. J., Brett M. (2007). Analysis of functional magnetic resonance imaging in python. Comp. Sci. Eng. 9, 52–55
    1. Mohammadi S., Moller H. E., Kugel H., Muller D. K., Deppe M. (2010). Correcting eddy current and motion effects by affine whole-brain registrations: evaluation of three-dimensional distortions and comparison with slicewise correction. Magn. Reson. Med. 64, 1047–1056 10.1002/mrm.22501
    1. Mohammadi S., Nagy Z., Hutton C., Josephs O., Weiskopf N. (2012). Correction of vibration artifacts in DTI using phase-encoding reversal (COVIPER). Magn. Reson. Med. 68, 882–889 10.1002/mrm.23308
    1. Mori S. (2007). Introduction to Diffusion Tensor Imaging. Amsterdam: Elsevier Science
    1. Mori S., Barker P. B. (1999). Diffusion magnetic resonance imaging: its principle and applications. Anat. Rec. 257, 102–109 10.1002/(SICI)1097-0185(19990615)257:3<102::AID-AR7>;2-6
    1. Mori S., Crain B. J., Chacko V. P., van Zijl P. C. (1999). Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging. Ann. Neurol. 45, 265–269
    1. Mori S., van Zijl P. C. (2002). Fiber tracking: principles and strategies– a technical review. NMR Biomed. 15, 468–480 10.1002/nbm.781
    1. Mori S., Zhang J. (2006). Principles of diffusion tensor imaging and its applications to basic neuroscience research. Neuron 51, 527–539 10.1016/j.neuron.2006.08.012
    1. Moritani T., Ekholm S., Westesson P. (2005). Diffusion-Weighted MR Imaging of the Brain. Berlin, Heidelberg: Springer
    1. Moriya J., Kakeda S., Abe O., Goto N., Yoshimura R., Hori H., et al. (2010). Gray and white matter volumetric and diffusion tensor imaging (DTI) analyses in the early stage of first-episode schizophrenia. Schizophr. Res. 116, 196–203 10.1016/j.schres.2009.10.002
    1. Moseley M., Bammer R., Illes J. (2002). Diffusion-tensor imaging of cognitive performance. Brain Cogn. 50, 396–413 10.1016/S0278-2626(02)00524-9
    1. Moseley M. E., Cohen Y., Mintorovitch J., Chileuitt L., Shimizu H., Kucharczyk J., et al. (1990). Early detection of regional cerebral ischemia in cats: comparison of diffusion- and T2-weighted MRI and spectroscopy. Magn. Reson. Med. 14, 330–346
    1. Mukherjee P., Berman J. I., Chung S. W., Hess C. P., Henry R. G. (2008a). Diffusion tensor MR imaging and fiber tractography: theoretic underpinnings. AJNR. Am. J. Neuroradiol. 29, 632–641 10.3174/ajnr.A1051
    1. Mukherjee P., Chung S. W., Berman J. I., Hess C. P., Henry R. G. (2008b). Diffusion tensor MR imaging and fiber tractography: technical considerations. AJNR. Am. J. Neuroradiol. 29, 843–852 10.3174/ajnr.A1052
    1. Mukherjee P., Hess C. P., Xu D., Han E. T., Kelley D. A., Vigneron D. B. (2008c). Development and initial evaluation of 7-T q-ball imaging of the human brain. Magn. Reson. Imaging 26, 171–180 10.1016/j.mri.2007.05.011
    1. Nana R., Zhao T., Hu X. (2008). Single-shot multiecho parallel echo-planar imaging (EPI) for diffusion tensor imaging (DTI) with improved signal-to-noise ratio (SNR) and reduced distortion. Magn. Reson. Med. 60, 1512–1517 10.1002/mrm.21770
    1. Nolte U. G., Finsterbusch J., Frahm J. (2000). Rapid isotropic diffusion mapping without susceptibility artifacts: whole brain studies using diffusion-weighted single-shot STEAM MR imaging. Magn. Reson. Med. 44, 731–736 10.1002/1522-2594(200011)44:5<731::AID-MRM11>;2-1
