Abstract: Techniques are disclosed for generating a quantitative parameter map from MR data. A specified signal model is adjusted to measured MR data. The signal model contains a time-dependent phase evolution map that specifies a respective separate phase evolution for each echo in a multi-echo sequence used to generate the MR data. Provision is also made for an image region that is to be represented to be divided up into a plurality of pixel fields, which include a plurality of pixels in each case. For all these pixel fields, at least the phase evolution for each echo is assumed to be equal for all the pixels in the respective pixel field, so as to achieve stability of the adjustment of the signal model to the MR data.

Abstract: In a method for generation of a homogenization field suitable for homogenization of magnetic resonance data of an examination object, first magnetic resonance data from an examination region of the examination object is provided, a trained function is provided, a homogenization field is extracted by processing the first magnetic resonance data by way of the trained function, and the homogenization field is provided.

Abstract: A method for generating a homogenization field for image data having image elements imaging an examination region may include: selecting a first image element comprising at least two first intensity values for a first positional value; smoothing image data surrounding the first image element in respect of the at least one spatial dimension to generate first smoothed image data; applying a robust estimation method to the first smoothed image data in respect of the statistical dimension to generate robustly estimated image data; and determining the homogenization field for the first positional value based on the robustly estimated image data. The examination region may be defined by positional values in at least one spatial dimension. The one image element in each case for one positional value in each case in the spatial dimension may include at least two intensity values in a statistical dimension.

Abstract: A method for acquiring magnetic resonance imaging data with respiratory motion compensation using one or more motion signals includes acquiring a plurality of gradient-delay-corrected radial readout views of a subject using a free-breathing multi-echo pulse sequence, and sampling a plurality of data points of the gradient-delay-corrected radial readout views to yield a self-gating signal. The self-gating signal is used to determine a plurality of respiratory motion states corresponding to the plurality of gradient-delay-corrected radial readout views. The respiratory motion states are used to correct respiratory motion bias in the gradient-delay-corrected radial readout views, thereby yielding gradient-delay-corrected and motion-compensated multi-echo data. One or more images are reconstructed using the gradient-delay-corrected and motion-compensated multi-echo data.

Abstract: A method of generating biomarker parameters includes acquiring imaging data depicting a patient using a MRI system. The imaging data is acquired for a plurality of contrasts resulting from application of a pulse on the patient's anatomy. A process is executed to generate a MoCoAve image for each contrast. This process includes dividing the imaging data for the contrast into bins corresponding to one of a plurality of respiratory motion phases, and reconstructing the imaging data in each bin to yield bin images. The process further includes selecting a reference bin image from the bin images, and warping the bin images based on the reference bin image. The warped bin images and the reference bin image are averaged to generate the MoCoAve image for the contrast. One or more biomarker parameter maps are calculated based on the MoCoAve images generated for the contrasts.

Abstract: A method for using a multi-echo magnetic resonance imaging (MRI) simultaneously quantify T1 and fat fraction in an anatomical region of interest includes performing a radial single shot multi-echo acquisition of the anatomical region of interest. The radial single shot multi-echo acquisition comprises applying a preparation pulse to invert longitudinal magnetization of the anatomical region of interest, and acquiring a plurality of radial readouts at different echo times (TE). A magnetization recovery curve is continuously sampled using the plurality of radial readouts to yield a plurality of radial spokes. The radial spokes for each TE are ground together to generate under-sampled k-space data for each TE. The under-sampled k-space data is reconstructed into a plurality of multi-echo images corresponding to the different echo times. One or more fitting algorithms are applied to the multi-echo images to generate a water-only T1 map and a proton density fat fraction (PDFF) measurement.

Abstract: In a magnetic resonance method and apparatus for the quantitative spatially resolved determination of a physiological tissue parameter of an examination subject, a signal model is determined with m different signal parameters that influence an MR signal of the subject. N different MR images of the subject are recorded with m?N, and measured data tuples with N measured values are determined from the N MR images. A lookup table is created with multiple table entries, which each assigns an N-dimensional tuple of t synthesized measured values, which were calculated using the signal model, to an m-dimensional tuple of signal parameters. The lookup table is pre-processed into a sorted lookup table, and at least some of the signal parameters are determined by comparing the pixel-by-pixel measured data tuples with N dimensional tuples of the synthesized measured values in the sorted lookup table for at least some of the pixels.

