Abstract: In a magnetic resonance (MR) apparatus and a method for operating an MR apparatus, MR data are acquired and evaluated with regard to multiple tentative signal models for producing a parameter map based on one of those signal models. The parameter map shows multiple parameters that have respective effects on the MR data. Each tentative signal model is initially analyzed to determine whether any of the parameters used therein can be assumed to be at least locally constant, and the initially analyzed tentative signal model is then subjected at least to a quality of fit analysis. The tentative signal model having at least the best quality of fit analysis result is then used to generate a parameter map that is displayed at a display monitor.

Abstract: In a magnetic resonance (MR) apparatus and method to evaluate the consistency of a signal model used to generate a quantitative parameter map, the residual of the quantitative parameter map is calculated and a residual map is generated. The residual map is displayed together with the quantitative parameter map, with the residual map serving as an indicator of the quality of fit of the signal model.

Abstract: Embodiments relate to evaluating properties of tissues with magnetic resonance imaging (MRI). A MR image is used to measure a characteristic that influences a particular chemical property of a tissue. In an exemplary embodiment, tissue transverse relaxation values or relaxation rates, which can readily be measured from MR images, are used to evaluate iron deposition in tissue. Iron deposition influences the tissue transverse relaxation values (T2 or T2*) or relaxation rates (R2=1/T2 or R2*=1/T2*). A clinically relevant R2CR* map is calculated based on the known values of the effective R2eff*, the water R2w*, and the fat R2f* by incorporating the most relevant value for each individual image element of a plurality of image elements of an MR image of the tissue. The clinically relevant R2CR* map provides an accurate evaluation of iron deposition in any region of the tissue with the use of one map.

Abstract: A method for denoising magnetic resonance images includes estimating a normalization field corresponding to a magnetic resonance imaging device and acquiring a non-normalized image from the magnetic resonance imaging device. A noise level estimation process is performed with the non-normalized image to yield a noise level. The normalization field is applied to the noise level to yield a potentially inhomogeneous noise-level map and to the non-normalized image to yield a normalized image. An adaptive polynomial filtering process is performed using the normalized image and the potentially inhomogeneous noise-level map to yield a denoised image.

Abstract: In a method and magnetic resonance (MR) apparatus for determining a first parameter and a second parameter in a volume of an examination object, MR signals of the volume are acquired using various values of at least one acquisition parameter. A first function is specified by which an MR signal can be determined depending on the first parameter and the at least one acquisition parameter, and a second function is specified by which an MR signal can be determined depending on the second parameter and the at least one acquisition parameter. A first subset of the MR signals is determined for the first parameter and a second subset of the MR signals is determined for the second parameter, wherein the first subset differs from the second subset.

Abstract: In a method to select an undersampling scheme of k-space and an associated set of reconstruction kernels to acquire reduced magnetic resonance (MR) data sets with multiple coils, a calibration data set is acquired for each of the respective coils, a noise covariance is determined from autocorrelations and correlations of the noise of the various coils. At least one set of reconstruction kernels is calculated for each of the multiple undersampling schemes from the calibration data sets of the various coils. For each set of reconstruction kernels, a characteristic value is calculated from the noise covariance and the respective reconstruction kernels of the coils, with the characteristic value being proportional to a spatial mean value of a signal noise of an MR image. A selected undersampling scheme and a selected set of reconstruction kernels are selected based on the calculated characteristic values.

Abstract: In a method to correct noise effects in magnetic resonance (MR) images, which is executed in a processor (computer), the processor executes a fitting algorithm in order to calculate initial values for each of selected variables in signal model that models noise effects in a modeled, noise-containing MR image. The processor then iteratively executes the same or a different fitting algorithm, in order to generate final values for each of the selected variables. The processor is provided with an actual, acquired MR image that contains noise, and the processor uses the final values of the selected variables to calculate synthetic signal intensities in the MR image, thereby producing a synthetic MR image with no noise bias effects of errors. This synthetic image is made available in electronic form at an output of the processor, as a data file.

