A system for estimating a distance between vehicles may include an oscillator, a transmitter, a receiver, a summing circuit, a signal analyzer, a tunable phase shifter, a distance estimator, and/or a vehicle identifier. The oscillator may generate a generated oscillating signal, transmitted by the transmitter. The receiver may receive a processed signal derived by a system of a second vehicle. The summing circuit may add the generated oscillating signal to the received signal to produce the updated oscillating signal. The signal analyzer may detect a spike in amplitude associated with the updated oscillating signal. The tunable phase shifter may shift a phase of the generated oscillating signal by an incremental phase shift amount until a spike in amplitude is detected. The distance estimator may estimate the distance between the first vehicle and the second vehicle based on a total phase shift amount and the predetermined wavelength.

The invention provides for a method of operating a magnetic resonance imaging system for imaging a subject. The method comprises acquiring (700) tagged magnetic resonance data (642) and a first portion (644) of fingerprinting magnetic resonance data by controlling the magnetic resonance imaging system with tagging pulse sequence commands (100). The tagging pulse sequence commands comprise a tagging inversion pulse portion (102) for spin labeling a tagging location within the subject. The tagging pulse sequence commands comprise a background suppression portion (104). The background suppression portion comprises MRF pulse sequence commands for acquiring fingerprinting magnetic resonance data according to a magnetic resonance fingerprinting protocol. The tagging pulse sequence commands comprise an image acquisition portion (106). The method comprises acquiring (702) control magnetic resonance data (646) and a second portion (648) of the fingerprinting magnetic resonance data by controlling the magnetic resonance imaging system with control pulse sequence commands. The control pulse sequence commands comprise a control inversion pulse portion (202). The control pulse sequence commands comprise the background suppression portion (104′). The control pulse sequence commands comprise the image acquisition portion (106). The method comprises reconstructing (704) tagged magnitude images (650) using the tagged magnetic resonance data. The method comprises reconstructing (706) a control magnitude images (652) using the control magnetic resonance data. The method comprises constructing (708) an ASL image by subtracting the control magnitude images and the tagged magnitude images from each other. The method comprises reconstructing (710) a series of magnetic resonance fingerprinting images (656) using the first portion of the fingerprinting magnetic resonance data and/or the second portion of the fingerprinting magnetic resonance data. The method comprises generating (712) at least one magnetic resonance parametric map (658) by comparing the series of magnetic resonance fingerprinting images with a magnetic resonance fingerprinting dictionary.

Provided is a new scheme for applying a CS technology in a technology for imaging a target tissue based on a difference from a reference image or a control image. In this way, an imaging time is shortened. A measurement unit of an MRI apparatus executes a first imaging sequence and a second imaging sequence having different contrasts for a target, and measures a nuclear magnetic resonance signal from a subject in each of the imaging sequences. In the second imaging sequence, under-sampling is performed, and a nuclear magnetic resonance signal having a small number of samples is measured. The image processing unit restores measurement data including a nuclear magnetic resonance signal obtained by under-sampling using compressed sensing. At this time, data restoration including a term for minimizing an L1 norm is performed for a difference image between an image obtained by execution of the first imaging sequence and an image obtained by execution of the second imaging sequence.

The present invention includes a computerized method of detecting fluid flow in a vessel, the method comprising: obtaining at least one non-contrast enhanced magnetic resonance image from a magnetic resonance imager; performing a phase sensitive reconstruction of the at least one non-contrast enhanced magnetic resonance image using a processor; combining the phase sensitive reconstruction with a velocity selective preparation of the non-contrast enhanced magnetic resonance image, to determine using the processor, in a single acquisition, at least one of: a flow direction of a fluid in the vessel, a reduction or elimination of a background signal, body fat, water/fat separation, or differentiation of a fast moving flow signal from a slow moving flow signal in an opposite direction with suppression of the background signal; and storing or displaying at least one of flow direction or flow strength of the fluid flow in the vessel obtained from the single acquisition.

A method of processing magnetic resonance (MR) data of a sample under investigation, includes the steps of providing the MR data being collected with an MRI scanner apparatus, and subjecting the MR data to a multi-parameter nonlinear regression procedure being based on a non-linear MR model and employing a set of input parameters, wherein the regression procedure results in creating a parameter map of model parameters of the sample, wherein the input parameters (initial values and possibly boundaries) of the regression procedure are estimated by a machine learning based estimation procedure applied to the MR data. The machine learning based estimation procedure preferably includes at least one of at least one neural network and a support vector machine. Furthermore, an MRI scanner apparatus is described.

A method for determining MRI biomarkers for in vivo issue includes the steps of obtaining raw data concerning the in vivo tissue from a MRI machine; processing the raw data to obtain parameter maps; when applicable, registering images such that the exact same tissue at serial points can be analyzed; applying a grid over a region of interest to create sub-regions of interest (SROIs); inserting parameter measures for each SROI into a spreadsheet program to create a large 3D data matrix; applying standard big-data analytics including data mining and statistics of matrix measures to find patterns of measurement values or measure changes (which may include established biomarkers). A medical imaging software program is used to obtain the parameter maps from the raw data and place multiple grids over the SROIs. 3D matrix measures may be data mined and analyzed using standard big-data analytics.

In the field of MRI, a model-based MRI image reconstruction technique is provided. The model-based reconstruction technique increases the performance of Time-of-Flight MRA. In a learning phase, a model is calculated from a sufficiently large set of data acquired at both low and high magnetic fields, using deep learning strategies. In a clinical phase, the model is applied to measured data generating high MR image quality.

Devices, systems, and methods for visually depicting a vessel and evaluating a physiological condition of the vessel are disclosed. One embodiment includes obtaining, at a first time, a first image of the vessel, the image being in a first medical modality, and obtaining, at a second time subsequent to the first time, a second image of the vessel, the image being in the first medical modality. The method also includes spatially co-registering the first and second images and outputting a visual representation of the co-registered first and second images on a display. Further, the method includes determining a physiological difference between the vessel at the first time and the vessel at the second time based on the co-registered first and second images, and evaluating the physiological condition of the vessel of the patient based on the determined physiological difference.

The present application provides a system and method for quantifying perfusion using a dictionary matching approach. In some aspects, the method comprises performing a predetermined pulse sequence using an MRI system to acquire MRI data from the subject after having delivered a dose of a contrast agent to the subject. The method also includes comparing the MRI data to a dictionary to determine perfusion information, and generating, using the perfusion information, a report indicative of perfusion within the subject.

A magnetic resonance imaging apparatus according to one embodiment includes sequence control circuitry and processing circuitry. The sequence control circuitry performs a first data acquisition for chemical shift measurement and a second data acquisition for either chemical shift measurement or MR imaging, which differs from chemical shift measurement, on the same subject under certain conditions that differ between those data acquisitions. The processing circuitry performs medical data classification on the subject based on first MR data obtained through the first data acquisition and second MR data obtained through the second data acquisition.