Systems, devices, and methods for sparse synthetic aperture ultrasound (SSAU) imaging and/or range-Doppler applications are described. An example method for SAU imaging includes receiving, via a user interface, an input including an array topology comprising a particular N-dimensional arrangement of a plurality of transducer elements of the SAU system, an objective space, a function characterizing an imaging capability of the SAU system, and one or more constraints, generating, based on the input, an acoustic field over the objective space for each of the plurality of transducer elements of the array topology, selecting one or more transducer elements from the plurality of transducer elements of the array topology based on evaluation of the function, and providing for display, on the user interface, the selected one or more transducer elements that satisfy each of the one or more constraints.

Systems and methods for harmonic shear wave detection using low frame rate ultrasound, or a three-dimensional (3D) volumetric scan, are provided. As one example, spurious motion sources, such as intrinsic tissue motion and waves that are not at the incident wave harmonic frequency, are removed based on a scanning sequence in which repeated acquisitions from a given subvolume occur closely in time so as to render effects of the spurious motions negligible. As another example, sampling frequency and center frequency are selected such that the spurious motion signal spectra do not overlap with aliased shear wave motion spectra, such that the spurious motions can be filtered.

A three-dimensional geometric image of an anatomical region is generated from a plurality of two-dimensional echographic image slices of the region. The image slices are filtered using a reaction-diffusion partial differential equation model before being arranged into a voxel space. Each voxel is then assigned a voxel value to create a volumetric data set from which the volumetric image can be rendered. The image is rendered from far to near, relative to a preset viewing direction, by an alpha-blending process. The alpha value at any given voxel can be determined using the magnitude of the density gradient vector at that voxel. Similarly, the direction of the density gradient vector at a given voxel can be used as a surface normal vector for shading purposes at that voxel.

The invention relates to an ultrasonic method for estimating a nonlinear shear wave elasticity of a medium, the method comprising the following steps: A1. a first collection step in which a first set comprising one shear wave elasticity data point of the medium is collected at a first level of deformation applied to the medium, A2. a second collection step in which a second set comprising one shear wave elasticity data point of the medium is collected at a second level of deformation applied to the medium different to the first level, A3. a deformation estimation step in which the difference of deformation between the first and the second level of deformation is estimated, B1. a calculation step in which a gradient between at least two data points respectively belonging to the first and the second set is calculated as a function of the difference of deformation between the first and the second level of deformation, B2. an elasticity estimation step in which the nonlinear shear wave elasticity of the medium is estimated as a function of the gradient.

An ultrasonic diagnostic imaging system is used to acquire a fetal image in a sagittal view for the performance of a nuchal translucency measurement. After a fetal image has been acquired, a zoom box is positioned over the image, encompassing a region of interest. The size of the zoom box is automatically set for the user in correspondence with gestational age or crown rump length. The system automatically tracks the region of interest within the zoom box in the presence of fetal motion in an effort to maintain the region of interest within the zoom box despite movement by the fetus.

The ultrasonic diagnostic apparatus according to the present embodiment includes processing circuitry. The processing circuitry is configured to: acquire multiple position data associated with respective multiple two-dimensional image data of ultrasonic related to multiple cross sections; smooth the acquired multiple position data; and arrange the multiple two-dimensional image data in accordance with the smoothed multiple position data to generate volume data.

A system is provided for augmenting a three-dimensional (3D) model of a heart to indicate the tissue state. The system accesses a 3D model of a heart, accesses two-dimensional (2D) images of tissue state slices of the heart, and accesses source location information of an arrhythmia. The system augments the 3D model with an indication of a source location based on the source location information. For each of a plurality of the tissue state slices of the heart, the system augments a 3D model slice of the 3D model that corresponds to that tissue state slice with an indication of the tissue state of the heart represented by the tissue state information of that tissue state slice. The system then displays a representation of the 3D model that indicates the source location of the arrhythmia and the tissue state of the heart.

A downloadable navigator for a mobile ultrasound unit having an ultrasound probe, implemented on a portable computing device. The navigator includes a trained orientation neural network to receive a non-canonical image of a body part from the mobile ultrasound unit and to generate a transformation associated with the non-canonical image, the transformation transforming from a position and rotation associated with a canonical image to a position and rotation associated with the non-canonical image; and a result converter to convert the transformation into orientation instructions for a user of the probe and to provide and display the orientation instructions to the user to change the position and rotation of the probe.

Aspects described herein disclose devices, systems, and methods for use in contexts such as minimally invasive surgery (MIS). Methods of use of radio frequency (RF) techniques for improved nerve detection in association with an ultrasound detection system are described. The methods include the use of RF echoes in the detection of tissue dependent features. The methods also include use of an RF classifier to reduce false positives. System dependent features are accounted for through use of a calibration spectrum or through non-parametric model estimation using machine learning.

A target biopsy system employing an ultrasound probe (20), a target biopsy needle (30) and a ultrasound guide controller (44). In operation, the ultrasound probe (20) projects an ultrasound plane intersecting an anatomical region (e.g. a liver). The target biopsy needle (30) include two or more ultrasound receivers (31) for sensing the ultrasound plane as the target biopsy needle (30) is inserted into the anatomical region. In response to the ultrasound receiver(s) (31) sensing the ultrasound plane, the ultrasound guide controller (44) predicts a biopsy trajectory of the target biopsy needle (30) within the anatomical region relative to the ultrasound plane. The prediction indicates the biopsy trajectory is either within the ultrasound plane (i.e., an in-plane biopsy trajectory) or outside of the ultrasound plane (i.e., an out-of-plane biopsy trajectory).