Abstract: A magnetic resonance imaging system may include: a magnet; gradient coils; an RF pulse transmitter; an RF receiver that receives MR signals from tissue that has been exposed to RF pulses from the RF pulse generator, gradient fields from the gradient coils, and a magnetic field from the magnet; a system controller that controls the magnet, gradient coils, RF pulse transmitter, and RF receiver so as to generate data representative of at least a portion of the composition of an object, including controlling the gradient coils and RF receiver so as to cause MRI data to be acquired that includes information about at least one attribute of the object at different points in time and that represents an incomplete sample of a portion of k-space that is a Fourier transform of the object; and a data processing system that generates one or more images of at least a portion of the object based on the MRI data.

Abstract: Systems and methods for correcting magnetic resonance (MR) data are provided. One method includes receiving the MR data and correcting errors present in the MR data due to non-uniformities in magnetic field gradients used to generate the diffusion weighted MR signals. The method also includes correcting errors present in the MR data due to concomitant gradient fields present in the magnetic field gradients by using one or more gradient terms. At least one of the gradient terms is corrected based on the correction of errors present in the MR data due to the non-uniformities in the magnetic field gradients.

Abstract: Tracer kinetic models are utilized as temporal constraints for highly under-sampled reconstruction of DCE-MRI data. The method is flexible in handling any TK model, does not rely on tuning of regularization parameters, and in comparison to existing compressed sensing approaches, provides robust mapping of TK parameters at high under-sampling rates. In summary, the method greatly improves the robustness and ease-of-use while providing better quality of TK parameter maps than existing methods. In another embodiment, TK parameter maps are directly reconstructed from highly under-sampled DCE-MRI data. This method provides more accurate TK parameter values and higher under-sampling rates. It does not require tuning parameters and there are not additional intermediate steps. The proposed method greatly improves the robustness and ease-of-use while providing better quality of TK parameter maps than conventional indirect methods.

Abstract: A magnetic resonance imaging system may include: a magnet; gradient coils; an RF pulse transmitter; an RF receiver that receives MR signals from tissue that has been exposed to RF pulses from the RF pulse generator, gradient fields from the gradient coils, and a magnetic field from the magnet; a system controller that controls the magnet, gradient coils, RF pulse transmitter, and RF receiver so as to generate data representative of at least a portion of the composition of an object, including controlling the gradient coils and RF receiver so as to cause MRI data to be acquired that includes information about at least one attribute of the object at different points in time and that represents an incomplete sample of a portion of k-space that is a Fourier transform of the object; and a data processing system that generates one or more images of at least a portion of the object based on the MRI data.

Abstract: Systems and methods for correcting magnetic resonance (MR) data are provided. One method includes receiving the MR data and correcting errors present in the MR data due to non-uniformities in magnetic field gradients used to generate the diffusion weighted MR signals. The method also includes correcting errors present in the MR data due to concomitant gradient fields present in the magnetic field gradients by using one or more gradient terms. At least one of the gradient terms is corrected based on the correction of errors present in the MR data due to the non-uniformities in the magnetic field gradients.