Provided is an ultrasound diagnostic apparatus including an ultrasound probe, an imaging section that images the subject on the basis of a reception signal output from the ultrasound probe to generate an ultrasound image, an image analysis section that performs image analysis using the ultrasound image, a movement detection sensor that detects and outputs a movement of the ultrasound probe as a detection signal, a movement amount calculation section that calculates a movement amount of the ultrasound probe in a case where an imaging inspection portion that is currently being imaged among a plurality of inspection portions of the subject is inspected, using the detection signal output from the movement detection sensor, and a portion discrimination section that discriminates the imaging inspection portion on the basis of an image analysis result in the image analysis section and the movement amount calculated by the movement amount calculation section.

Aspects of the technology described herein relate to guiding collection of ultrasound data collection using motion and/or orientation data. A first instruction for rotating or tilting the ultrasound imaging device to a default orientation may be provided. Based on determining that the ultrasound imaging device is in the default orientation, a second instruction for translating the ultrasound imaging device to a target position may be provided. Based on determining that the ultrasound imaging device is in the target position, a third instruction for rotating or tilting the ultrasound imaging device to a target orientation may be provided.

The present embodiments relate generally to systems and methods for securing operation of an ultrasound scanner for use with a multi-use electronic display device. In some embodiments, the multi-use electronic display device can control whether the ultrasound scanner is permitted to generate ultrasound image data for display based on an institution affiliation status of the ultrasound scanner retrieved from a server. In some embodiments, the multi-use electronic display device can control whether the ultrasound scanner is permitted to generate ultrasound image data for display based on whether a digital certificate provided by a server is successfully validated.

Methods, systems, and coaptation measurement devices as described herein include an elongate sensor body at the end of a proximal connecting member, and a plurality of sensors in an array across a face of the sensor body, wherein each sensor of the plurality of sensors is configured to detect if a portion of a heart valve is in contact with the sensor.

Systems and methods are disclosed for an ultrasound system. In various embodiments, a system is configured to receive echo data corresponding to a detection of an echo of a pulse signal, generate a set of transformations based on the echo data, and generate a set of point estimates for a frequency dependent filtering coefficient of a spectral response. The system is further configured to extract a set of attenuation coefficients based on the set of point estimates for the frequency dependent filtering coefficient and generate image data for the material of interest based on the set of attenuation coefficients.

An apparatus includes a processing device in operative communication with an ultrasound device. The processing device is configured to: receive a user selection of a lung imaging preset option and a user-selected imaging depth for the ultrasound device; define a threshold imaging depth based on a shallow lung imaging mode and a deep lung imaging mode (the threshold imaging depth is between approximately 4 cm and 8 cm); after receiving the user selection of the user-selected imaging depth, compare the user-selected imaging depth with the threshold imaging depth; and automatically configure the ultrasound device to switch between the shallow lung imaging mode and deep lung imaging mode, depending upon a result of the comparison of the user-selected imaging depth with the threshold imaging depth.

A thickness calculation method includes: a signal acquisition step of acquiring a reception signal by transmitting an ultrasonic wave from an ultrasonic probe into a living body and receiving the ultrasonic wave reflected in the living body by the ultrasonic probe; a boundary candidate extraction step of extracting a plurality of boundary candidates from the reception signal; a feature information acquisition step of acquiring feature information based on a change in the reception signal; a state determination step of inputting the feature information and the boundary candidate to a machine learning model that receives the feature information and the boundary candidate and outputs boundary information indicating whether the boundary candidate is a boundary of a tissue in the living body, and acquiring the boundary information; and a thickness calculation step of calculating a thickness of the tissue based on the boundary information.

A method for automatically determining a depth of a vascular feature on an ultrasound image feed, acquired from an ultrasound scanner comprises displaying, on a screen that is communicatively connected to the ultrasound scanner, the ultrasound image feed comprising ultrasound image frames of a region of interest comprising the vascular feature, activating a Doppler mode of the ultrasound scanner, in which the ultrasound scanner obtains a Doppler-mode ultrasound signal corresponding to the region of interest comprising the vascular feature, applying at least one image processing filter to preserve the Doppler-mode ultrasound signal (the “preserved Doppler-mode signal”), generating from the preserved Doppler-mode signal of the vascular feature as returned to the ultrasound scanner, the depth of the vascular feature and indicating depth of the vascular feature to a user of ultrasound scanner

An ultrasonic diagnostic apparatus according to an embodiment has transmitting and receiving circuitry that transmits and receives ultrasonic waves, and processing circuitry. The transmitting and receiving circuitry is configured to perform first beamforming processing on reflected wave signals output from a plurality of transducer elements that receive reflected waves and perform second beamforming processing different from the first beamforming processing on the reflected wave signals. The processing circuitry is configured to calculate an evaluation value of spatial correlation of the reflected wave signals and perform third beamforming processing based on a first processing result that is a processing result of the first beamforming processing, a second processing result that is a processing result of the second beamforming processing, and the evaluation value.

Within the field of elastography, a new approach analyzes the limiting case of shear waves established as a reverberant field. In this framework, it is assumed that a distribution of shear waves exists, oriented across all directions in 3D (e.g. 2D space+time). The simultaneous multi-frequency application of reverberant shear wave fields can be accomplished by applying an array of external sources that can be excited by multiple frequencies within a bandwidth, for example 50, 100, 150, . . . 500 Hz, all contributing to the shear wave field produced in the liver or other target organ. This enables the analysis of the dispersion of shear wave speed as it increases with frequency, indicating the viscoelastic and lossy nature of the tissue under study. Furthermore, dispersion images can be created and displayed alongside the shear wave speed images. Studies on breast and liver tissues using the multi-frequency reverberant shear wave technique, employing frequencies up to 700 Hz in breast tissue, and robust reverberant patterns of shear waves across the entire liver and kidney in obese patients are reported. Dispersion images are shown to have contrast between tissue types and with quantitative values that align with previous studies.