An ultrasound diagnostic apparatus 1 includes: a data acquisition unit 3 that repeatedly transmits an ultrasound beam to a subject a plurality of times in a range over a plurality of scanning lines to acquire a time-series data string of reflected waves from the subject; an analysis target data selection unit 7 that estimates the amount of relative positional deviation of a scatterer of the subject which is included in the time-series data string and excludes time-series data satisfying an exclusion condition based on the amount of positional deviation of the scatterer from the time-series data string to select analysis target data; an MTI filter unit 8 that removes a clutter component from the analysis target data; and a blood flow information estimation unit 9 that analyzes the analysis target data from which the clutter component has been removed to estimate blood flow information of the subject.

Devices, systems, and methods of imaging a blood vessel are provided. For example, the method can include obtaining fluoroscopic image data of a region of interest in a blood vessel using an x-ray source; obtaining intravascular ultrasound (IVUS) data at a plurality of positions across the region of interest using an IVUS component disposed on an intravascular device; processing the fluoroscopic image data and IVUS data, including: determining, using the fluoroscopic image data, a position of the intravascular device with respect to the x-ray source at each of the plurality of positions across the region of interest; co-registering the fluoroscopic image data and the IVUS image data; and generating, a model of the region of interest including position information of a border of a lumen of the blood vessel at each of the plurality of locations; and outputting a visual representation of the model of the region of interest.

An ultrasound imaging system may acquire short and/or undersampled radiofrequency ensembles for generating color Doppler images. The ultrasound imaging system may process the short and/or undersampled ensembles to simulate color Doppler images acquired from long radiofrequency ensembles. In some examples, the ultrasound imaging system may include a neural networks to process the ensembles. In some examples, the neural network may include two serial neural networks. In some examples, during training of the neural network, a power Doppler-based flow mask may be used on the output of the neural network. In some examples, during training of the neural network, an adversarial loss may be used on the output of the neural network.

An ultrasound imaging device and a clutter filtering method using the same are disclosed. The clutter filtering method using the ultrasound imaging device according to one embodiment includes obtaining ultrasound data from a field-of-view (FOV) of an object, generating decomposition data including common scale information by performing rank matrix decomposition once on all of the obtained ultrasound data, estimating local characteristic information by reflecting spatial information on each pixel to the common scale information, and extracting a blood flow signal by performing filtering on each pixel based on the estimated local characteristic information.

The invention provides an ultrasound imaging apparatus capable of highly accurately extracting a blood flow in a fine blood vessel in a short time. N pieces of frame data is generated by receiving ultrasound waves reflected by a subject with a plurality of transducers. A correlation matrix is generated based on a vector in which data at a corresponding position of the frame data is arranged for N frames, and a singular value and a singular vector for each of N ranks are calculated. A first filter element is calculated based on a variance between data at a corresponding position zx among a plurality of blood flow component frame data obtained by multiplying a plurality of the frame data by singular vectors at a threshold rank k or more. The second filter element is calculated based on the tissue component frame data obtained by multiplying the frame data by a singular vector at a rank 1. The frame data is weighted by the first filter element and/or the second filter element to generate a clutter reducing image.

A clutter signal mixed in a blood flow signal is reduced in a color Doppler, and blood flow visibility is improved. A combination of parameters that maximize a difference between a blood flow and a clutter (a signal other than the blood flow) is determined by analyzing a reception signal, a clutter estimated value (a value indicating a degree of being estimated as a clutter) is set based on the combination, and a reduction coefficient map (hereinafter, simply referred to as a reduction map) that reduces a clutter signal is generated based on the estimated value. The clutter signal is reduced by multiplying the reception signal (an IQ signal after quadrature detection) by the reduction map.

An ultrasound diagnosis apparatus according to an embodiment includes processing circuitry. The processing circuitry is configured: to generate a piece of reflected-wave data by performing a phased addition process while using reflected-wave signals generated by transmitting an ultrasound wave with respect to mutually the same scanning line; to speculate a degree of saturation of the reflected-wave signals observed before the phased addition process on the basis of a relationship between signals and noise in a data sequence represented by a set made up of pieces of the reflected-wave data; and to output a result of the speculation. The processing circuitry is configured to cause a display to display data based on the result of the speculation.

An ultrasound diagnostic apparatus including a hardware processor that: calculates a plurality of eigenvectors by performing principal component analysis on a time-series reflection wave data group; calculates a principal frequency component of a time direction represented by the plurality of eigenvectors; determines a reduction rate of each of the plurality of eigenvectors on a basis of the principal frequency component of each of the plurality of eigenvectors and a clutter component reduction condition that defines a reference frequency for reduction of a clutter component; calculates a filter coefficient for reduction of the clutter component on a basis of the plurality of eigenvectors, and the reduction rate corresponding to each of the plurality of eigenvectors; and generates blood flow image data by applying the filter coefficient to the time-series reflection wave data group.

Described here are systems and methods for ultrasound clutter filtering to produce images of blood flow in a subject. The systems and methods described in the present disclosure may be advantageously applied to fast ultrasound imaging techniques, including ultrafast plane wave imaging techniques.

A method includes emitting an ultrasound beam from an array of ultrasound transducers in a catheter placed in a blood pool in an organ. Echo signals reflected in response to the ultrasound beam are received in the array. Distinction is made in the echo signals between (i) first spectral signal components having Doppler shifts characteristic of blood and (ii) second spectral signal components having Doppler shifts characteristic of tissue of the organ. The first spectral signal components are suppressed relative to the second spectral signal components in the echo signals. An ultrasound image of at least a portion of the organ is reconstructed from the echo signals having the suppressed first spectral signal components. The reconstructed image is displayed to a user.