Supplementary material to "Nuclear spin noise tomography in three dimensions"

Author(s):  
Stephan J. Ginthör ◽  
Judith Schlagnitweit ◽  
Matthias Bechmann ◽  
Norbert Müller
2020 ◽  
Vol 1 (2) ◽  
pp. 165-173
Author(s):  
Stephan J. Ginthör ◽  
Judith Schlagnitweit ◽  
Matthias Bechmann ◽  
Norbert Müller

Abstract. We report three-dimensional spin noise imaging (SNI) of nuclear spin density from spin noise data acquired by Faraday detection. Our approach substantially extends and improves the two-dimensional SNI method for excitation-less magnetic resonance tomography reported earlier (Müller and Jerschow, 2006). This proof of principle was achieved by taking advantage of the particular continuous nature of spin noise acquired in the presence of constant magnitude magnetic field gradients and recent advances in nuclear spin noise spectroscopy acquisition as well as novel processing techniques. In this type of projection–reconstruction-based spin noise imaging the trade-off between signal-to-noise ratio (or image contrast) and resolution can be adjusted a posteriori during processing of the original time-domain data by iterative image reconstruction in a unique way not possible in conventional rf-pulse-dependent magnetic resonance imaging (MRI). The 3D SNI is demonstrated as a proof of concept on a commercial 700 MHz high-resolution NMR spectrometer, using a 3D-printed polymeric phantom immersed in water.


2020 ◽  
Author(s):  
Stephan J. Ginthör ◽  
Judith Schlagnitweit ◽  
Matthias Bechmann ◽  
Norbert Müller

Abstract. We report three-dimensional spin noise imaging (SNI) of nuclear spin density from spin noise data acquired by Faraday detection. Our approach substantially extends and improves the two-dimensional SNI method for excitation-less magnetic resonance tomography reported earlier. (Müller, N. and Jerschow, A.: Nuclear spin noise imaging, Proc. Natl. Acad. Sci. U.S.A., 103(18), 6790–6792, doi:10.1073/pnas.0601743103, 2006.) This proof of principle was achieved by taking advantage of the particular continuous nature of spin noise acquired in the presence of constant magnitude magnetic field gradients and recent advances in nuclear spin noise spectroscopy acquisition as well as novel processing techniques. In this type of projection-reconstruction based spin noise imaging the trade-off between signal-to-noise ratio (or image contrast) and resolution can be adjusted a posteriori during processing of the original time domain data by iterative image reconstruction in a unique way not possible in conventional rf-pulse dependent MRI. The 3D SNI is demonstrated as a proof of concept on a commercial 700 MHz high resolution NMR spectrometer, using a 3D-printed polymeric phantom immersed in water.


2009 ◽  
Vol 121 (24) ◽  
pp. 4405-4407 ◽  
Author(s):  
Hervé Desvaux ◽  
Denis J. Y. Marion ◽  
Gaspard Huber ◽  
Patrick Berthault

2015 ◽  
Vol 143 (9) ◽  
pp. 094201 ◽  
Author(s):  
Guillaume Ferrand ◽  
Gaspard Huber ◽  
Michel Luong ◽  
Hervé Desvaux
Keyword(s):  

2015 ◽  
Vol 92 (16) ◽  
Author(s):  
Wen-Long Ma ◽  
Gary Wolfowicz ◽  
Shu-Shen Li ◽  
John J. L. Morton ◽  
Ren-Bao Liu
Keyword(s):  

2009 ◽  
Vol 48 (24) ◽  
pp. 4341-4343 ◽  
Author(s):  
Hervé Desvaux ◽  
Denis J. Y. Marion ◽  
Gaspard Huber ◽  
Patrick Berthault

Author(s):  
Norbert Müller ◽  
Alexej Jerschow ◽  
Judith Schlagnitweit
Keyword(s):  

2022 ◽  
Vol 64 (2) ◽  
pp. 206
Author(s):  
А.В. Шумилин ◽  
Д.С. Смирнов

We consider the central spin model in the box approximation taking into account an external magnetic field and the anisotropy of the hyperfine interaction. From the exact Hamiltonian diagonalization we obtain analytical expressions for the nuclear spin dynamics in the limit of many nuclear spins. We predict the nuclear spin precession in zero magnetic field for the case of the anisotropic interaction between electron and nuclear spins. We calculate and describe the nuclear spin noise spectra in the thermodynamic equilibrium. The obtained results can be used for the analysis of the nuclear spin induced current fluctuations in organic semiconductors.


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