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.

Systems and methods for data transmission may be provided. The system may at least include a data transmission module. The system may obtain MR signals from one or more RF coils. The system may generate, via a first portion of the data transmitting module, first data based on the MR signals. The system may generate, via a second portion of the data transmitting module, second data based on the first data. The second portion of the data transmitting module may connect to the first portion of the data transmitting module wirelessly. The system may further store the second data in a non-transitory computer-readable storage medium.

Systems and methods are disclosed for assessing the quality of medical images of at least a portion of a patient's anatomy, using a computer system. One method includes receiving one or more images of at least a portion of the patient's anatomy; determining, using a processor of the computer system, one or more image properties of the received images; performing, using a processor of the computer system, anatomic localization or modeling of at least a portion of the patient's anatomy based on the received images; obtaining an identification of one or more image characteristics associated with an anatomic feature of the patient's anatomy based on the anatomic localization or modeling; and calculating, using a processor of the computer system, an image quality score based on the one or more image properties and the one or more image characteristics.

Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.

Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.

Described here are systems and methods for reconstructing images from multi-level sampled data acquired with a magnetic resonance imaging (MRI) system. An alternating direction method-of multipliers (ADMM) strategy is implemented for sparse reconstruction of multi-level sampled data, and which decomposes the reconstruction problem into simpler subproblems and enables certain operations to be computed once offline and recycled during the reconstruction process rather than repeated at every iteration. As one example, the described reconstruction technique enables sparse reconstruction of 3D contrast-enhanced MR angiogram time-series in just several minutes rather than the several hours previously required.

Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.

Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patients heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.

A method of magnetic resonance imaging (100, 200) includes acquiring (300) tagged magnetic resonance data (144) by controlling the magnetic resonance imaging system with tagging pulse sequence commands (140). The tagging pulse sequence commands include a tagging inversion pulse portion (404) for spin labeling a tagging location (122, 122) within a subject (118). The tagging pulse sequence commands comprise a phase-contrast readout portion (406) which phase-contrast encodes in at least one direction. The control pulse sequence commands include a control inversion pulse portion (500) and the phase-contrast readout portion. A tagged magnitude image (148) is reconstructed (304) using the tagged magnetic resonance data. A control magnitude image (150) is reconstructed (306) using the control magnetic resonance data. An arterial image (152) is reconstructed (308) by subtracting the control magnitude image and the tagged magnitude image. At least one phase image (156, 158, 160) is reconstructed (312) using either the tagged magnetic resonance data and/or the control magnetic resonance data.

A magnetic resonance imaging apparatus according to an embodiment includes sequence control circuitry and processing circuitry. The sequence control circuitry executes two pulse sequences, thereby acquiring two pieces of data, each of the two pulse sequences being a pulse sequence in which the sequence control circuitry acquires data after applying a short inversion time recovery (STIR) pulse while concurrently applying a gradient magnetic field for spatial selection and each of the two pulse sequences being executed in two different timings by the sequence control circuitry. The processing circuitry generates an image by performing a subtraction processing between the two pieces of data acquired by the sequence control circuitry.