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.

Abstract: The disclosure includes a method for generating quantitative magnetic resonance (MR) images of an object under investigation. A first MR data set of the object under investigation is captured in an undersampled raw data space, wherein the object under investigation is captured in a plurality of 2D slices, in which the resolution in a slice plane of the slices is in each case higher than perpendicular to the slice plane, wherein the plurality of 2D slices are in each case shifted relative to one another by a distance which is smaller than the resolution perpendicular to the slice plane. Further MR raw data points of the first MR data set are reconstructed with the assistance of a model using a cost function which is minimized. The cost function takes account of the shift of the plurality of 2D slices perpendicular to the slice plane.

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 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: In a magnetic resonance (MR) apparatus, and model-based method, for identifying a nuclear spin-dependent attribute of a subject, MR signals are acquired in multiple repetitions of an MR data acquisition sequence that is changed from repetition-to-repetition so as to deliberately encode effects of magnetization transfer between nuclear spins into the acquired MR signals. A model is generated, composed of at least two molecule pools, in which a single magnetization transfer parameter is used that is derived from the MR signals in which the magnetization transfer is encoded. A nuclear spin-dependent attribute of the subject is then identified, by comparing at least one MR signal evolution from the subject to at least one signal evolution produced by the model.

Abstract: Organ tissue properties of a patient are automatically compared with organ tissue properties of a healthy subject group. A population norm for the organ tissue properties is determined by: selecting at least two different tissue properties of the organ; determining for each tissue property previously selected and for each subject of said group a quantitative tissue property map; for each subject of the group, calculating a joint histogram from all the quantitative tissue property maps obtained for said subject; and determining an averaged joint histogram from all subjects of the healthy group, thus defining the population norm. A comparison is automatically performed of the averaged joint histogram with a patient joint histogram obtained for the organ tissue properties of the patient, by calculating a statistical deviation of values of a patient joint histogram relative to values of the averaged joint histogram, and mapping the statistical deviation to the patient organ.

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: Organ tissue properties of a patient are automatically compared with organ tissue properties of a healthy subject group. A population norm for the organ tissue properties is determined by: selecting at least two different tissue properties of the organ; determining for each tissue property previously selected and for each subject of said group a quantitative tissue property map; for each subject of the group, calculating a joint histogram from all the quantitative tissue property maps obtained for said subject; and determining an averaged joint histogram from all subjects of the healthy group, thus defining the population norm. A comparison is automatically performed of the averaged joint histogram with a patient joint histogram obtained for the organ tissue properties of the patient, by calculating a statistical deviation of values of a patient joint histogram relative to values of the averaged joint histogram, and mapping the statistical deviation to the patient organ.

Abstract: In a magnetic resonance (MR) apparatus, and model-based method, for identifying a nuclear spin-dependent attribute of a subject, MR signals are acquired in multiple repetitions of an MR data acquisition sequence that is changed from repetition-to-repetition so as to deliberately encode effects of magnetization transfer between nuclear spins into the acquired MR signals. A model is generated, composed of at least two molecule pools, in which a single magnetization transfer parameter is used that is derived from the MR signals in which the magnetization transfer is encoded. A nuclear spin-dependent attribute of the subject is then identified, by comparing at least one MR signal evolution from the subject to at least one signal evolution produced by the model.

Abstract: A method is disclosed for recording a parameter map of a target region via a magnetic resonance device. In at least one embodiment, an optimization method is used for the iterative reconstruction of the parameter map. In the optimization method, the deviation of undersampled magnetic resonance data of the target region present in the k-space for different echo times, magnetic resonance data of a portion of the k-space being present in each case for each echo time, is assessed from hypothesis data of a current hypothesis for the parameter map obtained as a function of the parameter from a model for the magnetization. To determine the magnetic resonance data of a portion of the k-space, undersampled raw data is initially acquired within the portions by way of the magnetic resonance device embodied for parallel imaging, and missing magnetic resonance data within the portions is completed by way of interpolation.