Abstract: The disclosure relates to techniques for automatically characterizing liver tissue of a patient, comprising receiving morphological magnetic resonance image data set and at least one magnetic resonance parameter map of an imaging region comprising at least partially the liver of the patient, each acquired by a magnetic resonance imaging device, via a first interface. The techniques further include applying a trained function comprising a neural network to input data comprising at least the image data set and the parameter map. At least one tissue score describing the liver tissue is generated as output data, which is provided using a second interface.

Abstract: A method for multi-point magnetic resonance imaging including: receiving measured magnetic resonance data, which maps the magnetizations of a number of spin species in a measuring range with a number of echo times; carrying out an optimization for determining fitted magnetic resonance data on the basis of the measured magnetic resonance data, wherein an optimization function of the optimization implements a penalty for a higher rank of a matrix representing the fitted magnetic resonance data and a correction term for the localized evolution of a phase of the measured magnetic resonance data by means of field inhomogeneities or by means of a counterrotation of gradient fields with the number of echo times; and applying a spectral model to the fitted magnetic resonance data to determine magnetic resonance images with contrasts which correspond to the number of spin species.

Abstract: In a method for determining the T1 time and also of at least one tissue proportion per voxel in a predetermined volume segment of an examination object with a magnetic resonance (MR) sequence: a radio frequency (RF) preparation pulse is radiated in; a readout module is repeatedly run after the RF preparation pulse to acquire MR data; and the T1 time and the at least one tissue proportion per voxel is determined as a function of the MR data. The readout module can include: an RF excitation pulse at a beginning of the readout module, a phase encoding gradient, and a number of readout gradients (3a-3g) for acquiring the MR data. During running of the readout module, the MR data may be acquired, at least at times, with more than two echoes.

Abstract: In a computer-implemented method of training a machine learning based processor, the processor can be trained to derive image data from signal data sets of multiple spin echo sequences. The trained processor can be configured to perform image processing for Magnetic Resonance Imaging (MRI) to derive the image data.

Abstract: A method for estimating a coil sensitivity map for a magnetic resonance (MR) image includes providing a matrix A of sliding blocks of a 3D image of coil calibration data, calculating a left singular matrix V? from a singular value decomposition of A corresponding to ? leading singular values, calculating P=V?V?H, calculating a matrix that is an inverse Fourier transform of a zero-padded matrix P, and solving MHcr=(Sr)Hcr for cr, where cr is a vector of coil sensitivity maps for all coils at spatial location r, and M = ( ( 1 1 … 1 0 0 … 0 … … … 0 0 … 0 ) ? ( 0 0 … 0 1 1 … 1 … … … 0 0 … 0 ) ? ? … ? ? ( 0 0 … 0 0 0 … 0 … … … 1 1 … 1 ) ) .

Abstract: In a method for filtering magnetic resonance (MR) image data, complex MR image data is acquired from a region to be imaged, and a sliding window averaging is applied to the complex MR image data to generate filtered MR image data. For each window position of the sliding window averaging: a phase variation of the complex MR image data of individual image points of a sliding window is estimated with a model using a linear phase progression, and filtered complex MR image data is generated based on the estimated phase variation of the complex MR image data. The generation of the filtered complex MR image data uses an average formation of the complex MR image data of the individual image points of the sliding window.

Abstract: Techniques are disclosed for generating a quantitative parameter map from MR data. A specified signal model is adjusted to measured MR data. The signal model contains a time-dependent phase evolution map that specifies a respective separate phase evolution for each echo in a multi-echo sequence used to generate the MR data. Provision is also made for an image region that is to be represented to be divided up into a plurality of pixel fields, which include a plurality of pixels in each case. For all these pixel fields, at least the phase evolution for each echo is assumed to be equal for all the pixels in the respective pixel field, so as to achieve stability of the adjustment of the signal model to the MR data.

