Systems, methods, and computer program products for determining different states of a contrast agent in different types of tissue can involve generating a magnetic resonance waveform for the contrast agent in an examination region that includes multiple tissue types. The contrast agent may have different relaxation-shortening effects in each different tissue type. The generated waveform may be compared to database waveforms to determine the concentration of the contrast agent in each tissue type in the examination region.

An inventive computer-implemented method for creating correction data, which corrects measurement data missing in a measurement dataset recorded using a partial Fourier technique (PF technique), i.e. measurement data which was not recorded even though this is required in accordance with Nyquist for a complete measurement dataset, may include: receiving input data created on the basis of measurement data in the measurement dataset, applying at least one trained correction function to the input data to determine output data, and providing the output data. The output data may include correction information that corrects measurement data missing in the measurement dataset.

Super-resolution processing is performed on an MRI image by using an NMR signal as a point spread function (PSF) . Image processing of increasing a resolution is performed on a reconstructed image by using the point spread function. The point spread function is a signal obtained by, after a phantom disposed in an imaging space is irradiated with a high-frequency magnetic field, acquiring a nuclear magnetic resonance signal from the phantom without applying frequency encoding and phase encoding, and performing Fourier transform on the acquired nuclear magnetic resonance signal.

Super-resolution processing is performed on an MRI image by using an NMR signal as a point spread function (PSF) . Image processing of increasing a resolution is performed on a reconstructed image by using the point spread function. The point spread function is a signal obtained by, after a phantom disposed in an imaging space is irradiated with a high-frequency magnetic field, acquiring a nuclear magnetic resonance signal from the phantom without applying frequency encoding and phase encoding, and performing Fourier transform on the acquired nuclear magnetic resonance signal.

Systems and methods for performing ungated magnetic resonance imaging are disclosed herein. A method includes producing magnetic resonance image MRI data by scanning a target in a low magnetic field with a pulse sequence having a spiral trajectory; sampling k-space data from respective scans in the low magnetic field and receiving at least one field map data acquisition and a series of MRI data acquisitions from the respective scans; forming a field map and multiple sensitivity maps in image space from the field map data acquisition; forming target k-space data with the series of MRI data acquisitions; forming initial magnetic resonance images in the image domain by applying a Non-Uniform Fast Fourier Transform to the target k-space data; and forming reconstructed images with a low rank plus sparse (L+S) reconstruction algorithm applied to the initial magnetic resonance images.

A method for multi-dimensional, relaxation-diffusion magnetic resonance fingerprinting (MRF) includes performing, using a magnetic resonance imaging (MRI) system, a pulse sequence that integrates free-waveform b-tensor diffusion encoding into a magnet resonance fingerprinting pulse sequence to perform a multi-dimensional, relaxation-diffusion encoding while acquiring MRF signal evolutions, processing, using a processor, the acquired MRF signal evolutions to determine at least one relaxation parameter and at least one diffusivity parameter, and generating, using the processor, a report including at least one of the at least one relaxation parameter and the at least diffusivity parameter.

Automated processing and radiomic analysis of magnetic resonance imaging (“MRI”), such as multi-contrast MR images, and magnetic resonance fingerprinting (“MRF”) data, such as quantitative parameter maps, are integrated into a single workflow.

During operation, a computer system may acquire magnetic resonance (MR) signals associated with a sample from a measurement device or memory. Then, the computer system may access a predetermined set of coil magnetic field basis vectors associated with a surface surrounding the sample, where coil sensitivities of coils in the measurement device are represented by weighted superpositions of the predetermined set of coil magnetic field basis vectors using coefficients, and where the predetermined coil magnetic field basis vectors are solutions to Maxwell's equations. Next, the computer system may solve, on a voxel-by-voxel basis for voxels associated with the sample, a nonlinear optimization problem for MR information associated with the sample and the coefficients using: a forward model that uses the MR information as inputs and simulates response physics of the sample, the MR signals and the predetermined set of coil magnetic field basis vectors.

Systems and methods are provided for susceptibility contrast imaging of nanoparticles at low magnetic fields. A susceptibility-based MRI technique, such as imaging with a balanced steady-state free precession (bSSFP) pulse sequence, may be used for imaging a contrast agent such as biocompatible superparamagnetic nanoparticles at ultra-low fields. The contrast agent and imaging technique may be used to improving the visibility of anatomical structures and detecting diseases, such as cancer, with low-field MRI.

A computer system that performs a sparsity technique is described. During operation, the computer system accesses or obtains information associated with non-invasive measurements performed on at least an individual, historical non-invasive measurements, and a dictionary of predetermined features or basis functions associated with the historical non-invasive measurements. Note that the non-invasive measurements and the historical non-invasive measurements may include or correspond to magnetic resonance (MR) measurements. For example, the MR measurements may include magnetic resonance imaging (MRI) scans. Then, the computer system updates the dictionary of predetermined features based at least in part on the non-invasive measurements and the historical non-invasive measurements, where the updating includes performing a minimization technique with a cost function having an L2-norm term and an L0-norm term. Next, the computer system determines weights associated with features in the updated dictionary of predetermined features based at least in part on the non-invasive measurements.