Techniques for co-imaging tissue stiffness and blood flow using a single MRI scan are disclosed. The methods use a combined gradient waveform that provides adequate sensitivity for concurrent encodings of flow and tissue stiffness. During a scan, the application of the combined gradient waveform, in the presence of an applied oscillatory motion, simultaneously encodes both flow and stiffness information into the phase of the resulting MRI image. To separate the flow information from the tissue displacement caused by the oscillatory motion, a Fourier transform applied along the direction of applied oscillatory motion. After the transformation, baseband information (flow velocity) may be separated from modulated information (tissue displacement). The separated data may be used to create a velocity map and a displacement map, which can then be converted to a stiffness map.

A method and system for image reconstruction are provided. A projection image of a projection object may be obtained. A processed projection image may be generated based on the projection image through one or more pre-process operations. A reconstructed image including an artifact may be reconstructed based on the processed projection image. The artifact may be a detector edge artifact, a projection object edge artifact, and a serrated artifact. The detector edge artifact, the projection object edge artifact, and the serrated artifact may be removed from the reconstructed image.

A computer-implemented method of visualizing blood flow through a patient using magnetic resonance imaging (MRI) includes receiving an image of the portal venous system of the patient's liver at a full field of view. A reduced field of view is defined which encompasses the portal venous system of the patient's liver and excludes extraneous anatomy in the full field of view. A navigator area is defined in the full field of view and outside of the reduced field of view. Transmit channels are used to selectively excite the reduced field of view and the navigator area throughout a cardiac cycle of the patient. Measurement data is acquired in response to the selective excitation. The acquired data is used to generate time-resolved 3D datasets. Additionally, a 3D visualization of blood flow though the portal venous system is generated based on the time-resolved 3D datasets.

A magnetic resonance imaging (MRI) system, method and/or computer readable medium is configured to effect magnetic resonance angiography (MRA) images with reduced motion artifacts includes acquiring a plurality of k-space data sets by traversing a plurality of radial trajectories in three-dimensional (3D) k-space, generating a plurality of 3D MR images derived from k-space populated by the k-space data sets, aligning the 3D MR images with respect to each other, determining one or more motion parameters for the object based upon the aligning, modifying values of k-space data sets using the determined one or more motion parameters, generating a motion-corrected 3D MR image from a combination of acquired k-space data sets including the modified values.

Provided is an MRI apparatus. In the MRI apparatus, a data collection unit repetitively performs a tag mode of applying an RF wave to at least an upstream portion of an imaging area to perform fluid labeling of a fluid flown into the imaging area and, after a lapse of an inversion time from application of the RF wave, performing magnetic resonance data collection, while changing the inversion time. An image reconstruction unit reconstructs a plurality of tag images corresponding to a plurality of different inversion times based on the magnetic resonance data collected in the tag mode. A reference image generation unit generates a reference image based on the plurality of the tag images. A fluid image generation unit generates a subtraction image between each of the tag images and the reference image as a fluid image.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing EEG source localization. One of the methods includes obtaining brain data comprising: EEG data comprising respective channel data corresponding to each of a plurality of electrodes of an EEG sensor, and fMRI data comprising respective voxel data corresponding to each of a plurality of voxels; identifying, in a three-dimensional coordinate system, a respective location for each electrode; generating, using the respective identified locations of each electrode, data representing a location in the three-dimensional coordinate system of each voxel; determining, for each electrode, a region of interest in the three-dimensional coordinate system; and identifying, for each electrode, one or more corresponding parcellations in the brain of the subject, wherein each parcellation that corresponds to an electrode at least partially overlaps with the region of interest of the electrode.

In order to achieve a prediction approximating an actual change with time of a pixel value in a tissue with higher accuracy, provided is a simulator, which is configured to predict a change with time of a pixel value in a tissue of an object, including: an object information acquisition unit configured to acquire information on the object; a protocol acquisition unit configured to acquire an injection protocol for a contrast medium; a tissue information acquisition unit configured to acquire information on the tissue; and a prediction unit configured to predict, based on the information on the object, the injection protocol, and the information on the tissue, a change with time of a pixel value of each of a plurality of compartments obtained by dividing the tissue along a blood flow direction.

3D cine MR angiography systems and methods are disclosed for use during the steady state intravascular distribution phase of ferumoxytol. The 3D cine MRA technique enables improved delineation of cardiac anatomy in pediatric patients undergoing cardiovascular MRI.

A method and system for determining hemodynamic indices, such as fractional flow reserve (FFR), for a location of interest in a coronary artery of a patient is disclosed. Medical image data of a patient is received. Patient-specific coronary arterial tree geometry of the patient is extracted from the medical image data. Geometric features are extracted from the patient-specific coronary arterial tree geometry of the patient. A hemodynamic index, such as FFR, is computed for a location of interest in the patient-specific coronary arterial tree based on the extracted geometric features using a trained machine-learning based surrogate model. The machine-learning based surrogate model is trained based on geometric features extracted from synthetically generated coronary arterial tree geometries.

Described herein is a method to detect perfusion and brain functional activity using Hyperpolarized xenon-129 (.sup.129Xe) Time-of-Flight (TOF) Magnetic Resonance Imaging (MRI). Specifically, this method uses hyperpolarized .sup.129Xe MRI to detect blood flow and perfusion changes in the region of interest. In addition, this method can be used to detect blood flow changes in brain tissue that corresponds to the brain functional activities by detecting the amount of .sup.129Xe dissolved in blood and brain tissue per unit of time.