Concerning the matching of magnetic susceptibility differences for the compensation of background gradients in anisotropic diffusion fibre phantoms
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[1] S. Meiboom,et al. Modified Spin‐Echo Method for Measuring Nuclear Relaxation Times , 1958 .
[2] J. E. Tanner,et al. Spin diffusion measurements : spin echoes in the presence of a time-dependent field gradient , 1965 .
[3] D. A. Dunnett. Classical Electrodynamics , 2020, Nature.
[4] K. J. Packer. The effects of diffusion through locally inhomogeneous magnetic fields on transverse nuclear spin relaxation in heterogeneous systems. Proton transverse relaxation in striated muscle tissue , 1973 .
[5] J. Leyte,et al. An NMR contribution to the interpretation of the dynamical behavior of water molecules as a function of the magnesium chloride concentration at 25.degree.C , 1987 .
[6] Jörg Kärger,et al. Principles and Application of Self-Diffusion Measurements by Nuclear Magnetic Resonance , 1988 .
[7] John C. Gore,et al. Studies of diffusion in random fields produced by variations in susceptibility , 1988 .
[8] John C. Gore,et al. Effects of susceptibility variations on NMR measurements of diffusion , 1991 .
[9] J C Gore,et al. Studies of restricted diffusion in heterogeneous media containing variations in susceptibility , 1991, Magnetic resonance in medicine.
[10] Aaron J. Miller,et al. The use of power images to perform quantitative analysis on low SNR MR images. , 1993, Magnetic resonance imaging.
[11] D. Ballon,et al. Resolution enhanced NMR spectroscopy in biological systems via magnetic susceptibility matched sample immersion chambers , 1993, Magnetic Resonance in Medicine.
[12] M. G. Prammer,et al. The CPMG Pulse Sequence in Strong Magnetic Field Gradients with Applications to Oil-Well Logging , 1995 .
[13] C. Beaulieu,et al. An in vitro evaluation of the effects of local magnetic‐susceptibility‐induced gradients on anisotropic water diffusion in nerve , 1996, Magnetic resonance in medicine.
[14] J. Schenck. The role of magnetic susceptibility in magnetic resonance imaging: MRI magnetic compatibility of the first and second kinds. , 1996, Medical physics.
[15] R. Fox,et al. Classical Electrodynamics, 3rd ed. , 1999 .
[16] Yu-Chung N. Cheng,et al. Magnetic Resonance Imaging: Physical Principles and Sequence Design , 1999 .
[17] G. Barker,et al. An in vivo evaluation of the effects of local magnetic susceptibility-induced gradients on water diffusion measurements in human brain. , 1999, Journal of magnetic resonance.
[18] N. J. Shah,et al. A New Method for Fast Multislice T 1 Mapping , 2001, NeuroImage.
[19] Stephen M. Smith,et al. A global optimisation method for robust affine registration of brain images , 2001, Medical Image Anal..
[20] D. Le Bihan,et al. Diffusion tensor imaging: Concepts and applications , 2001, Journal of magnetic resonance imaging : JMRI.
[21] Phillip Zhe Sun,et al. Background gradient suppression in pulsed gradient stimulated echo measurements. , 2003, Journal of magnetic resonance.
[22] V. Wedeen,et al. Reduction of eddy‐current‐induced distortion in diffusion MRI using a twice‐refocused spin echo , 2003, Magnetic resonance in medicine.
[23] Ching Yao,et al. Validation of diffusion spectrum magnetic resonance imaging with manganese-enhanced rat optic tracts and ex vivo phantoms , 2003, NeuroImage.
[24] V. Kiselev,et al. Effect of magnetic field gradients induced by microvasculature on NMR measurements of molecular self-diffusion in biological tissues. , 2004, Journal of magnetic resonance.
[25] Mark W. Woolrich,et al. Advances in functional and structural MR image analysis and implementation as FSL , 2004, NeuroImage.
[26] J. Sijbers,et al. Maximum likelihood estimation of signal amplitude and noise variance from MR data , 2004, Magnetic resonance in medicine.
