A method of performing personalized neuromodulation on a subject is provided. The method includes acquiring functional magnetic resonance imaging (fMRI) data of a brain of the subject. The method also includes calculating functional connectivity of the brain between a voxel in a subcortical region of the brain and a voxel in a cortical region of the brain, based on the fMRI data. The method also includes identifying a target location in the brain to be targeted by neuromodulation based on the calculated functional connectivity.

Described here are systems and methods for separating magnetic resonance signals that are changing over a scan duration (i.e., dynamic signals) from magnetic resonance signals that are static over the same duration. As such, the systems and methods described in the present disclosure can be used to remove artifacts associated with dynamic signals from images of static structures, or to better image the dynamic signal (e.g., pulsatile blood flow or respiratory motion).

A magnetic resonance imaging apparatus according to an embodiment includes sequence controlling circuitry and processing circuitry. The sequence controlling circuitry is configured to execute (i) a first pulse sequence in which a spatially selective Inversion recovery (IR) pulse and a spatially non-selective IR pulse are applied, and subsequently an acquisition is performed and (ii) a second pulse sequence in which the spatially non-selective IR pulse is applied without applying the spatially selective IR pulse, and subsequently an acquisition is performed, while varying the first TI period, with respect to a plurality of first TI periods. The processing circuitry is configured to calculate a second TI period to be used in a third pulse sequence and a fourth pulse sequence, based on data obtained from the first pulse sequence and the second pulse sequence. 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 subsequently an acquisition is performed and (iv) the fourth pulse sequence in which the spatially non-selective IR pulse is applied without applying the spatially selective IR pulse, and subsequently an acquisition is performed. 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.

The invention relates to a method of Dixon-type MR imaging. It is an object of the invention to provide a method that enables efficient and reliable Dixon water/fat separation, in particular using a bipolar acquisition strategy, while avoiding flow-induced leakage and swapping artifacts. According to the invention, an imaging sequence is executed which comprises at least one excitation RF pulse and switched magnetic field gradients, wherein pairs of echo signals are generated at two different echo times (TE1, TE2) and during two or more different cardiac phases (AW1, AW2). The echo signals are acquired and phase images are reconstructed therefrom. A final diagnostic image is reconstructed from the echo signal data using water/fat separation, wherein regions of flow and/or estimates of flow- induced phase errors are derived from the phase images to suppress or compensate for flow- induced leakage and/or swapping artifacts in the final diagnostic image. Therein, flow- induced phase offsets are determined by voxel-wise comparison of the phase images associated with the different cardiac phases. Moreover, the invention relates to a MR device (1) and to a computer program to be run on a MR device (1).

Disclosed are a system, method, and computer program product for generating pruned tractograms of neural fiber bundles. The method includes receiving scan data produced by diffusion imaging of at least a portion of a brain from a magnetic-resonance imaging (MRI) device. The method also includes generating an initial tractogram by mapping neuronal fiber pathways of a target fiber bundle of the scan data. The method further includes generating a density map using a set of tracts from the initial tractogram, identifying each tract that passes through a segment of the density map more than once, and setting a contribution of said tract to a unique tract count of the segment equal to a threshold pruning value. The method further includes generating a pruned tractogram by identifying a segment having a unique tract count less than or equal to the threshold pruning value and excluding the segment from the pruned tractogram.

A Computer-implemented method of reconstructing a dynamic series of motion-compensated magnetic resonance images of a patient is provided. Images of a patient are acquired over time, at least partially in free-breathing, at a first image resolution and on a frame-by-frame basis. Each frame of the k-space data includes a first subset of data points having a first sample density and a second subset of data points having a second sample density. For each frame, a sub-group of the first subset and the second subset of the k-space data is selected, and an image is reconstructed at a second image resolution. The motion between the second image resolution images is estimated in the form of motion fields. The motion information is incorporated into a final reconstruction of a dynamic series of motion-compensated magnetic resonance images of the patient at a third image resolution.

Systems and methods are provided for performing automated reconstruction of a dynamic MRI dataset that is acquired without a fixed temporal resolution. On one or more image quality metrics (IQMs) are obtained by processing a subset of the acquired dataset. In one example implementation, at each stage of an iterative process, one or more IQMs of the image subset is computed, and the parameters controlling the reconstruction and/or the strategy for data combination are adjusted to provide an improved or optimal image reconstruction. Once the IQM of the image subset satisfies acceptance criteria based on an estimate of the overall temporal fidelity of the reconstruction, the full reconstruction can be performed, and the estimate of the overall temporal fidelity can be reported based on the IQM at the final iteration.

A patient couch for a magnetic resonance tomography system and a magnetic resonance tomography system are provided. The patient couch includes a feed facility for radiofrequency energy having a plurality of conduction paths for feeding radiofrequency energy. The patient couch also includes a plurality of plug-in connectors for local coils having a transmit coil, and a distribution structure for the distribution of radiofrequency energy from the feed facility to the plug-in connectors.

A patient couch for a magnetic resonance tomography system and a magnetic resonance tomography system are provided. The patient couch includes a feed facility for radiofrequency energy having a plurality of conduction paths for feeding radiofrequency energy. The patient couch also includes a plurality of plug-in connectors for local coils having a transmit coil, and a distribution structure for the distribution of radiofrequency energy from the feed facility to the plug-in connectors.

In a method and magnetic resonance (MR) apparatus for establishing imaging sequence parameter values with a reduced eddy current formation for flow-encoded magnetic resonance imaging, a number of different flow-encoded candidate raw datasets are acquired by executing a flow-encoded gradient measurement sequence with different imaging sequence parameter values from a test or calibration region of an examination object. Flow-encoded candidate image datasets are reconstructed from the different flow-encoded candidate raw datasets. A flow-encoded candidate image dataset is selected as a function of a background phase contrast established in a phase-contrast image assigned to the respective flow-encoded candidate image dataset. The imaging sequence parameter values assigned to the flow-encoded candidate image dataset are selected as parameter values for an imaging sequence for subsequent diagnostic flow-encoded magnetic resonance imaging.