    1. Nowinski W. L., Chua B. C., Yang G. L., Qian G. Y. (2012). Three-dimensional interactive and stereotactic human brain atlas of white matter tracts. Neuroinformatics 10, 33–55 10.1007/s12021-011-9118-x
    1. Nucifora P. G., Verma R., Lee S. K., Melhem E. R. (2007). Diffusion-tensor MR imaging and tractography: exploring brain microstructure and connectivity. Radiology 245, 367–384 10.1148/radiol.2452060445
    1. Oishi K., Faria A. V., Zijl P. C. M., Mori S. (2010). MRI Atlas of Human White Matter. London: Academic Press
    1. Oishi K., Zilles K., Amunts K., Faria A., Jiang H., Li X., et al. (2008). Human brain white matter atlas: identification and assignment of common anatomical structures in superficial white matter. Neuroimage 43, 447–457 10.1016/j.neuroimage.2008.07.009
    1. Ordidge R. J., Helpern J. A., Qing Z. X., Knight R. A., Nagesh V. (1994). Correction of motional artifacts in diffusion-weighted MR images using navigator echoes. Magn. Reson. Imaging 12, 455–460
    1. Papademetris X., Jackowski M., Rajeevan N., Constable R. T., Staib L. (2005). Bioimage Suite: an integrated medical image analysis suite, in The Insight Journal – 2005 MICCAI Open-Source Workshop (Palm Springs, CA: ).
    1. Park H. J., Kubicki M., Shenton M. E., Guimond A., McCarley R. W., Maier S. E., et al. (2003). Spatial normalization of diffusion tensor MRI using multiple channels. Neuroimage 20, 1995–2009 10.1016/j.neuroimage.2003.08.008
    1. Park H. J., Shenton M. E., Westin C. F. (2004). An analysis tool for quantification of diffusion tensor imaging, in Seventh International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'04) (Saint-Malo: ), 1040–1041
    1. Parker G. J., Haroon H. A., Wheeler-Kingshott C. A. (2003). A framework for a streamline-based probabilistic index of connectivity (PICo) using a structural interpretation of MRI diffusion measurements. J. Magn. Reson. Imaging 18, 242–254 10.1002/jmri.10350
    1. Patel V., Dinov I. D., Van Horn J. D., Thompson P. M., Toga A. W. (2010). LONI MiND: metadata in NIfTI for DWI. Neuroimage 51, 665–676 10.1016/j.neuroimage.2010.02.069
    1. Pfefferbaum A., Adalsteinsson E., Sullivan E. V. (2003). Replicability of diffusion tensor imaging measurements of fractional anisotropy and trace in brain. J. Magn. Reson. Imaging 18, 427–433 10.1002/jmri.10377
    1. Pieper S., Lorensen B., Schroeder W., Kikinis R. (2006). The NA-MIC kit: ITK, VTK, pipelines, grids and 3D slicer as an open platform for the medical image computing community, in Proceedings of the IEEE International Symposium on Biomedical Imaging ISBI (Arlington, TX: ), 698–701
    1. Pierpaoli C., Basser P. J. (1996). Toward a quantitative assessment of diffusion anisotropy. Magn. Reson. Med. 36, 893–906
    1. Pierpaoli C., Jezzard P., Basser P. J., Barnett A., Di Chiro G. (1996). Diffusion tensor MR imaging of the human brain. Radiology 201, 637–648
    1. Pierpaoli C., Walker L., Irfanoglu M. O., Barnett A., Basser P., Chang L. C., et al. (2010). TORTOISE: an integrated software package for processing of diffusion MRI data, in ISMRM 18th Annual Meeting (Stockholm: ).
