Imaging in the presence of nonlinear static and gradient magnetic fields is outlined. Analytic expressions are provided for the signal obtained using specific magnetic resonance imaging (MRI) sequences with the addition of field nonlinearities. We show that using nonlinear Fourier transform image reconstruction, high-quality images can be obtained for the case when the static magnetic field has large peak-to-peak error, and the gradient field exhibits variations beyond currently acceptable levels over the imaging field-of-view. Our results show that MRI can be performed in nonlinear magnetic fields, provided that a versatile technique is used to reconstruct the images
The theory and techniques of NMR imaging are described together with a detailed description of the F...
Abstract — In magnetic resonance imaging (MRI), the spatial inhomogeneity of the static magnetic fie...
The magnetic gradient fields used in magnetic resonance imaging (MRI) have a component which is para...
Within the past few decades magnetic resonance imaging has become one of the most important imaging ...
Spatial encoding in MR techniques is achieved by sampling the signal as a function of time in the pr...
International audienceWe present a method to correct intensity variations and voxel shifts caused by...
Abstract—In magnetic resonance imaging, spatial localization is usually achieved using Fourier encod...
Purpose: Nonlinear spatial encoding magnetic fields result inan inhomogeneous image resolution. With...
Nonlinear spatial encoding fields for magnetic resonance imaging (MRI) hold great promise to improve...
Reconstruction of MRI data is based on exact knowledge of all magnetic field dynamics, since the int...
In parallel MRI, the acquisition of data from multiple receive coils allows for the undersampling o...
Magnetic resonance imaging (MRI) in very low fields is fundamentally limited by untruncated concomi...
The classic paradigm for MRI requires a homogeneous B 0 field in combination with linear encoding gr...
Due to engineering limitations, the spatial encoding gradient fields in conventional magnetic resona...
Quantitative Magnetic Resonance Imaging (MRI) is based on a two-steps approach: estimation of the ma...
The theory and techniques of NMR imaging are described together with a detailed description of the F...
Abstract — In magnetic resonance imaging (MRI), the spatial inhomogeneity of the static magnetic fie...
The magnetic gradient fields used in magnetic resonance imaging (MRI) have a component which is para...
Within the past few decades magnetic resonance imaging has become one of the most important imaging ...
Spatial encoding in MR techniques is achieved by sampling the signal as a function of time in the pr...
International audienceWe present a method to correct intensity variations and voxel shifts caused by...
Abstract—In magnetic resonance imaging, spatial localization is usually achieved using Fourier encod...
Purpose: Nonlinear spatial encoding magnetic fields result inan inhomogeneous image resolution. With...
Nonlinear spatial encoding fields for magnetic resonance imaging (MRI) hold great promise to improve...
Reconstruction of MRI data is based on exact knowledge of all magnetic field dynamics, since the int...
In parallel MRI, the acquisition of data from multiple receive coils allows for the undersampling o...
Magnetic resonance imaging (MRI) in very low fields is fundamentally limited by untruncated concomi...
The classic paradigm for MRI requires a homogeneous B 0 field in combination with linear encoding gr...
Due to engineering limitations, the spatial encoding gradient fields in conventional magnetic resona...
Quantitative Magnetic Resonance Imaging (MRI) is based on a two-steps approach: estimation of the ma...
The theory and techniques of NMR imaging are described together with a detailed description of the F...
Abstract — In magnetic resonance imaging (MRI), the spatial inhomogeneity of the static magnetic fie...
The magnetic gradient fields used in magnetic resonance imaging (MRI) have a component which is para...