A method comprising: providing an autonomous vehicle (AV) with a first estimated position of a target; directing the AV to travel toward the first estimated position at a constant velocity; receiving echo signals of transmitted sonar signals, the echo signals indicating a range and an azimuth of the target; determining a depth difference of the AV and the target based on the received echo signals, the depth difference being determined based on changes to the range and azimuth of the target over time; and in response to a depth difference existing, re-directing the AV toward a second estimated position of the target generated from the depth difference.

An ultrasound diagnosis apparatus according to an embodiment includes processing circuitry. The processing circuitry is configured to sequentially obtain eigenvalues of a correlation matrix of a scan range, the correlation matrix being obtained from a data sequence of reflected-wave data in mutually the same position acquired by performing an ultrasound scan on the scan range formed with a plurality of scanning lines. The processing circuitry is configured to determine a filter coefficient to be applied to a Moving Target Indicator (MTI) filter, on a basis of the plurality of eigenvalues obtained at mutually-different points in time.

Ultrasound image devices, systems, and methods are provided. An ultrasound imaging system, comprising an intraluminal imaging device including an ultrasound transducer array configured to obtain first signal data and second signal data representative of a body lumen, the first signal data and the second signal data associating with different imaging modes of the ultrasound transducer array; and a processor in communication with the intraluminal imaging device and configured to generate motion data of a flow within the body lumen based on the first signal data; generate structural data of the body lumen based on the second signal data; combine the motion data and the structural data based on a first threshold; and output, to a display in communication with the processor, an intraluminal ultrasound image representing the combined motion data and structural data.

An ultrasonic imaging system acquires frames of echo data at a high acquisition frame rate using a single mode of acquisition. The echo data is used by three image processors to produce an anatomical image, a mechanical function image, and a hemodynamic image from the same echo data. A display displays an anatomical image, a mechanical function image, and a hemodynamic image simultaneously.

Described here are systems and methods for imaging blood flow in a subject's vasculature, which may include small blood vessels, using ultrasound without the need for a contrast agent. A locally implemented low-rank matrix decomposition is used together with adaptive cutoff values to provide noninvasive ultrasound blood flow imaging capable of imaging the subject's vasculature with very high spatial and temporal resolution, and without the administration of contrast agents such as microbubble contrast agents. Thus, in some instances the systems and methods can be used to image blood flow in small vessels and tissue microvasculature with high spatial and temporal resolution.

An ultrasound system that includes a transducer configured to acquire ensemble channel/echo data and a filter bank configured to receive the echo data from the transducer, wherein the echo data is passed through a plurality of clutter filters within the filter bank to realize a plurality of echo data outputs. A processor calculates a spatial coherence value from each of the plurality of echo data outputs, compares the spatial coherence values of each filter, and selects the filter that yields a best spatial coherence for subsequent velocity estimation used to generate an output image for clinical use, where the best spatial coherence value is a highest and best spatial coherence value among the set of spatial coherence values.

A Doppler measurement system includes a random generator outputting a control signal encoding a random selection, and an ultrasonic array transducer for emitting a sequence of transmit pulses at a target at either an adjustable steering angle (plane wave imaging) or from a selectable non-sequential transducer element order (synthetic aperture imaging) corresponding to the random selection and for receiving an echo of each transmit pulse reflected from the target. Each transmit pulse is independently adjusted to a steering angle (plane wave imaging) or selectable transducer element order (synthetic aperture imaging) corresponding to a unique random selection so that the sequence of transmit pulses is a random sweep. The system can also include a memory for storing echo data, and a processor connected to the memory for using transmit data and echo data to extract a Doppler parameter. Methods of Doppler measurement and computer-readable medium can incorporating the measurement system.

Described herein are methods and apparatus for increasing sensitivity of ultrasound imaging of fluid flow in an object of interest. Ultrasound imaging of blood perfusion can be performed without contrast enhancement. Embodiments include transforming a spatiotemporal echo data array into a three-dimensional perfusion data array having a spatial dimension, a slow-time dimension, and a frame-time dimension, and filtering the perfusion data array with an eigen passband clutter filter. The clutter filter can increase sensitivity and utility of ultrasound imaging of fluid flow. In some aspects, the method can yield blood flow signal power and perfusion values well separated from tissue clutter. In an example, enhancements to ischemic tissue perfusion maps in a murine model are shown.

An ultrasound signal processing device that generates, for each detection wave, a first complex Doppler signal sequence through quadrature detection of a reception signal sequence; generates tissue velocity data by calculating velocity values for each set of coordinates of observation points in a region of interest from the first complex Doppler signal sequence; generates a second complex Doppler signal sequence by performing clutter removal filter processing on the first complex Doppler signal sequence; generates first velocity data by calculating velocity values for each set of coordinates of the observation points from the second complex Doppler signal sequence; and generates, for each set of coordinates of the observation points, second velocity data based on the first velocity data and the tissue velocity data, and third velocity data by applying a correction to velocity values of the second velocity data that have an absolute value equal to or less than a threshold.

Systems and methods for removing the bias induced by noise from power Doppler images to achieve improvements of microvessel image contrast are provided. In one example, the noise-induced bias can be suppressed by utilizing the characteristics of uncorrelated noise in the ultrasound image from data acquired or compounded at different transmitting angles. In another example, the noise-induced bias can be suppressed due to the lack of correlation between adjacent ultrasound images. These example implementations may also be combined, as will be described below.