    1. Pipe J. G. (1999). Motion correction with PROPELLER MRI: application to head motion and free-breathing cardiac imaging. Magn. Reson. Med. 42, 963–969 10.1002/(SICI)1522-2594(199911)42:5<963::AID-MRM17>;2-L
    1. Pipe J. G., Farthing V. G., Forbes K. P. (2002). Multishot diffusion-weighted FSE using PROPELLER MRI. Magn. Reson. Med. 47, 42–52 10.1002/mrm.10014
    1. Polders D. L., Leemans A., Hendrikse J., Donahue M. J., Luijten P. R., Hoogduin J. M. (2011). Signal to noise ratio and uncertainty in diffusion tensor imaging at 1.5, 3.0, and 7.0 Tesla. J. Magn. Reson. Imaging 33, 1456–1463 10.1002/jmri.22554
    1. Propper R. E., O'Donnell L. J., Whalen S., Tie Y., Norton I. H., Suarez R. O., et al. (2010). A combined fMRI and DTI examination of functional language lateralization and arcuate fasciculus structure: effects of degree versus direction of hand preference. Brain Cogn. 73, 85–92 10.1016/j.bandc.2010.03.004
    1. Pruessmann K. P., Weiger M., Scheidegger M. B., Boesiger P. (1999). SENSE: sensitivity encoding for fast MRI. Magn. Reson. Med. 42, 952–962 10.1002/(SICI)1522-2594(199911)42:5<952::AID-MRM16>;2-S
    1. Reese T. G., Heid O., Weisskoff R. M., Wedeen V. J. (2003). Reduction of eddy-current-induced distortion in diffusion MRI using a twice-refocused spin echo. Magn. Reson. Med. 49, 177–182 10.1002/mrm.10308
    1. Rohde G. K., Barnett A. S., Basser P. J., Marenco S., Pierpaoli C. (2004). Comprehensive approach for correction of motion and distortion in diffusion-weighted MRI. Magn. Reson. Med. 51, 103–114 10.1002/mrm.10677
    1. Rosset A., Spadola L., Ratib O. (2004). OsiriX: an open-source software for navigating in multidimensional DICOM images. J. Digit. Imaging 17, 205–216 10.1007/s10278-004-1014-6
    1. Seifert M. H., Jakob P. M., Jellus V., Haase A., Hillenbrand C. (2000). High-resolution diffusion imaging using a radial turbo-spin-echo sequence: implementation, eddy current compensation, and self-navigation. J. Magn. Reson. 144, 243–254 10.1006/jmre.2000.2041
    1. Smith S. M., Jenkinson M., Johansen-Berg H., Rueckert D., Nichols T. E., MacKay C. E., et al. (2006). Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage 31, 1487–1505 10.1016/j.neuroimage.2006.02.024
    1. Smith S. M., Jenkinson M., Woolrich M. W., Beckmann C. F., Behrens T. E., Johansen-Berg H., et al. (2004). Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 23Suppl. 1, S208–S219 10.1016/j.neuroimage.2004.07.051
    1. Snook L., Plewes C., Beaulieu C. (2007). Voxel based versus region of interest analysis in diffusion tensor imaging of neurodevelopment. Neuroimage 34, 243–252 10.1016/j.neuroimage.2006.07.021
    1. Song S. K., Sun S. W., Ramsbottom M. J., Chang C., Russell J., Cross A. H. (2002). Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water. Neuroimage 17, 1429–1436 10.1006/nimg.2002.1267
    1. Stehling M. K., Turner R., Mansfield P. (1991). Echo-planar imaging: magnetic resonance imaging in a fraction of a second. Science 254, 43–50 10.1126/science.1925560
