Optimization of eddy-current compensation

Vaals, J. J. Van; Bergman, Arieh

doi:10.1016/0022-2364(90)90365-g

Cited by 134 publications

(138 citation statements)

References 17 publications

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“…Active shielding of gradients reduces eddy currents substantially (Bowtell and Mansfield, 1991;Mansfield and Chapman, 1986;Turner et al, 1988) and in combination with effective compensation methods (Boesch et al, 1991;Jehensen et al, 1990;Kickler et al, 2010;Terpstra et al, 1998a;Van Vaals and Bergman, 1990) the eddy current effects can be minimized.…”

Section: Gradient Performancementioning

confidence: 99%

The neurochemical profile quantified by in vivo 1H NMR spectroscopy

et al. 2012

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Section: Gradient Performancementioning

confidence: 99%

The neurochemical profile quantified by in vivo 1H NMR spectroscopy

et al. 2012

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“…Eddy currents can be temporally modeled as the sum of N causal exponential functions (6,15) that are characterized by their amplitudes, ␣ n , and time-constants, n :…”

Section: Theorymentioning

confidence: 99%

Characterization and correction of system delays and eddy currents for MR imaging with ultrashort echo‐time and time‐varying gradients

Atkinson

Thulborn

2009

Magnetic Resonance in Med

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Reconstruction of high-quality MR images requires precise knowledge of the dynamic gradient magnetic fields used to perform spatial encoding. System delays and eddy currents can perturb the gradient fields in both time and space and significantly degrade the image quality for acquisitions with an ultrashort echo time or with rapidly varying readout gradient waveforms. A technique for simultaneously characterizing and correcting the system delay and linear-and zero-order eddy currents of an MR system is proposed. A single set of calibration scans were used to compute a set of system constants that describe the effects of system delays and eddy currents to enable accurate reconstruction of data collected before uncorrected eddy currents have decayed. Accurate MR image formation requires precise control of the gradient magnetic fields to traverse a defined k-space trajectory during data acquisition. System delays and eddy currents can cause the actual trajectory to deviate substantially from the ideal trajectory (1,2). Modern MRI systems include preemphasis hardware for eddy current compensation (3-5) that correct linear (first-order) eddy currents by altering the digital gradient waveform (1) or high-pass filtering the gradient waveform (6) and correct B 0 (zero-order) eddy currents by modulating the receiver phase (5) or using a current-controlled B 0 coil. Because preemphasis systems are limited to a small number of time-constants, it is not uncommon for short-time constant eddy currents to remain even when they are optimally configured. System delays (e.g., amplifier group delay) are typically determined during manufacturing or installation using calibration scans and manual tuning. However, because eddy currents with time-constants shorter than, or comparable to, the echo-time cannot be distinguished from a true delay (1), the measured delay value is more properly termed the apparent system delay.Traditional Cartesian acquisitions are inherently robust to uncorrected delays and short time-constant eddy currents, particularly when the echo-time is long and the data are primarily acquired under a constant gradient amplitude after all uncorrected eddy currents have decayed. These conditions are often met when preemphasis is used to compensate long time-constant eddy currents, enabling high-quality images to be obtained with minor retrospective data corrections. In contrast, acquisitions that use an ultrashort TE (UTE) or traverse complex k-space trajectories using high slew-rate, time-varying readout gradient waveforms (e.g., Twisted Projection Imaging [TPI], 3D Cones) sample data while uncorrected eddy currents are present, distorting the actual k-space path, and may have an undefined center of k-space due to the unknown system delay, leading to significant image degradation (2).A potential solution is to measure the actual k-space trajectories (7-12) and eddy currents (12) and to use them to accurately reconstruct the acquired data. While such measurement approaches work well in principle, all unique gradient w...

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“…To combine the EC parameters corresponding to the diffusion-gradient direction i, we made use of a linear relation between applied diffusion gradient and induced EC-field (11,24,30,31):…”

Section: Ec Field and Distortionsmentioning

confidence: 99%

“…strong gradients used for diffusion encoding (in the following referred to as "diffusion gradients") create ECs in the conductive parts of the magnet, causing geometric distortions in the DW images that depend on the amplitude and direction of the diffusion gradients (11)(12)(13)(14). The EC effects depend on the pulse sequence (15)(16)(17)(18), scanner calibration, and scanner design.…”

mentioning

confidence: 99%

Correcting eddy current and motion effects by affine whole‐brain registrations: Evaluation of three‐dimensional distortions and comparison with slicewise correction

Mohammadi

Möller

Kugel

et al. 2010

Magnetic Resonance in Med

134

142

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Eddy-current (EC) and motion effects in diffusion-tensor imaging (DTI) bias the estimation of quantitative diffusion indices, such as the fractional anisotropy. Both effects can be retrospectively corrected by registering the strongly distorted diffusion-weighted images to less-distorted T2-weighted images acquired without diffusion weighting. Two different affine spatial transformations are usually employed for this correction: slicewise and whole-brain transformations. However, a relation between estimated transformation parameters and EC distortions has not been established yet for the latter approach. In this study, a novel diffusion-gradient-direction-independent estimation of the EC field is proposed based solely on affine whole-brain registration parameters. Using this model, it is demonstrated that a more distinct evaluation of the wholebrain EC effects is possible if the through-plane distortion was considered in addition to the well-known in-plane distortions. Moreover, a comparison of different whole-brain registrations relative to a slicewise approach is performed, in terms of the relative tensor error. Our findings suggest that for appropriate intersubject comparison of DTI data, a whole-brain registration containing nine affine parameters provides comparable performance (between 0 and 3%) to slicewise methods and can be performed in a fraction of the time.Magn strong gradients used for diffusion encoding (in the following referred to as "diffusion gradients") create ECs in the conductive parts of the magnet, causing geometric distortions in the DW images that depend on the amplitude and direction of the diffusion gradients (11-14). The EC effects depend on the pulse sequence (15-18), scanner calibration, and scanner design. The EC and motion effects can be retrospectively corrected by registering the strongly distorted DW images to the less distorted images acquired without diffusion weighting (14,19). However, the EC effects cannot be completely corrected by retrospective registration. Thus, after retrospective EC correction residual image artifacts (e.g., image blurring caused by the time-dependent components of the EC field) will remain and reduce the comparability of DTI data. This is particularly important for longitudinal DTI studies, during which the scanner adjustment and, thus, the EC effects might vary.One possibility for assessing the comparability of DTI data is to quantify EC effects by estimating the induced EC field. Rohde et al. (20) presented a new registration approach for EC and motion correction, using a whole-brain transformation. They showed that the EC field induced by one diffusion gradient can be retrospectively estimated from the transformation parameters of a 14-parameter, nonlinear transformation that corrects the distortions of the corresponding DW image. The DTI data, however, consists of at least six DW images, each corresponding to different diffusion directions and containing EC distortions that are corrected by a specific set of EC parameters. Each respective set ...

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Optimization of eddy-current compensation

Cited by 134 publications

References 17 publications

The neurochemical profile quantified by in vivo 1H NMR spectroscopy

The neurochemical profile quantified by in vivo 1H NMR spectroscopy

Characterization and correction of system delays and eddy currents for MR imaging with ultrashort echo‐time and time‐varying gradients

Correcting eddy current and motion effects by affine whole‐brain registrations: Evaluation of three‐dimensional distortions and comparison with slicewise correction

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