Abstract: A system and a method for measuring a maturation stage of a biological organ are based on quantitative MR maps for the organ. The method includes acquiring with a first interface and for a subject, a quantitative MR map for the organ. The quantitative MR map includes voxels each characterized by a quantitative value. The quantitative value of each voxel represents a measurement of a physical or physiological property of a tissue of the biological organ for the voxel. The method also includes applying to the quantitative map a trained function to estimate the subject organ maturation stage, and the trained function outputting an age. The method provides with a second interface the maturation stage of the organ of the subject as being the output age.

Abstract: A system and a method for detecting and quantifying a tissue alteration of a biological object. The method comprises the following steps: acquiring multiple quantitative maps of the biological object, wherein each of the multiple quantitative maps is a quantitative map of a different physical tissue property of the biological object; combining the acquired quantitative maps into a combined quantitative map (CQM); and calculating a deviation map by comparing the CQM to a normative atlas configured for providing expected values for the CQM.

Abstract: A computer-implemented method and system for automated segmentation of anatomical structures of a biological object, include acquiring an MRI image of the object constructed from a set of slices of the object, dividing the set of slices into overlapping groups of consecutive slices, and feeding each overlapping group of consecutive slices as input into a neural network for outputting a labelled map for each inputted slice. For each slice belonging to several overlapping groups, determining for each voxel a final label from specific labels assigned to the voxel by the neural network when considering the labelled maps outputted for the considered slice and assigning to each voxel the final label previously determined for the considered voxel and outputting a final segmentation map of final labels assigned to the voxels of the considered slice. A final 3D segmented image of the object is created from previously obtained final segmentation maps.

Abstract: A method for controlling a magnetic resonance imaging system, including: selecting a plurality of spatially non-selective initial RF-pulses each having a predefined pulse shape and a predefined frequency; determining a combined RF-pulse from the initial RF-pulses by choosing a time-offset comprising a relative application time-shift between the initial RF-pulses, wherein this time-offset is chosen such that the initial RF-pulses overlap; and including the combined RF pulse in a pulse sequence applied in a magnetic resonance imaging system.

Abstract: In a method for improving the contrast of magnetization-transfer-prepared magnetic resonance imaging (MRI), an acquisition scheme comprising a plurality of inversion-recovery (IR)-imaging modules in an interleaved arrangement is selected, a number of magnetization-transfer (MT)-preparation modules is selected, a pulse sequence is generated by arranging at least one MT-preparation module of the number of MT-preparation modules between two successive IR-preparation modules of the interleaved IR-imaging modules or in front of the first IR-preparation module of a group of interleaved IR-imaging modules, and the pulse sequence for an MRI examination is applied or saved. Each IR-imaging module may include an IR-preparation module and a slice acquisition module.

Abstract: A motion correction method may include: calculating a current motion-corrected MR image based on a current motion parameter of an imaging target and K-space measurement data of the imaging target; calculating current motion-corrected K-space data based on the current motion parameter of the imaging target and the current motion-corrected MR image; calculating a current K-space measurement data error based on the K-space measurement data of the imaging target and the current motion-corrected K-space data; and determining, based on the current K-space measurement data error, whether an iteration end condition is met. If so, using the current motion-corrected MR image as a final motion-corrected MR image to be used. Otherwise, updating the current motion parameter of the imaging target based on the current K-space measurement data error and the current motion-corrected MR image. The method advantageously provides an increased motion correction speed of an MR image.

Abstract: A qMRI system and method map qMRI parameters of a biological object. The method includes performing, by the qMRI system, N scans wherein each scan, includes: performing T2-prepared inversion pulse series, each followed by readout blocks, each magnetization preparation RF pulse series is a T2-prepared inversion pulse series containing multiple pulses and an inter-pulse duration, for varying to obtain different T2 weightings; and acquiring, by the MRI system and during each readout block of an MRI, a recovery signal generated by a part of the biological object, wherein for each readout block, an MRI signal is acquired by the MRI system at different inversion times. An image of the part is reconstructed for and from each MRI signal. A voxel-wise signal is created by concatenating intensity values for a same voxel for the reconstructed images. A physical model is fitted to the concatenated intensity values to obtain a qMRI map.