Abstract: A method for improving image homogeneity of image data acquired from balanced Steady-State Free Precision (bSSFP) sequences in magnetic resonance imaging. Multiple bSSFP sequences are performed with different radio frequency phase increments to create multiple bSSFP image volumes with different phase offsets ?. Each image has voxels whose intensity M is a function of a nuclear resonance signal (or magnetization) measured by the MR imaging apparatus. Per-voxel fitting of a mathematical signal model onto the measured magnetization of the field of view in function of the phase offsets ?. Then the spin density M0, the relaxation time ratio ? and the local phase offset ?? are determined from the fit for each voxel. A homogeneous image of the object is generated by calculating the signal intensity in each voxel, using the spin density M0 and the relaxation time ratio ?, wherein ?? is chosen such that ????=0°.

Abstract: The disclosure includes a method for generating quantitative magnetic resonance (MR) images of an object under investigation. A first MR data set of the object under investigation is captured in an undersampled raw data space, wherein the object under investigation is captured in a plurality of 2D slices, in which the resolution in a slice plane of the slices is in each case higher than perpendicular to the slice plane, wherein the plurality of 2D slices are in each case shifted relative to one another by a distance which is smaller than the resolution perpendicular to the slice plane. Further MR raw data points of the first MR data set are reconstructed with the assistance of a model using a cost function which is minimized. The cost function takes account of the shift of the plurality of 2D slices perpendicular to the slice plane.

Abstract: A method detects phase-encoding ghosting in a MR image of an object to be imaged and mitigates the corresponding artifact in the MR image. The method includes acquiring MRI raw data of the object by a MRI apparatus. The MRI apparatus has multiple receiver channels for acquiring the MRI raw data. An artifact map of at least one part of the object to be imaged is calculated from the MRI raw data, the artifact map is configured for highlighting artifact appearing in the MR image. An outlier mask representing detected phase-encoding artifact is created in the artifact map. The phase-encode ghosting in the MR image is mitigated by using the previously obtained artifact map and the outlier mask for obtaining an improved MR image.

Abstract: A method for improving image homogeneity of image data acquired from balanced Steady-State Free Precision (bSSFP) sequences in magnetic resonance imaging. Multiple bSSFP sequences are performed with different radio frequency phase increments to create multiple bSSFP image volumes with different phase offsets ?. Each image has voxels whose intensity M is a function of a nuclear resonance signal (or magnetization) measured by the MR imaging apparatus. Per-voxel fitting of a mathematical signal model onto the measured magnetization of the field of view in function of the phase offsets ?. Then the spin density M0, the relaxation time ratio ? and the local phase offset ?? are determined from the fit for each voxel. A homogeneous image of the object is generated by calculating the signal intensity in each voxel, using the spin density M0 and the relaxation time ratio ?, wherein ?? is chosen such that ????=0°.

Abstract: A method detects phase-encoding ghosting in a MR image of an object to be imaged and mitigates the corresponding artifact in the MR image. The method includes acquiring MRI raw data of the object by a MRI apparatus. The MRI apparatus has multiple receiver channels for acquiring the MRI raw data. An artifact map of at least one part of the object to be imaged is calculated from the MRI raw data, the artifact map is configured for highlighting artifact appearing in the MR image. An outlier mask representing detected phase-encoding artifact is created in the artifact map. The phase-encode ghosting in the MR image is mitigated by using the previously obtained artifact map and the outlier mask for obtaining an improved MR image.

Abstract: A method is disclosed for recording a parameter map of a target region via a magnetic resonance device. In at least one embodiment, an optimization method is used for the iterative reconstruction of the parameter map. In the optimization method, the deviation of undersampled magnetic resonance data of the target region present in the k-space for different echo times, magnetic resonance data of a portion of the k-space being present in each case for each echo time, is assessed from hypothesis data of a current hypothesis for the parameter map obtained as a function of the parameter from a model for the magnetization. To determine the magnetic resonance data of a portion of the k-space, undersampled raw data is initially acquired within the portions by way of the magnetic resonance device embodied for parallel imaging, and missing magnetic resonance data within the portions is completed by way of interpolation.