    1. Sundgren P. C., Dong Q., Gomez-Hassan D., Mukherji S. K., Maly P., Welsh R. (2004). Diffusion tensor imaging of the brain: review of clinical applications. Neuroradiology 46, 339–350 10.1007/s00234-003-1114-x
    1. Tang C. Y., Friedman J., Shungu D., Chang L., Ernst T., Stewart D., et al. (2007). Correlations between Diffusion Tensor Imaging (DTI) and Magnetic Resonance Spectroscopy (1H MRS) in schizophrenic patients and normal controls. BMC Psychiatry 7:25 10.1186/1471-244X-7-25
    1. Taylor D. G., Bushell M. C. (1985). The spatial mapping of translational diffusion coefficients by the NMR imaging technique. Phys. Med. Biol. 30, 345–349 10.1088/0031-9155/30/4/009
    1. Tensaouti F., Lahlou I., Clarisse P., Lotterie J. A., Berry I. (2011). Quantitative and reproducibility study of four tractography algorithms used in clinical routine. J. Magn. Reson. Imaging 34, 165–172 10.1002/jmri.22584
    1. Thomason M. E., Dougherty R. F., Colich N. L., Perry L. M., Rykhlevskaia E. I., Louro H. M., et al. (2010). COMT genotype affects prefrontal white matter pathways in children and adolescents. Neuroimage 53, 926–934 10.1016/j.neuroimage.2010.01.033
    1. Thomason M. E., Thompson P. M. (2011). Diffusion imaging, white matter, and psychopathology. Annu. Rev. Clin. Psychol. 7, 63–85 10.1146/annurev-clinpsy-032210-104507
    1. Tournier J. D., Calamante F., Connelly A. (2012). MRtrix: diffusion tractography in crossing fiber regions. Int. J. Imaging Syst. Technol. 22, 53–66 10.1016/j.neuroimage.2010.12.008
    1. Tournier J. D., Mori S., Leemans A. (2011). Diffusion tensor imaging and beyond. Magn. Reson. Med. 65, 1532–1556 10.1002/mrm.22924
    1. Toussaint N., Souplet J. C., Fillard P. (2007). MedINRIA: medical image navigation and research tool by INRIA, in Workshop on Interaction in Medical Image Analysis and Visualization (Brisbane, QLD: ).
    1. Truong T. K., Chen B., Song A. W. (2008). Integrated SENSE DTI with correction of susceptibility- and eddy current-induced geometric distortions. Neuroimage 40, 53–58 10.1016/j.neuroimage.2007.12.001
    1. Truong T.-K., Chen N.-K., Song A. W. (2011). Dynamic correction of artifacts due to susceptibility effects and time-varying eddy currents in diffusion tensor imaging. Neuroimage 57, 1343–1347 10.1016/j.neuroimage.2011.06.008
    1. Tuch D. S. (2004). Q-ball imaging. Magn. Reson. Med. 52, 1358–1372 10.1002/mrm.20279
    1. Tuch D. S., Reese T. G., Wiegell M. R., Makris N., Belliveau J. W., Wedeen V. J. (2002). High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity. Magn. Reson. Med. 48, 577–582 10.1002/mrm.10268
    1. Turner R., Le Bihan D., Chesnick A. S. (1991). Echo-planar imaging of diffusion and perfusion. Magn. Reson. Med. 19, 247–253
    1. Van Den Heuvel M., Mandl R., Luigjes J., Hulshoff Pol H. (2008). Microstructural organization of the cingulum tract and the level of default mode functional connectivity. J. Neurosci. 28, 10844–10851 10.1523/JNEUROSCI.2964-08.2008
    1. Van Den Heuvel M. P., Mandl R. C., Kahn R. S., Hulshoff Pol H. E. (2009). Functionally linked resting-state networks reflect the underlying structural connectivity architecture of the human brain. Hum. Brain Mapp. 30, 3127–3141 10.1002/hbm.20737
