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 apparatus includes an imaging probe and is configured for dynamically arranging presentation of visual feedback for guiding manual adjustment, via the probe, of a location, and orientation, associated with the probe. The arranging is selectively based on comparisons between fields of view of the probe and respective results of segmenting image data acquired via the probe. In an embodiment, the apparatus includes a sensor which guides a decision that acoustic coupling quality is insufficient, the apparatus issuing a user alert upon the decision.

The invention provides an ultrasound system including an ultrasound transducer array and a processor. The ultrasound transducer array comprises a plurality of transducer elements adapted to conform with a subjects body. Further, at least two ultrasound transducer elements of the plurality of transducer elements are adapted to acquire a plurality of ultrasound signals from a region of interest at different orientations relative to said region of interest. The processor is adapted to receive ultrasound signals acquired by the ultrasound transducer array. The processor is further adapted to partition the plurality of ultrasound signals according to a signal depth and, for each ultrasound signal partition, calculate a Doppler power. For each ultrasound signal, the processor identifies a depth of a fetal heartbeat based on the Doppler power of each ultrasound signal partition and identifies a fetal heart region based on the identified fetal heartbeat and a location of the at least two ultrasound transducers.

This invention discloses an image analysis system and method, which detects blood vessels in ultrasound structural B-mode images using deep learning and identifies blood vessel type (vein or artery) based on automatic Doppler spectrogram features analysis. Such an automatic solution is important for successful catheter insertion under ultrasound guidance or other procedures which requires differentiation between the arteries or the veins or quantitative characterization of blood flow. The system contains: an ultrasound scanner with implemented B-mode and PW mode equipped with probe and algorithms implemented as software modules in the ultrasound scanner: 1) for automatic vessel tracking in real-time based on deep learning and, 2) algorithms for Doppler spectrogram quality assessment and parameterization by using quantitative spectrogram features. The system detects and classifies scanned vessels according to blood flow into: 1) arteries, or 2) veins.

The subject matter of the present disclosure generally relates to techniques for neuromodulation that include applying energy (e.g., ultrasound energy) into an internal tissue to cause tissue displacement and identifying that the tissue displacement has occurred. In one embodiment, the presence of tissue displacement is associated with a desired therapeutic or physiological outcome, such as a change in a molecule of interest.

A fully automated ultrasound apparatus includes a sensor or probe which can be initially manually attached to a side of the neck of a patient, an ultrasound interface to control the sensor and periodically acquire raw ultrasound data, a signal and image processing system to autonomously convert the raw ultrasound data into a measurement that is useful to physicians, and a display to relay the current measurements and measurement history to provide data trends. The sensor can include one or more ultrasound transducers built into a housing. A disposable component can serve to secure the sensor to the neck of the patient and to provide a coupling medium between the sensor and the skin of the patient.

According to one embodiment, an analysis apparatus includes processing circuitry. The processing circuitry configured to generate a harmonic signal and a fundamental wave signal based on a reception signal that is collected by an ultrasound probe, the harmonic signal corresponding to a harmonic component of a reflected wave of a ultrasound generated in the subject, the fundamental wave signal corresponding to a fundamental wave component of the reflected wave, calculate a first index value indicating tissue properties of the subject based on the harmonic signal, and calculate a second index value indicating the tissue properties based on the fundamental wave signal, and display an analysis result based on the first index value and the second index value.

A virtual conference in relation to diagnostic object data is created. Messages posted to the virtual conference from terminal devices of users participating in the virtual conference are received, and the posted messages are sent to the other terminal devices beside the terminal devices of the users. Information relating to the diagnostic object data is generated, which information is obtained in accordance with analysis results of analyzing the posted messages. The information relating to the diagnostic object data is sent to the terminal devices.

The present disclosure provides a positioning method for head and neck assessment comprising positioning a probe to the head and neck structures of a subject according to reference planes defined by light beams.

Methods and system for characterizing ligament properties using elastography are disclosed. An ultrasound system capable of performing shear wave elasticity imaging and/or supersonic shear imaging may retrieve one or more images from a proposed surgical site. The one or more images may be provided to a surgical planning system that identifies one or more properties of ligaments proximate to the surgical site. Musculoskeletal simulations may be performed using the identified properties to preoperatively identify a surgical plan. Preoperative identification of a surgical plan may enable a surgeon to select from more fine-tuning options for a joint replacement than conventional systems.