Abstract: A computer-implemented method for quantifying fat and iron in anatomical tissue includes acquiring a plurality of multi-echo signal datasets representative of the anatomical tissue using a magnetic resonance (MR) pulse sequence. A plurality of multi-echo signal datasets are selected from the plurality of multi-echo signal datasets and used to determine a first water magnitude value and a first fat magnitude value. In response to determining that the multi-echo signal datasets include at least three multi-echo datasets, a first stage analysis is performed. This first stage analysis comprises selecting a first effective transverse relaxation rate value. Next, first algorithm inputs comprising the first water magnitude value, the first fat magnitude value, and the first effective transverse relation rate value are created.

Abstract: Disclosed herein is a framework for identifying signal components in image data. In accordance with one aspect, the framework receives multiple measured signal values corresponding to respective quantified signal components in image data. The framework determines at least one first measure of fit map of a signal model based on the measured signal values. The measured signal values may be swapped to generate swapped signal values. At least one second measure of fit map of the signal model may be determined based on the swapped signal values. The multiple signal components may then be identified by comparing the first and second measure of fit maps.

Abstract: In a method and a magnetic resonance system for acquisition of spectroscopy data in a predetermined volume segment of an examination subject, spectroscopy data in the volume segment are acquired in multiple measurement steps, and spatially resolved MR data of the examination subject also are acquired in multiple measurement steps. Each of the measurement steps to acquire the spectroscopy data or to acquire the MR data respectively includes an excitation step and a readout step associated with that excitation step. At least one of the measurement steps to acquire the MR data occurs between one of the measurement steps to acquire the spectroscopy data and another of the measurement steps to acquire the spectroscopy data.

Abstract: In a method and magnetic resonance (MR) apparatus to acquire MR data from a subject, a predetermined spectral model of a multipoint Dixon technique is used that includes at least two spectral components with respective associated relaxation rates, a first phase due to field inhomogeneities; and a second phase due to eddy current effects. MR data are acquired using a bipolar multi-echo MR measurement sequence for multiple image points wherein, for each image point, the multi-echo MR measurement sequence alternately uses positive and negative readout gradient fields for the readout of MR signals of the MR data at at least three echo times. The at least two spectral components are determined based on the MR data.

Abstract: In a method and a magnetic resonance system to determine the T1 time of water and the T1 time of fat in a predetermined volume segment of an examination subject, magnetic field gradients are activated to generate multiple gradient echoes. First echoes are acquired at at least two different echo times based on RF pulses with a first flip angle. A first water magnetization and a first fat magnetization are determined for each voxel of the volume segment from the first echoes, according to the Dixon method. Second echoes are acquired at at least two different echo times based on RF pulses with a second flip angle. A second water magnetization and a second fat magnetization are determined for each voxel of the volume segment depending on the second echoes according to the Dixon method.

Abstract: In a method and system for magnetic resonance imaging of an examination subject on the basis of partially parallel acquisition (PPA) with multiple component coils, a calibration measurement is implemented in a first time period and an actual measurement for the imaging is implemented in a subsequent second time period. In the calibration measurement, calibration data for predetermined calibration points in spatial frequency space are acquired with the multiple component coils. In the actual measurement, incomplete data sets are respectively acquired in spatial frequency space with each of the multiple component coils. Complete data sets are reconstructed from the incomplete data sets and the calibration data. The first time period and the second time period are different, and the measurements are implemented when triggered in the two time periods. An essentially identical state of the examination subject or of the measurement system is used as a trigger.

Abstract: An apparatus and a method for generating an image from N reception signal data sets of signals received by a plurality of coils of a magnetic resonance tomography appliance from a region of a body to be examined using an image processing computer are provided. The apparatus includes a degree-of-compression determining device. A ratio N/M of the number N of N reception signal data sets generated from the signals received by the plurality of coils to a smaller number M of mode data sets is defined taking account of a plurality of parameters. The plurality of parameters at least also represent system resources of the image processing computer. Using a compression computer, the N reception signal data sets are compressed into M mode data sets. After this, the M mode data sets are used by the image processing computer for generating the image of the region of the body.