    1. Van Hecke W., Leemans A., De Backer S., Jeurissen B., Parizel P. M., Sijbers J. (2010). Comparing isotropic and anisotropic smoothing for voxel-based DTI analyses: a simulation study. Hum. Brain Mapp. 31, 98–114 10.1002/hbm.20848
    1. Vilanova A., Zhang S., Kindlmann G., Laidlaw D. (2006). An introduction to visualization of diffusion tensor imaging and its applications, in Visualization and Processing of Tensor Fields, eds Weickert J., Hagen H. (Berlin, Heidelberg: Springer; ), 121–153
    1. Voineskos A. N., Rajji T. K., Lobaugh N. J., Miranda D., Shenton M. E., Kennedy J. L., et al. (2012). Age-related decline in white matter tract integrity and cognitive performance: a DTI tractography and structural equation modeling study. Neurobiol. Aging 33, 21–34 10.1016/j.neurobiolaging.2010.02.009
    1. Vos S. B., Jones D. K., Jeurissen B., Viergever M. A., Leemans A. (2012). The influence of complex white matter architecture on the mean diffusivity in diffusion tensor MRI of the human brain. Neuroimage 59, 2208–2216 10.1016/j.neuroimage.2011.09.086
    1. Wakana S., Caprihan A., Panzenboeck M. M., Fallon J. H., Perry M., Gollub R. L., et al. (2007). Reproducibility of quantitative tractography methods applied to cerebral white matter. Neuroimage 36, 630–644 10.1016/j.neuroimage.2007.02.049
    1. Wakana S., Jiang H., Nagae-Poetscher L. M., van Zijl P. C., Mori S. (2004). Fiber tract-based atlas of human white matter anatomy. Radiology 230, 77–87 10.1148/radiol.2301021640
    1. Wang J. J., Durazzo T. C., Gazdzinski S., Yeh P. H., Mon A., Meyerhoff D. J. (2009). MRSI and DTI: a multimodal approach for improved detection of white matter abnormalities in alcohol and nicotine dependence. NMR Biomed. 22, 516–522 10.1002/nbm.1363
    1. Wang J. Y., Abdi H., Bakhadirov K., Diaz-Arrastia R., Devous M. D., Sr. (2011). A comprehensive reliability assessment of quantitative diffusion tensor tractography. Neuroimage 60, 1127–1138 10.1016/j.neuroimage.2011.12.062
    1. Wang R., Benner T., Sorensen A. G., Wedeen V. J. (2007). Diffusion toolkit: a software package for diffusion imaging data processing and tractography, in Proceedings of the International Society for Magnetic Resonance in Medicine (Berlin: ), 3720.
    1. Wedeen V. J., Rosene D. L., Wang R., Dai G., Mortazavi F., Hagmann P., et al. (2012). The geometric structure of the brain fiber pathways. Science 335, 1628–1634 10.1126/science.1215280
    1. Wedeen V. J., Wang R. P., Schmahmann J. D., Benner T., Tseng W. Y., Dai G., et al. (2008). Diffusion spectrum magnetic resonance imaging (DSI) tractography of crossing fibers. Neuroimage 41, 1267–1277 10.1016/j.neuroimage.2008.03.036
    1. Weinstein D. M., Kindlmann G. L., Lundberg E. C. (1999). Tensorlines: advection-diffusion based propagation through diffusion tensor fields, in Proceedings of the 10th IEEE Visualization 1999 Conference (VIS'99) (San Francisco, CA: IEEE Computer Society; ).
