A magnetic resonance imaging apparatus includes sequence controlling circuitry and processing circuitry. The sequence controlling circuitry executes (i) a first pulse sequence in which a spatially selective Inversion recovery (IR) pulse and a spatially non-selective IR pulse are applied, and (ii) a second pulse sequence in which the spatially non-selective IR pulse is applied without applying the spatially selective IR pulse, while varying the first TI period, with respect to a plurality of first TI periods. The sequence controlling circuitry executes (iii) the third pulse sequence in which the spatially selective IR pulse and the spatially non- selective IR pulse are applied, and (iv) the fourth pulse sequence in which the spatially non-selective IR pulse is applied without applying the spatially selective IR pulse. The processing circuitry generates a magnetic resonance image of an imaged region based on data obtained from the third pulse sequence and the fourth pulse sequence.

A method for determining a brain age, the method comprising the following: providing a brain age determining convolutional neural network (CNN) (200); training the CNN (200) to determine the brain age based on a plurality of sets of input data comprising magnetic resonance imaging (MRI) scans of a brain, the set comprising at least two types of MRI volumes, wherein the at least one type of brain tissue on the first type of the MRI volume is represented by a different contrast with respect to other tissues than on a second type of the MRI volume; and performing an inference process using the trained CNN (200) to determine the brain age based on the set of input data comprising magnetic resonance imaging (MRI) scans of a brain, the set comprising at least the two types of the MRI volumes as used for the training.

A method for applying a diffusion-weighting gradient during acquisition of diffusion-weighted imaging signals from a selected portion of a nervous system of a subject. Planar diffusion-weighted spin-echo (DWSE) imaging signals and planar diffusion-weighted stimulated-echo (DWSTE) imaging signals can be obtained to provide a plurality of sets of imaging signals. At least one set of imaging signals includes DWSTE signals that are associated with a high-b-value. A signal difference between DWSE imaging signals and DWSTE imaging signals can be corrected based on respective sets of DWSE imaging signals and DWSTE imaging signals having b-values at or near zero.

A magnetic resonance imaging apparatus according to an embodiment includes sequence control circuitry and processing circuitry. The sequence control circuitry performs multi-frame acquisition where FOVs (Field Of Views) of at least two acquired frames are overlapped in a first direction. Then, based on the multi-frame acquisition performed by the sequence control unit, the processing unit generates data regarding the components in the first direction of flow of a fluid.

A magnetic resonance imaging apparatus according to an embodiment includes sequence control circuitry and processing circuitry. The sequence control circuitry performs multi-frame acquisition where FOVs (Field Of Views) of at least two acquired frames are overlapped in a first direction. Then, based on the multi-frame acquisition performed by the sequence control unit, the processing unit generates data regarding the components in the first direction of flow of a fluid.

Techniques are disclosed for capturing scan data of an examination object via a magnetic resonance system. The techniques include capturing a first set of a diffusion-weighted scan data by excitation and, in an acquisition phase, acquiring a first echo signal, wherein before the acquisition phase in a diffusion preparation phase, diffusion gradients are switched for diffusion encoding of the scan data, The techniques additionally include capturing a second set of non-diffusion-weighted scan data by excitation and, in an acquisition phase, acquiring a second echo signal, wherein before the acquisition phase, in a diffusion preparation phase, the same diffusion gradients are switched as are switched for diffusion encoding of the scan data of the first set of diffusion-weighted scan data, although they have no influence on the second echo signal. Diffusion-weighted and non-diffusion-weighted scan data is thereby captured, having identical disturbances caused by eddy currents induced by switched gradients.

The present invention relates to the locally resolved examination of objects by means of magnetic resonance (MR) and relates specifically to a less motion-artifact prone method for navigated multi-shot acquisition of diffusion-weighted image data using moment-nulled magnetic field gradients for diffusion encoding. The invention further relates to an apparatus for performing the method.

The disclosure provides a diffusion kurtosis imaging method, which includes acquiring scan image signals of a scanned object; fitting the scan image signals using an unconstrained optimization algorithm to obtain elements of a first diffusion tensor and elements of a first kurtosis tensor; determining at least one type of parameters of diffusion tensor imaging parameters or kurtosis tensor imaging parameters based on the elements of the first diffusion tensor and the elements of the first kurtosis tensor; and generating a parameter image based on the at least one type of parameters of diffusion tensor imaging parameters or kurtosis tensor imaging parameters.

The present disclosure is related to systems and methods for image processing. The method includes obtaining an original image. The original image includes at least one blood vessel region and at least one scalp region. The method includes determining an intermediate image by removing the at least one scalp region from the original image. The method includes generating at least one target image by performing a maximum intensity projection operation on the intermediate image. The at least one target image represents the at least one blood vessel region in the original image.

Techniques for correcting gradient non-linearity bias in mean diffusivity measurements by MRI systems are shown and include minimal number of spatial correction terms to achieve sufficient error control using three orthogonal diffusion weighted imaging (DWI) gradients. The correction is based on rotation of system gradient nonlinearity tensor into a DWI gradient frame where spatial bias of b-matrix is described by its Euclidian norm. The techniques obviate time consuming multi-direction acquisition and noise-sensitive mathematical diagonalization of a full diffusion tensor for medium of arbitrary anisotropy.