Abstract: An MRI method and system for mapping T1 relaxation times of a biological object with a part having a short-T2 relaxation time. The MRI system first performs one or several magnetization preparation radio frequency pulse sequences, with successive RF pulse sequences being separated by a repetition time interval TR. The MRI system acquires an MRI signal generated by the part of said biological object during each repetition time interval TR in response to a plurality of 3D readout blocks generated by the MRI system and applied to the part of the biological object. For each readout block, an MRI signal is acquired by the MRI system at a different recovery time. Each readout block is sensitive to short-T2 signal. An image of the part is reconstructed from each MRI signal and T1 values are mapped for the part from at least two of said reconstructed images.

Abstract: A system and a method for mapping brain tissue damage from quantitative imaging data. The method is implemented by acquiring a quantitative map of a brain tissue parameter of said brain; acquiring a tractography map for said brain; superimposing a first map based on the quantitative map onto a second map based on the tractography map. Metrics are extracted from the superimposition that reflect a distribution of tract-specific quantitative values of the brain tissue parameter and the metrics of the brain are displayed.

Abstract: In a method for control, input magnetic field map data is received. In this case, the input magnetic field map data for at least one magnetic field type in each case describes a magnetic field map for a state that an examination object is in at an initial location in the MR apparatus. In this case, the estimated magnetic field map data for at least one magnetic field type in each case describes at least one magnetic field map for in each case a state that the examination object is in at an alternative location that is different compared to the initial location. Control data is determined by the system control unit, using the estimated magnetic field map data or using the input magnetic field map data and the estimated magnetic field map data. The control data is suitable for controlling the MR apparatus.

Abstract: A system and a method determine a value for a parameter. Reference values for the parameter are determined from a group of objects. A first technique is used by the system for determining for each object the reference value from a first set of data. A learning dataset is created by associating for each object of the group of objects a second set of data and the reference value. The second set of data is acquired by the system according to a second technique for determining values of the parameter and is configured for enabling a determination of the parameter. A machine learning technique trained on the learning dataset is used for determining a value of the parameter. The second set of data obtained for each of the objects is used as input in a machine learning algorithm and its associated reference value is used as output target.

Abstract: In a method for improving the contrast of magnetization-transfer-prepared magnetic resonance imaging (MRI), an acquisition scheme comprising a plurality of inversion-recovery (IR)-imaging modules in an interleaved arrangement is selected, a number of magnetization-transfer (MT)-preparation modules is selected, a pulse sequence is generated by arranging at least one MT-preparation module of the number of MT-preparation modules between two successive IR-preparation modules of the interleaved IR-imaging modules or in front of the first IR-preparation module of a group of interleaved IR-imaging modules, and the pulse sequence for an MRI examination is applied or saved. Each IR-imaging module may include an IR-preparation module and a slice acquisition module.

Abstract: In a method for control, input magnetic field map data is received. In this case, the input magnetic field map data for at least one magnetic field type in each case describes a magnetic field map for a state that an examination object is in at an initial location in the MR apparatus. In this case, the estimated magnetic field map data for at least one magnetic field type in each case describes at least one magnetic field map for in each case a state that the examination object is in at an alternative location that is different compared to the initial location. Control data is determined by the system control unit, using the estimated magnetic field map data or using the input magnetic field map data and the estimated magnetic field map data. The control data is suitable for controlling the MR apparatus.

Abstract: A method and a system create an age-specific quantitative atlas for a biological object. The method includes obtaining a quantitative map of the biological object for each subject of a healthy subject population, generating an age-specific initial map for the biological object using a weighted mean, and spatially registering each of the quantitative maps on the age-specific initial map. The generating and registering steps are repeated iteratively until reaching a first predefined alignment threshold between all spatially registered quantitative maps. The new age-specific initial map obtained is stored at the end of the iterative process of the repeating step as the age-specific quantitative atlas for a biological object characterized by the specific age.