    1. Westin C. F., Maier S. E., Mamata H., Nabavi A., Jolesz F. A., Kikinis R. (2002). Processing and visualization for diffusion tensor MRI. Med. Image Anal. 6, 93–108 10.1016/S1361-8415(02)00053-1
    1. White T., Nelson M., Lim K. O. (2008). Diffusion tensor imaging in psychiatric disorders. Top. Magn. Reson. Imaging 19, 97–109 10.1097/RMR.0b013e3181809f1e
    1. Wiegell M. R., Larsson H. B., Wedeen V. J. (2000). Fiber crossing in human brain depicted with diffusion tensor MR imaging. Radiology 217, 897–903
    1. Xing D., Papadakis N. G., Huang C. L., Lee V. M., Carpenter T. A., Hall L. D. (1997). Optimised diffusion-weighting for measurement of apparent diffusion coefficient (ADC) in human brain. Magn. Reson. Imaging 15, 771–784
    1. Xu D., Henry R. G., Mukherjee P., Carvajal L., Miller S. P., Barkovich A. J., et al. (2004). Single-shot fast spin-echo diffusion tensor imaging of the brain and spine with head and phased array coils at 1.5 T and 3.0 T. Magn. Reson. Imaging 22, 751–759 10.1016/j.mri.2004.01.075
    1. Xu D., Mori S., Shen D., Van Zijl P. C., Davatzikos C. (2003). Spatial normalization of diffusion tensor fields. Magn. Reson. Med. 50, 175–182 10.1002/mrm.10489
    1. Yakushev I., Schreckenberger M., Muller M. J., Schermuly I., Cumming P., Stoeter P., et al. (2011). Functional implications of hippocampal degeneration in early Alzheimer's disease: a combined DTI and PET study. Eur. J. Nucl. Med. Mol. Imaging 38, 2219–2227 10.1007/s00259-011-1882-1
    1. Yamada K., Sakai K., Akazawa K., Yuen S., Nishimura T. (2009). MR tractography: a review of its clinical applications. Magn. Reson. Med. Sci. 8, 165–174
    1. Yang E., Nucifora P. G., Melhem E. R. (2011). Diffusion MR imaging: basic principles. Neuroimaging Clin. N. Am. 21, 1–25 10.1016/j.nic.2011.02.001
    1. Zalesky A. (2011). Moderating registration misalignment in voxelwise comparisons of DTI data: a performance evaluation of skeleton projection. Magn. Reson. Imaging 29, 111–125 10.1016/j.mri.2010.06.027
    1. Zhang H., Yushkevich P. A., Gee J. C. (2009). DTI toolkit: a spatial normalization and atlas construction toolkit optimized for examining white matter morphometry using DTI data, in International Society for Magnetic Resonance in Medicine (Honolulu, HI: ).
    1. Zhang Y., Zhang J., Oishi K., Faria A. V., Jiang H., Li X., et al. (2010). Atlas-guided tract reconstruction for automated and comprehensive examination of the white matter anatomy. Neuroimage 52, 1289–1301 10.1016/j.neuroimage.2010.05.049
    1. Zhou Y., Qun X., Qin L. D., Qian L. J., Cao W. W., Xu J. R. (2011a). A primary study of diffusion tensor imaging-based histogram analysis in vascular cognitive impairment with no dementia. Clin. Neurol. Neurosurg. 113, 92–97 10.1016/j.clineuro.2010.09.007
    1. Zhou Z., Liu W., Cui J., Wang X., Arias D., Wen Y., et al. (2011b). Automated artifact detection and removal for improved tensor estimation in motion-corrupted DTI data sets using the combination of local binary patterns and 2D partial least squares. Magn. Reson. Imaging 29, 230–242 10.1016/j.mri.2010.06.022
    1. Zhu T., Hu R., Qiu X., Taylor M., Tso Y., Yiannoutsos C., et al. (2011). Quantification of accuracy and precision of multi-center DTI measurements: a diffusion phantom and human brain study. Neuroimage 56, 1398–1411 10.1016/j.neuroimage.2011.02.010
    1. Zhuang J., Hrabe J., Kangarlu A., Xu D., Bansal R., Branch C. A., et al. (2006). Correction of eddy-current distortions in diffusion tensor images using the known directions and strengths of diffusion gradients. J. Magn. Reson. Imaging 24, 1188–1193 10.1002/jmri.20727
    1. Zwiers M. P. (2010). Patching cardiac and head motion artefacts in diffusion-weighted images. Neuroimage 53, 565–575 10.1016/j.neuroimage.2010.06.014

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