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: 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: 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: A closure system for a motor vehicle cargo bed includes a closure panel having a plurality of slats moveable between a deployed position and a retracted position, with each adjacent pair of the slats being pivotably connected to one another by a hinge unit for pivotal movement of the adjacent slats about a hinge axis. First and second guide track units are configured to be mounted to one side of the cargo bed to extend adjacent opposite side edge portions of the closure panel. A plurality of roller units, each having first and second rollers, are supported along the opposite side edge portions of the cover panel for rolling movement along the first and second guide track units, with each roller unit rolling about a roller axis that is coaxially aligned with one of the hinge axes.

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 method for acquiring a magnetic resonance data set of an object under examination by a magnetic resonance system using a scan sequence is provided. The scan sequence includes a succession of sequence blocks, and in each sequence block, there is at least one sub-block including an excitation section and/or a detection section. An excitation section includes at least one excitation pulse, and in a detection section, an echo signal or an echo train is acquired as a scan signal. At least one item of motion information is provided for each sub-block. The motion information contains information about a movement of the object under examination within a duration of the sub-block. Some of the sub-blocks are automatically repeated. At least the sub-blocks having motion information that exceeds a threshold value are repeated. The threshold value defines a motion amplitude.

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 monitor a biological process. The method includes obtaining an abnormal tissue mask from an abnormal tissue segmentation of an image of an object containing tissue to be analyzed, the image being acquired at a time t0 being a reference time point. Other images of the object are registered onto the abnormal tissue mask, the other images being acquired at other time points. Image contrasts of the other images are normalized with respect to the contrasts of the image acquired at the reference time point. The normalized images are subtracted for each available contrast in order to obtain difference images. A joint difference image is created by summing the previously obtained difference images. A biological process progression map is created by overlapping the abnormal tissue mask obtained and the joint difference image after applying a pre-defined threshold.

Abstract: A method is used to carry out a magnetic resonance measurement with at least one echo train with n spin echoes and prospective movement correction. Movement correction data for each echo train is updated at the start of the echo train and is then updated again at most partially for the spin echoes.

Abstract: A method for adapting a medical system to an object movement during medical examination of the object and a medical system configured for carrying out the method. The medical system has a device for detecting and quantifying a motion of the object before or during an acquisition of diagnostic data. The system for detecting and quantifying a motion of the object is able to directly identify and qualify the occurrence of object motion and to automatically suggest an adaptation of the diagnostic data acquisition strategy/technique as a function of the object motion.

Abstract: A system and a method for mapping lesions or damage instances of a brain. The method includes receiving a lesion segmentation mask for the brain and receiving a tractography atlas. A connectivity damage brain map is constructed from (i) superimposing the lesion segmentation mask and a tractography atlas-based image, and (ii) combining information from the lesion segmentation mask with information from the tractography atlas-based image. The tractography atlas-based image is an image obtained from the tractography atlas, and the tractography atlas-based image and the lesion segmentation mask are registered to a common space.

Abstract: Techniques are disclosed for a scan recommendation method is disclosed, wherein evaluation data comprising classification data are received, the classification data classifying anomalies detected in input data concerning the medical condition of a patient. Based on the evaluation data, an automatic determination of a next recommended MR protocol to be executed in accordance with an MR scan of the patient is performed. Further, a personal scan preparation method is disclosed and a medical imaging method is described, as well as a scan workflow performing method. For execution of the above-mentioned methods, a scan recommendation system, a personal scan preparation system, a medical imaging system, and a scan workflow performing system are also described.

Abstract: A method and system are provided for detecting a position of a periodically moving organ in a MRI examination. MR images of an examining person including a periodically moving organ are provided over a plurality of periodic cycles of the periodically moving organ. Based on the provided MR images, a pixel frequency is associated with each pixel of the MR images. Using the associated pixel frequencies and the positions of the pixels within the MR images, the position and the frequency of the periodically moving organ are determined.

Abstract: The disclosure relates to a method for the interactive acquisition of data from an object under investigation by a magnetic resonance system. The data is acquired from the object under investigation with the magnetic resonance system and images are automatically reconstructed and displayed in real time based on the data. A time interval is determined during which a predetermined condition is met in the images. Quality images are automatically reconstructed based on the data acquired within the time interval. The temporal resolution during reconstruction of the quality images is higher than the temporal resolution during reconstruction of the images.

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: A method for acquiring a magnetic resonance data set of an object under examination by a magnetic resonance system using a scan sequence is provided. The scan sequence includes a succession of sequence blocks, and in each sequence block, there is at least one sub-block including an excitation section and/or a detection section. An excitation section includes at least one excitation pulse, and in a detection section, an echo signal or an echo train is acquired as a scan signal. At least one item of motion information is provided for each sub-block. The motion information contains information about a movement of the object under examination within a duration of the sub-block. Some of the sub-blocks are automatically repeated. At least the sub-blocks having motion information that exceeds a threshold value are repeated. The threshold value defines a motion amplitude.

Abstract: In order to reduce the time and effort required to generate high-quality image reconstructions, a machine-trained neural network may assign a quality score to an image at each iteration of a reconstruction. The neural network may confirm that the iterative reconstruction process increases image quality as each iteration converges to the solution of an optimization problem. The image quality score generated by the neural network may drive the reconstruction toward better image quality by contributing to a regularization term of a cost function minimized by the optimization problem. The neural network may allow for multiple reconstruction of image data to be performed rapidly and for the highest image quality reconstruction to be identified. Additionally, the neural network may provide exit criteria of the iterative reconstruction or may contribute to the optimization problem.