Efficient concomitant and remanence field artifact reduction in ultra‐low‐field MRI using a frequency‐space formulation

Hsu, Yi‐Cheng; Vesanen, Panu T.; Nieminen, Jaakko O.; Zevenhoven, Koos C. J.; Dabek, Juhani; Parkkonen, Lauri; Chern, I‐Liang; Ilmoniemi, Risto J.; Lin, Fa‐Hsuan

doi:10.1002/mrm.24745

Cited by 6 publications

(11 citation statements)

References 28 publications

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“…For detecting distortions in incorrectly reconstructed images, we fitted the quadratic mapping [Eq. (21)] with 18 additional coefficients. The error statistics are shown in Figs.…”

Section: Resultsmentioning

confidence: 99%

Automatic Spatial Calibration of Ultra-Low-Field MRI for High-Accuracy Hybrid MEG–MRI

Mäkinen

Zevenhoven

Ilmoniemi

2019

IEEE Trans. Med. Imaging

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With a hybrid MEG-MRI device that uses the same sensors for both modalities, the co-registration of MRI and MEG data can be replaced by an automatic calibration step. Based on the highly accurate signal model of ultra-low-field (ULF) MRI, we introduce a calibration method that eliminates the error sources of traditional co-registration. The signal model includes complex sensitivity profiles of the superconducting pickup coils. In ULF MRI, the profiles are independent of the sample and therefore well-defined. In the most basic form, the spatial information of the profiles, captured in parallel ULF-MR acquisitions, is used to find the exact coordinate transformation required. We assessed our calibration method by simulations assuming a helmetshaped pickup-coil-array geometry. Using a carefully constructed objective function and sufficient approximations, even with low-SNR images, sub-voxel and sub-millimeter calibration accuracy was achieved. After the calibration, distortion-free MRI and high spatial accuracy for MEG source localization can be achieved. For an accurate sensor-array geometry, the co-registration and associated errors are eliminated, and the positional error can be reduced to a negligible level.

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“…For detecting distortions in incorrectly reconstructed images, we fitted the quadratic mapping [Eq. (21)] with 18 additional coefficients. The error statistics are shown in Figs.…”

Section: Resultsmentioning

confidence: 99%

Automatic Spatial Calibration of Ultra-Low-Field MRI for High-Accuracy Hybrid MEG–MRI

Mäkinen

Zevenhoven

Ilmoniemi

2019

IEEE Trans. Med. Imaging

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“…In RSA, we reduced concomitant field artifacts by explicitly describing the relationship between magnetization and measured signal under imaging gradient fields and concomitant field (14,15). There are other approaches to minimize the concomitant field artifacts.…”

Section: Discussionmentioning

confidence: 99%

“…Note that the magnetization precession frequency xðx; zÞ depends on the spatial distribution of the magnetic field strength b(x, z): xðx; zÞ ¼ g b ðx; zÞ, where c is the gyromagnetic ratio. According to Maxwell's equations, a linear magnetic field in the z direction generated by gradient coils must have nonzero x and y field components (13)(14)(15). In fact, this physical principle causes significant concomitant-field artifacts in low-field and ULF MRI (13)(14)(15).…”

Section: Theorymentioning

confidence: 99%

“…Accordingly, if image reconstruction can explicitly incorporate the field distribution, the blurring arising from concomitant fields can be reduced significantly. Different from conventional ULF MRI, in which both frequency and phase encoding are used to produce an image, RSA requires no phase encoding, thus simplifying the image reconstruction without the necessity of considering highly nonlinear phase increments across phase-encoding steps because of different precession axes, precession frequencies, and initial angles (15). The absence of phase encoding also allows acquisition very soon after the prepolarizing pulse, before significant T 2 decay has taken place.…”

Section: Comparison Of Rsa and Radial Trajectory Acquisitionmentioning

confidence: 99%

“…This feature also suggests that RSA, like radial-trajectory acquisition, can have better quality using fewer data samples than Cartesian trajectory acquisition (12). Different from the radial-trajectory acquisition, where careful measurement of the concomitant field across rotation angles and complicated postprocessing methods (13)(14)(15) are needed to reduce image blurring and distortion artifacts in ULF MRI, RSA can reduce the image distortion and blurring caused by the concomitant field without tedious calibration measurements, because concomitant fields do not change between rotation angles in RSA. Using empirical data, we demonstrate that RSA can generate a full-FOV image using 33% of the amount of data collected by the conventional Fourier encoding method with only three localized SQUID sensors.…”

Section: Introductionmentioning

confidence: 99%

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Rotary scanning acquisition in ultra‐low‐field MRI

Hsu

Zevenhoven

Chu

et al. 2015

Magnetic Resonance in Med

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Rapid calculation of static magnetic field perturbation generated by magnetized objects in arbitrary orientations

Yeo

Lee

2021

Magnetic Resonance in Med

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Purpose Most previous work on the calculation of susceptibility‐induced static magnetic field (B0) inhomogeneity has considered strictly unidirectional magnetic fields. Here, we present the theory and implementation of a computational method to rapidly calculate static magnetic field vectors produced by an arbitrary distribution of voxelated magnetization vectors. Theory and Methods Two existing B0 calculation methods were systematically extended to include arbitrary orientations of the magnetization and the magnetic field; they are (1) Fourier‐domain convolution with k‐space‐discretized (KD) dipolar field, and (2) generalized susceptibility voxel convolution (gSVC). The methods were tested on an analytical ellipsoid model and a tilted human head model, as well as against experimentally measured B0 fields induced by a stainless‐steel implant located in an inhomogeneous region of a clinical 3T MRI magnet. Results Both methods were capable of correctly calculating B0 fields inside a magnetized ellipsoid in all tested orientations. The KD method generally required a larger grid and longer computation time to achieve accuracy comparable to gSVC. Measured B0 fields due to the implant showed a good match with the gSVC‐calculated fields that accounted for the spatial variation of the applied magnetic field including the radial components. Conclusion Our method can provide a reliable and efficient computational tool to calculate B0 perturbation by magnetized objects under a variety of circumstances, including those with inhomogeneous magnetizing fields, anisotropic susceptibility, and a rotated coordinate system.

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Efficient concomitant and remanence field artifact reduction in ultra‐low‐field MRI using a frequency‐space formulation

Abstract: We present this method together with numerical simulations and experimental data to demonstrate how concomitant and remanence field artifacts in ultra-low-field MRI can be corrected efficiently.

Cited by 6 publications

References 28 publications

Automatic Spatial Calibration of Ultra-Low-Field MRI for High-Accuracy Hybrid MEG–MRI

Automatic Spatial Calibration of Ultra-Low-Field MRI for High-Accuracy Hybrid MEG–MRI

Rotary scanning acquisition in ultra‐low‐field MRI

Rapid calculation of static magnetic field perturbation generated by magnetized objects in arbitrary orientations

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