A computer-implemented method of analysing nuclear magnetic resonance, NMR, data of a target object is provided. The method comprises receiving NMR data of the target object, and analysing the received NMR data using a model of the diffusive behaviour of 5 particles within the target object. The model includes a time parameter and a space parameter, the time parameter describing temporal characteristics of the diffusive behaviour of particles in the model and the space parameter describing spatial characteristics of the diffusive behaviour of particles in the model. The model is constrained such that the value of the time parameter and the value of the space parameter 10 are related according to a correlation function. An apparatus for analysing nuclear magnetic resonance, NMR, data of a target object is also provided.

An ambulance-compatible magnetic resonance imaging (MRI) system for on-site emergency diagnosis includes a mid-field super-conducting head-only magnet including a bore and an active shield arranged relative to the magnet, a passive shield arranged relative to the magnet, the passive shield including a first flange arranged adjacent to a first side of the magnet bore, a second flange arranged adjacent to a second side of the magnet bore, wherein the first flange and the second flange are electrically connected to each other, and wherein the passive shield is operative to capture flux extending out from the magnet bore and return the flux to the magnet. An asymmetric head gradient assembly for generating magnetic gradient field in the mid-field super-conducting magnet is also provided, the magnetic gradient field being between 100-150 mT/m or having a slew rate between 400-800 T/m/s. The MRI system includes a receiver coil and a controller operatively coupled to the receive coil, the controller configured to produce an image based on data obtained from the receive coil. The MRI system is mountable in an ambulance vehicle.

The present disclosure provides a system and method for magnetic resonance imaging. The method may include obtaining a first set of imaging data, the first set of imaging data being sampled in multiple shots, each shot of the multiple shots corresponding to a plurality of echo times, the first set of imaging data including partially sampled data in a first k space; obtaining a second set of imaging data, the second set of imaging data including fully sampled data in a central region of a second k space; determining fitting data in the first k space based on the first set of imaging data and the second set of imaging data; and/or generating a target image based on the fitting data in the first k space and the first set of imaging data in the first k space.

A method (100), a device (400), and a system for detecting the sweetness of fruit, and a storage medium. The method (100) comprises: using magnetic resonance diffusion weighted imaging to acquire an apparent diffusion coefficient (ADC) of fruit to be detected when same is undamaged (S110); determining an effective ADC of said fruit according to the ADC of said fruit (S120); and determining the sweetness of said fruit according to the effective ADC (S130). The ADC of fruit to be detected may be acquired on the basis of magnetic resonance imaging when said fruit is undamaged, and the ADC is used to determine the sweetness of the fruit, thus achieving non-destructive and reliable fruit sweetness detection.

A diagnostic system to analyze imaging data includes a memory configured to store hybrid imaging data of a tissue sample. The system also includes a processor operatively coupled to the memory and configured to generate a four quadrant plot based on the hybrid imaging data. Each point in the four quadrant plot corresponds to an image voxel of the tissue sample. The processor is also configured to determine one or more angle values and one or more distance values for image voxels in the four quadrant plot. The processor is further configured to identify one or more characteristics of the tissue sample based at least in part on the one or more angle values and the one or more distance values. The processor is further configured to perform a matrix analysis of the data, which can be used to identify the one or more characteristics of the tissue sample.

The present invention relates to an apparatus (10) to analyse diffusion magnetic resonance imaging data. The apparatus comprises an input unit (20), a processing unit (30), and an output unit (40). The input unit is configured to provide the processing unit with at least one diffusion magnetic resonance imaging “dMRI” image of a patient's brain. The processing unit is configured to determine an estimate of an orientation of neurons at each voxel in the dMRI image, the determination comprising utilization of the at least one dMRI image. The processing unit is configured to determine a plurality of fiber tracts in the at least one dMRI image, the determination comprising utilization of the estimated orientation of neurons at each voxel in the at least one dMRI image. The processing unit is configured to select a plurality of voxels along at least one fiber tract of the plurality of fiber tracts. The processing unit is configured to determine a neurological disease classification, the determination comprising utilization of at least one diffusivity feature associated with each of the selected plurality of voxels. The output unit is configured to output the neurological disease classification.

Methods and systems are provided for analyzing diffusion weighted images (DWI) using impeded diffusion fraction models for quantitative imaging diagnostic assay of cancer, such as glandular tissue cancers. The Impeded diffusion fraction models are tissue and cancer independent and generate a single score representative of multi-compartment diffusion fractions occurring within each voxel of a DWI image.

In a method for diffusion-weighted MR-imaging of an object, which undergoes a cyclic motion, a first sub-period type of the cyclic motion is predicted for a first acquisition timeframe, where the first sub-period type corresponds to one of two or more predefined characteristic types of sub-periods of the cyclic motion. A first amount of diffusion-weighting may be selected based on the first sub-period type. A first MR-acquisition may be carried out during the first acquisition timeframe, where a diffusion-weighting according to the first amount of diffusion-weighting is applied. An MR-image of the object is generated based on MR-data including a first MR-dataset obtained as a result of the first MR-acquisition.

An inventive computer-implemented method for creating correction data, which corrects measurement data missing in a measurement dataset recorded using a partial Fourier technique (PF technique), i.e. measurement data which was not recorded even though this is required in accordance with Nyquist for a complete measurement dataset, may include: receiving input data created on the basis of measurement data in the measurement dataset, applying at least one trained correction function to the input data to determine output data, and providing the output data. The output data may include correction information that corrects measurement data missing in the measurement dataset.

Calibration data is generated for completing undersampled measurement data acquired via a magnetic resonance system. This includes recording N measurement data sets using an acquisition scheme, and undersampling the k-space with an acceleration factor R, with N being greater than or equal to R, and the N measurement data sets together scanning the k-space completely. Phase images are generated from the N recorded measurement data sets, at least one homogeneity value of the created phase images is determined, and a complete calibration data set is generated based upon the recorded measurement data sets, taking into account the at least one homogeneity value. Thus, it is possible to determine which measurement data sets are subject to undesired phase errors, the measurement data sets used for the creation of the calibration data sets can be selected optimally, and input of the detected phase errors into the calibration data sets can be avoided.