[27] D. Tuch. Q‐ball imaging , 2004, Magnetic resonance in medicine.
[28] D. LeBihan,et al. Validation of q-ball imaging with a diffusion fibre-crossing phantom on a clinical scanner , 2005, Philosophical Transactions of the Royal Society B: Biological Sciences.
[29] R. Bowtell,et al. Application of a Fourier‐based method for rapid calculation of field inhomogeneity due to spatial variation of magnetic susceptibility , 2005 .
[30] Nathan Yanasak,et al. Use of capillaries in the construction of an MRI phantom for the assessment of diffusion tensor imaging: demonstration of performance. , 2006, Magnetic resonance imaging.
[31] Osamu Abe,et al. Flexible ex vivo phantoms for validation of diffusion tensor tractography on a clinical scanner , 2006, Radiation Medicine.
[32] Xenophon Papademetris,et al. Rapid calculations of susceptibility-induced magnetostatic field perturbations for in vivo magnetic resonance , 2006, Physics in medicine and biology.
[33] Alan Connelly,et al. Robust determination of the fibre orientation distribution in diffusion MRI: Non-negativity constrained super-resolved spherical deconvolution , 2007, NeuroImage.
[34] Jeff H. Duyn,et al. High-field MRI of brain cortical substructure based on signal phase , 2007, Proceedings of the National Academy of Sciences.
[35] William S. Price,et al. Suppression of background gradients in (B0 gradient‐based) NMR diffusion experiments , 2007 .
[36] E. Achten,et al. The design of anisotropic diffusion phantoms for the validation of diffusion weighted magnetic resonance imaging , 2008, Physics in medicine and biology.
[37] J. Mangin,et al. New diffusion phantoms dedicated to the study and validation of high‐angular‐resolution diffusion imaging (HARDI) models , 2008, Magnetic resonance in medicine.
[38] E. Achten,et al. Simulation and experimental verification of the diffusion in an anisotropic fiber phantom. , 2008, Journal of magnetic resonance.
[39] M. E. Bellemann,et al. Anisotropic Phantoms for Quantitative Diffusion Tensor Imaging and Fiber-Tracking Validation , 2008 .
[40] Chun-Hung Yeh,et al. Resolving crossing fibres using constrained spherical deconvolution: Validation using diffusion-weighted imaging phantom data , 2008, NeuroImage.
[41] Alexander Leemans,et al. The B‐matrix must be rotated when correcting for subject motion in DTI data , 2009, Magnetic resonance in medicine.
[42] P. Boesiger,et al. Construction of a temperature‐controlled diffusion phantom for quality control of diffusion measurements , 2009, Journal of magnetic resonance imaging : JMRI.
[43] Bram Stieltjes,et al. On the effects of dephasing due to local gradients in diffusion tensor imaging experiments: relevance for diffusion tensor imaging fiber phantoms. , 2009, Magnetic resonance imaging.
[44] Santiago Aja-Fernández,et al. Noise estimation in single- and multiple-coil magnetic resonance data based on statistical models. , 2009, Magnetic resonance imaging.
[45] Mark W. Woolrich,et al. Bayesian analysis of neuroimaging data in FSL , 2009, NeuroImage.
[46] Behrens,et al. Validation of Tractography , 2009 .
[47] P. Basser,et al. In vivo measurement of axon diameter distribution in the corpus callosum of rat brain. , 2009, Brain : a journal of neurology.
[48] Jan Sijbers,et al. ExploreDTI: a graphical toolbox for processing, analyzing, and visualizing diffusion MR data , 2009 .
[49] M. Fukunaga,et al. Sensitivity of MRI resonance frequency to the orientation of brain tissue microstructure , 2010, Proceedings of the National Academy of Sciences.
[50] Orientation and Microstructure Effects on Susceptibility Reconstruction : a Diffusion Phantom Study , 2010 .
[51] Chunlei Liu. Susceptibility tensor imaging , 2010, Magnetic resonance in medicine.