Abstract: Embodiments relate to evaluating properties of tissues with magnetic resonance imaging (MRI). A MR image is used to measure a characteristic that influences a particular chemical property of a tissue. In an exemplary embodiment, tissue transverse relaxation values or relaxation rates, which can readily be measured from MR images, are used to evaluate iron deposition in tissue. Iron deposition influences the tissue transverse relaxation values (T2 or T2*) or relaxation rates (R2=1/T2 or R2*=1/T2*). A clinically relevant R2CR* map is calculated based on the known values of the effective R2eff*, the water R2w*, and the fat R2f* by incorporating the most relevant value for each individual image element of a plurality of image elements of an MR image of the tissue. The clinically relevant R2CR* map provides an accurate evaluation of iron deposition in any region of the tissue with the use of one map.

Abstract: A computer-implemented method for quantifying fat and iron in anatomical tissue includes acquiring a plurality of multi-echo signal datasets representative of the anatomical tissue using a magnetic resonance (MR) pulse sequence. A plurality of multi-echo signal datasets are selected from the plurality of multi-echo signal datasets and used to determine a first water magnitude value and a first fat magnitude value. In response to determining that the multi-echo signal datasets include at least three multi-echo datasets, a first stage analysis is performed. This first stage analysis comprises selecting a first effective transverse relaxation rate value. Next, first algorithm inputs comprising the first water magnitude value, the first fat magnitude value, and the first effective transverse relation rate value are created.

Abstract: In a method and apparatus to determine a magnetic resonance image of an examination subject with at least two spin species by using a chemical shift imaging multi-echo MR measurement sequence, first approximated MR image is determined based on a first approximative model and of a second approximated MR image is determined based on a second approximative model, wherein the first and second approximative model respectively express an MR signal under consideration of one or more MR parameters, and wherein the first and second approximative model differ with regard to the consideration of at least one MR parameter. The MR image is determined from a mean calculation that depends on the first and second approximated MR image.

Abstract: Various embodiments relate to a method for determining distortion-reduced magnetic resonance data in a subarea of a magnetic resonance system located along a radial direction of the magnetic resonance system at the edge of a field of view of the magnetic resonance system. The method includes positioning the object to be examined at a first and a second position along an axial direction of the magnetic resonance system and acquiring first magnetic resonance data in the subarea at the first position and acquiring second magnetic resonance data in the same subarea at the second position. The method also includes determining distortion-reduced magnetic resonance data based on the first and second magnetic resonance data.

Abstract: In a method and apparatus for time-resolved acquisition of magnetic resonance (MR) data, an examination subject is continuously moved through the examination region of an MR scanner, and MR signals are acquired. Prior to the acquisition of MR signals, a phase coding that corresponds to a position for data entry in k-space is carried out. An interruption of the movement of the subject takes place at a predetermined table position, and the acquisition of MR signals is continued over the course of a predetermined time period, while the subject is at rest in the predetermined position. At least while the subject is at rest, the phase coding causes acquisition of a predetermined number of MR signals for filling a first region of k-space to alternate with MR data and a predetermined number of MR signals for filling a second region of k-space.

Abstract: In a method to select an undersampling scheme of k-space and an associated set of reconstruction kernels to acquire reduced magnetic resonance (MR) data sets with multiple coils, a calibration data set is acquired for each of the respective coils, a noise covariance is determined from autocorrelations and correlations of the noise of the various coils. At least one set of reconstruction kernels is calculated for each of the multiple undersampling schemes from the calibration data sets of the various coils. For each set of reconstruction kernels, a characteristic value is calculated from the noise covariance and the respective reconstruction kernels of the coils, with the characteristic value being proportional to a spatial mean value of a signal noise of an MR image. A selected undersampling scheme and a selected set of reconstruction kernels are selected based on the calculated characteristic values.