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.

Radiomic analysis of multiparametric magnetic resonance imaging (“MRI”) and magnetic resonance fingerprinting (“MRF”) data enhances delineation and mapping of tumor regions. Radiomic features are extracted from MRI and MRF tumor images. Distinct tumor regions, including but not limited to necrotic core, enhancing tumor, and peritumoral white matter, are segmented and mapped. Whole tumor as well as tumor region characteristics are evaluated. Tumors can also be differentiated and classified by pathology, grading, staging, and so on. Tumor infiltration into peritumoral white matter regions can also be mapped for recurrence prediction

The present disclosure relates to: a method for evaluating a state of a motor function of a patient who has or is suspected of having brain damage by using parameters obtained from a diffusion weighted image of the patient's brain; a program for executing the method in a computer; and an image processing device and an MRI device which can be used in practicing the method. According to the present disclosure, the motor function state of a patient who has or is suspected of having brain damage can be evaluated, and it is also possible to predict the recovery of the motor function after regeneration treatment. Accordingly, whether the patient is suitable for the regeneration treatment can be determined before the start of the treatment.

One or more tractograms of a global tractography of a tissue of interest are determined. At least one instance of diffusion magnetic resonance imaging data of the tissue of interest is obtained. A trained machine-learning algorithm generates the one or more tractograms based on the at least one instance of the diffusion magnetic resonance imaging data.

A method for creating calibration data for processing accelerated measurement data of an object to be examined using a magnetic resonance system. The method includes recording measurement data sets using an acquisition acceleration method, recording calibration data sets, and determining processed measurement data sets from the accelerated measurement data sets using the calibration data sets so that effects of the acquisition acceleration method used are eliminated in the processed measurement data sets. The recording of the calibration data sets includes an application of at least one attenuation method for attenuating signals causing phase errors.

In a method for avoiding artifacts during acquisition of MR data, a first measurement data set (MDS) of a target region of the examination object and at least one second MDS of the target region are acquired, and a combined MDS is created based on the acquired data sets. The first MDS does not sample a first region of k-space to be sampled according to Nyquist and corresponding to a first partial factor, and a second MDS does not sample a second region of k-space to be sampled according to Nyquist and corresponding to a second partial factor. The first and second regions of the k-space are different from each other. Advantageously, a k-space region acquired in none of the acquisitions made can be minimized by the inventive variation in the respective sampling pattern of the acquired MDS, so artifacts are reduced/avoided in MR images reconstructed from the MDS.

A computer-implemented method and system includes accessing neurophysiological and neurovascular data recorded during sleep. A function mapping is executed from said neurophysiological and neurovascular data to a target that is one of a glymphatic flow marker, a molecular analysis marker of neurodegeneration, or a neuroimaging marker of neurodegeneration. A target prediction model is output based on the function mapping. The target prediction model can receive new neurophysiological and neurovascular data and output a predicted marker of neurodegeneration.

A computer-implemented method and system includes accessing neurophysiological and neurovascular data recorded during sleep. A function mapping is executed from said neurophysiological and neurovascular data to a target that is one of a glymphatic flow marker, a molecular analysis marker of neurodegeneration, or a neuroimaging marker of neurodegeneration. A target prediction model is output based on the function mapping. The target prediction model can receive new neurophysiological and neurovascular data and output a predicted marker of neurodegeneration.

A method for 3D oscillating-gradient prepared gradient spin-echo imaging and a device. The imaging method comprises the following steps: first, using a global saturation module to destroy previous residual transverse magnetization; second, embedding a pair of trapezoidal cosine oscillating gradients into a 90°.sub.x-180°.sub.y-90°.sub.−x radiofrequency pulse by a diffusion encoding module, to separate diffusion encoding from signal acquisition; then, using a fat saturation module to suppress a fat signal; finally, acquiring a signal by means of gradient spin-echo readout, and correcting phase errors among multiple excitations by multiplexed sensitivity-encoding reconstruction. Compared with a 2D plane echo-based oscillating gradient diffusion sequence used on a 3T clinical system, a 3D oscillating-gradient prepared gradient spin-echo sequence effectively reduces the imaging time, improves the signal to noise ratio, and is beneficial to clinical transformation of time-dependent diffusion MRI technology

A method for generating a magnetic resonance image includes providing MR segment data records, wherein each MR segment data record has N×M frequency voxels in k-space. To reduce the acquisition time during MR segment recordings, the amount of MR data is reduced by incompletely sampling the k-space during a recording. The missing data of the MR segment data records are reconstructed twice: Preliminarily reconstructed MR segment data records are calculated first, with a reconstruction kernel obtained from reference data. Modified reference images containing phase information are obtained by creating phase images from the preliminarily reconstructed MR segment data records and combining these phase images with the absolute value of the reference image generated from the reference data. The second reconstruction kernels are ascertained therefrom in turn. In contrast to the first reconstruction kernel, these contain phase information, such that the missing data can be reconstructed without phase artifacts.