Abstract: A method for determining a contrast agent concentration can be performed after contrast agent administration based on acquired MR images taken before and after contrast agent administration. The method can include the automated steps of determining a model equation describing the contrast agent concentration as a function of a plurality of model parameters, determining values for the plurality of model parameters taking the acquired MR images into account, determining the contrast agent concentration based on the model equation and the values determined, checking whether the contrast agent concentration determined is within an expected value range. If not, determining a corrected contrast agent concentration on the basis of the model equation and a corrected value for at least one of the model parameters. The corrected value for this at least one model parameter is determined such that the contrast agent concentration having the corrected value is within the expected value range.

Abstract: In a method, computer and magnetic resonance (MR) apparatus for normalizing MR contrast images of an examination object that has two chemically different substances (SW, SF), wherein the first substance produces a first image signal and the second substance produces a second image signal, a processor is provided with a complex-valued contrast having pixels with signal contributions from the first and second substances. A phase correction of this contrast image is performed by calculating a real-valued contrast from the amount of the image signals of each pixel of the complex-valued contrast image. A mathematically smooth correction map is determined based on a number of the pixels that have a defined real-valued contrast. The intensity of pixels of the complex-valued contrast image are homogenized with other scans based on the correction map.

Abstract: A method for reconstructing dynamic image data is described. In the method, raw data is acquired in a time-dependent manner from an examination region, wherein at least some of the raw data is assigned various values of movement parameters. First time-dependent image data based on acquired raw data is reconstructed. Furthermore, deformation fields based on the first image data are determined as a function of at least two time-dependent movement parameters. Based on the deformation fields, the raw data and the first image data, corrected image data is then generated. Furthermore, a reconstruction apparatus is described. Moreover, a magnetic resonance imaging system is described.

Abstract: Methods are provided for magnetic resonance (MR) image reconstruction. In one exemplary method, a low-resolution prescan MR data record is recorded, the prescan MR data record is adjusted to a provided form of a higher resolution scan MR data record which is likewise to be recorded, a compressed prescan MR data record is generated by geometric coil compression, the scan MR data record is recorded, a compressed scan MR data record is generated by geometric coil compression, and the compressed scan MR data record is then corrected by the compressed prescan MR data record. An MR system includes an MR coil arrangement configured to generate static and high-frequency magnetic fields at the site of an object to be examined and to detect response signals output by the object, and a data processing device configured to process data of the object generated from the response signals, wherein the data processing device is embodied to carry out the method.

Abstract: A method for acquiring magnetic resonance imaging data with respiratory motion compensation using one or more motion signals includes acquiring a plurality of gradient-delay-corrected radial readout views of a subject using a free-breathing multi-echo pulse sequence, and sampling a plurality of data points of the gradient-delay-corrected radial readout views to yield a self-gating signal. The self-gating signal is used to determine a plurality of respiratory motion states corresponding to the plurality of gradient-delay-corrected radial readout views. The respiratory motion states are used to correct respiratory motion bias in the gradient-delay-corrected radial readout views, thereby yielding gradient-delay-corrected and motion-compensated multi-echo data. One or more images are reconstructed using the gradient-delay-corrected and motion-compensated multi-echo data.

Abstract: A magnetic resonance imaging system and method are provided for improved determination of noise bias effects in calculating fitted parameters for quantitative MRI procedures. The system and method includes selecting a range for the SNR and fitted parameter values, and for each of a plurality of base pairs of these values and for a plurality of b values, adding a random noise term to the real and imaginary components of a plurality of corresponding signal terms, fitting magnitudes of the resulting “noisy” signals to determine a “noisy” fitted parameter value, and compare the “noisy” and base fitted parameter values to determine a noise-based error for each pair of base values. The noise-based errors can be used to generate an error map, modify imaging parameters to reduce such errors, or correct fitted parameters directly.