ArticleProceedings of SPIE--the International Society for Optical Engineering2018
Phantom-based field maps for gradient nonlinearity correction in diffusion imaging.
Article in Proceedings of SPIE--the International Society for Optical Engineering, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- MRI-based 3D estimation of skeletal muscle architecture and strain during contraction.Journal of biomechanics · 2026Article
- Is correction for gradient nonlinearity necessary in a brain diffusion tensor MRI clinical study?PloS one · 2026Article
- Article
- Efficient approximate signal reconstruction for correction of gradient nonlinearities in diffusion-weighted imaging.Magnetic resonance imaging · 2023Article
- Mapping the impact of nonlinear gradient fields with noise on diffusion MRI.Magnetic resonance imaging · 2023Article
- Mapping the Impact of Approximate Gradient Nonlinearity Fields Correction on Tractography.Proceedings of SPIE--the International Society for Optical Engineering · 2023Article
- Mapping gradient nonlinearity and miscalibration using diffusion-weighted MR images of a uniform isotropic phantom.Magnetic resonance in medicine · 2021Article
- Empirical field mapping for gradient nonlinearity correction of multi-site diffusion weighted MRI.Magnetic resonance imaging · 2021Article
- The effect of gradient nonlinearities on fiber orientation estimates from spherical deconvolution of diffusion magnetic resonance imaging data.Human brain mapping · 2021Article
- Consideration of Cerebrospinal Fluid Intensity Variation in Diffusion Weighted MRI.Proceedings of SPIE--the International Society for Optical Engineering · 2019Article
- Mapping the Impact of Non-Linear Gradient Fields on Diffusion MRI Tensor Estimation.Proceedings of SPIE--the International Society for Optical EngineeringArticle
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Authors and funding
9 authors.
Funding
Abstract
Gradient coils in magnetic resonance imaging do not produce perfectly linear gradient fields. For diffusion imaging, the field nonlinearities cause the amplitude and direction of the applied diffusion gradients to vary over the field of view. This leads to site- and scan-specific systematic errors in estimated diffusion parameters such as diffusivity and anisotropy, reducing reliability especially in studies that take place over multiple sites. These errors can be substantially reduced if the actual scanner-specific gradient coil magnetic fields are known. The nonlinearity of the coil fields is measured by scanner manufacturers and used internally for geometric corrections, but obtaining and using the information for a specific scanner may be impractical for many sites that operate without special-purpose local engineering and research support. We have implemented an empirical field-mapping procedure using a large phantom combined with a solid harmonic approximation to the coil fields that is simple to perform and apply. Here we describe the accuracy and precision of the approach in reproducing manufacturer gold standard field maps and in reducing spatially varying errors in quantitative diffusion imaging for a specific scanner. Before correction, median B value error ranged from 33 - 41 relative to manufacturer specification at 100 mm from isocenter; correction reduced this to 0 - 4. On-axis spatial variation in the estimated mean diffusivity of an isotropic phantom was 2.2% - 4.1% within 60 mm of isocenter before correction, 0.5% - 1.6% after. Expected fractional anisotropy in the phantom was 0; highest estimated fractional anisotropy within 60 mm of isocenter was reduced from 0.024 to 0.012 in the phase encoding direction (48% reduction) and from 0.020 to 0.006 in the frequency encoding direction (72% reduction).
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