Abstract: A computer-implemented method and system for automated segmentation of anatomical structures of a biological object, include acquiring an MRI image of the object constructed from a set of slices of the object, dividing the set of slices into overlapping groups of consecutive slices, and feeding each overlapping group of consecutive slices as input into a neural network for outputting a labelled map for each inputted slice. For each slice belonging to several overlapping groups, determining for each voxel a final label from specific labels assigned to the voxel by the neural network when considering the labelled maps outputted for the considered slice and assigning to each voxel the final label previously determined for the considered voxel and outputting a final segmentation map of final labels assigned to the voxels of the considered slice. A final 3D segmented image of the object is created from previously obtained final segmentation maps.

Abstract: A method for controlling a magnetic resonance imaging system, including: selecting a plurality of spatially non-selective initial RF-pulses each having a predefined pulse shape and a predefined frequency; determining a combined RF-pulse from the initial RF-pulses by choosing a time-offset comprising a relative application time-shift between the initial RF-pulses, wherein this time-offset is chosen such that the initial RF-pulses overlap; and including the combined RF pulse in a pulse sequence applied in a magnetic resonance imaging system.

Abstract: A tissue type fraction within a biological object is determined by a phase-cycled acquisition of several images of the object and deriving a complex signal profile for each voxel of the acquired images; generating a multidimensional dictionary of simulated signal profiles, wherein each simulated signal profile is configured for simulating the previously derived complex signal profile; using a weight optimization algorithm configured for expressing the complex signal profile as a weighted sum of the simulated signal profiles, wherein the weight optimization algorithm provides as output for each voxel a matrix M of optimized weights; for each voxel and each dimension of the obtained matrix M, extracting from the matrix M a distribution of the obtained optimized weights; and determining a type of tissue composing each voxel from the obtained distributions.

Abstract: A system and a method for measuring a maturation stage of a biological organ are based on quantitative MR maps for the organ. The method includes acquiring with a first interface and for a subject, a quantitative MR map for the organ. The quantitative MR map includes voxels each characterized by a quantitative value. The quantitative value of each voxel represents a measurement of a physical or physiological property of a tissue of the biological organ for the voxel. The method also includes applying to the quantitative map a trained function to estimate the subject organ maturation stage, and the trained function outputting an age. The method provides with a second interface the maturation stage of the organ of the subject as being the output age.

Abstract: A system and method generate a synthetic image with switchable image contrast components for a biological object. The method includes: a) using first and second quantitative MRI acquisition techniques for measuring a value of first or second quantitative parameters Q1, Q2 for the biological object and generating first and second quantitative maps, the first and second quantitative MRI acquisition techniques generate first and second contrast-weighted images; b) using the first and second quantitative maps, and the first and second contrast weighted images as inputs in a model configured for generating a synthetic image M with arbitrary sequence parameters P1, P2, P3, according to: M=|Cif(Q1,Q2,P1,P2,P3)| wherein Ci with i=1, 2, are contrast components for the generation of the synthetic image M coming from respectively the first (i=1) and second (i=2) contrast-weighted images (i=1) and f is a function of Q1, Q2, P1, P2 and P3; and c) displaying the synthetic image M.

Abstract: A tissue type fraction within a biological object is determined by a phase-cycled acquisition of several images of the object and deriving a complex signal profile for each voxel of the acquired images; generating a multidimensional dictionary of simulated signal profiles, wherein each simulated signal profile is configured for simulating the previously derived complex signal profile; using a weight optimization algorithm configured for expressing the complex signal profile as a weighted sum of the simulated signal profiles, wherein the weight optimization algorithm provides as output for each voxel a matrix M of optimized weights; for each voxel and each dimension of the obtained matrix M, extracting from the matrix M a distribution of the obtained optimized weights; and determining a type of tissue composing each voxel from the obtained distributions.