[52] F Fasano,et al. In vitro and in vivo MR evaluation of internal gradient to assess trabecular bone density , 2010, Physics in medicine and biology.
[53] M L Johns,et al. Nuclear magnetic resonance relaxation and diffusion in the presence of internal gradients: the effect of magnetic field strength. , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.
[54] Maxime Descoteaux,et al. Quantitative evaluation of 10 tractography algorithms on a realistic diffusion MR phantom , 2011, NeuroImage.
[55] C. Meyer,et al. Diffusion coefficient measurement using a temperature‐controlled fluid for quality control in multicenter studies , 2011, Journal of magnetic resonance imaging : JMRI.
[56] Rachid Deriche,et al. Multiple q-shell diffusion propagator imaging , 2011, Medical Image Anal..
[57] B. Stieltjes,et al. Novel spherical phantoms for Q‐ball imaging under in vivo conditions , 2011, Magnetic resonance in medicine.
[58] Xing Qiu,et al. Quantification of accuracy and precision of multi-center DTI measurements: A diffusion phantom and human brain study , 2011, NeuroImage.
[59] Ezequiel Farrher,et al. Novel multisection design of anisotropic diffusion phantoms. , 2012, Magnetic resonance imaging.
[60] Jürgen R. Reichenbach,et al. The future of susceptibility contrast for assessment of anatomy and function , 2012, NeuroImage.
[61] Umberto Sabatini,et al. Potential diagnostic role of the MRI-derived internal magnetic field gradient in calcaneus cancellous bone for evaluating postmenopausal osteoporosis at 3T. , 2013, Bone.
[62] S. Capuani,et al. Microstructural differences between osteoporotic and osteoarthritic femoral cancellous bone: an in vitro magnetic resonance micro-imaging investigation , 2013, Aging Clinical and Experimental Research.
[63] Karla L. Miller,et al. Detecting microstructural properties of white matter based on compartmentalization of magnetic susceptibility , 2013, NeuroImage.
[64] Derek K. Jones,et al. Investigating the prevalence of complex fiber configurations in white matter tissue with diffusion magnetic resonance imaging , 2013, Human brain mapping.
[65] Bram Stieltjes,et al. Investigation of resolution effects using a specialized diffusion tensor phantom , 2014, Magnetic resonance in medicine.
[66] Giulia Di Pietro,et al. Internal Magnetic Field Gradients in Heterogeneous Porous Systems: Comparison Between Spin-Echo and Diffusion Decay Internal Field (DDIF) Method , 2014 .
[67] Yi Wang,et al. Quantitative susceptibility mapping (QSM): Decoding MRI data for a tissue magnetic biomarker , 2014, Magnetic resonance in medicine.
[68] E. Macaluso,et al. New insight into the contrast in diffusional kurtosis images: Does it depend on magnetic susceptibility? , 2015, Magnetic resonance in medicine.
[69] P. Hubbard,et al. Biomimetic phantom for the validation of diffusion magnetic resonance imaging , 2015, Magnetic resonance in medicine.
[70] Ana-Maria Oros-Peusquens,et al. Multistage Background Field Removal (MUBAFIRE)—Compensating for B 0 Distortions at Ultra-High Field , 2015, PloS one.
[71] Natasha Lepore,et al. Fiber estimation and tractography in diffusion MRI: Development of simulated brain images and comparison of multi-fiber analysis methods at clinical b-values , 2015, NeuroImage.
[72] Risto A. Kauppinen,et al. Diffusion-mediated nuclear spin phase decoherence in cylindrically porous materials , 2016, Journal of magnetic resonance.
[73] Paul Strauss,et al. Magnetic Resonance Imaging Physical Principles And Sequence Design , 2016 .
[74] Emiliano Macaluso,et al. The γ-parameter of anomalous diffusion quantified in human brain by MRI depends on local magnetic susceptibility differences , 2017, NeuroImage.
[75] J. Rumble. CRC Handbook of Chemistry and Physics , 2019 .