Ultrasound-based estimation of disease activity, such as for NAS or other activity index for NAFLD for liver disease, is provided. Ultrasound measures acoustic scatter and shear wave propagation parameters, such as measuring acoustic backscatter coefficient, shear wave velocity, and shear wave damping ratio. A score for the disease activity is determined from these scatter and shear wave propagation parameters. The physician may be assisted by relatively inexpensive and rapid ultrasound as compared to biopsy or MRI based scoring in scoring activity of a disease, such as NAFLD. Ultrasound imaging is more readily available and less expensive and MRI, and is non-invasive.

An ultrasound imaging system computes real time physiological parameters from measurements of anatomical features in ultrasound image data using a neural network to identify the location of the anatomical features. In one embodiment, cardiac parameters are computed from endocardial wall tracings in M-mode ultrasound image data that are identified by the neural network.

The present invention relates to a monitoring apparatus for monitoring an ablation procedure. The monitoring apparatus comprises an ultrasound signal providing unit for providing an ultrasound signal that depends on received echo series of an object that is ablated. The monitoring apparatus further comprises an ablation depth determination unit for determining an ablation depth from the provided ultrasound signal. The ablation depth can be determined directly from the ultrasound signal and is an important parameter while performing an ablation procedure. For example, it can be used for determining the progress of ablation within the object and for determining when the ablation has reached a desired progression.

An ultrasonic diagnosis apparatus includes a position detector, and control circuitry. The position detector detects a position in a three-dimensional space of one of an ultrasonic image and an ultrasonic probe. The control circuitry uses a vivisection view defined in a three-dimensional space. The control circuitry associates a structure related to a subject included in the ultrasonic image with a structure included in the vivisection view using a position and orientation in a first three-dimensional coordinate system of the structure related to the subject included in the ultrasonic image and a position and orientation in a second three-dimensional coordinate system of the structure included in the vivisection view.

A system includes an ultrasound probe comprising an ultrasound transducer, a first motor configured to rotate the ultrasound transducer around a horizontal axis to scan a plane, and a second motor configured to rotate the ultrasound transducer around a vertical axis to move to a different plane. The system further includes a controller unit configured to select a number of scan planes for an interlacing scan to scan a volume of an area of interest in a patient's body using the ultrasound probe; select an interlacing factor for the interlacing scan; divide the scan planes into groups of scan planes based on the interlacing factor; and perform the interlacing scan by controlling the first motor and the second motor, wherein the first motor moves in a first direction for at least some of the scan planes and in a second direction for other ones of the scan planes.

Ultrasound methods provide for the motion tracking of both vessel wall motion and blood flow (e.g., with use of high frame rate ultrasound pulse echo data and speckle tracking both wall motion and flow can be tracked simultaneously). Ultrasound systems provide for the motion tracking of both vessel wall motion and blood flow (e.g., with use of high frame rate ultrasound pulse echo data and speckle tracking both wall motion and flow can be tracked simultaneously).

Methods and apparatuses for performing automated detection of lung slide using a computing device (e.g., an ultrasound system, etc.) are disclosed. In some embodiments, the techniques determine lung sliding using one or more neural networks. In some embodiments, the neural networks are part of a process that determines probabilities of the lung sliding at one or more M-lines. In some embodiments, the techniques display one or more probabilities of lung sliding in a B-mode ultrasound image.

Aspects of the technology described herein related to monitoring fetal heartbeat and uterine contraction signals. An ultrasound system may be configured to sweep a volume to collect ultrasound data, detect a fetal heartbeat and/or uterine contraction signal in the ultrasound data, and automatically steer an ultrasound beam to monitor the fetal heartbeat and/or uterine contraction signal. The ultrasound system may be further configured to determine a location where the fetal heartbeat and/or uterine contraction signal is detectable or detectable at a highest quality. The ultrasound system may include a wearable ultrasound device, such as an ultrasound patch coupled to a subject. The wearable ultrasound device may have a two-dimensional array of ultrasonic transducers capable of steering ultrasound beams in three dimensions.

For tissue property estimation with ultrasound, multiple different types of measurements are performed by an ultrasound system, including scatter measurements and shear wave propagation measurements. The tissue property, such as liver fat fraction, is estimated using a combination of these different types of measurements.

Systems and methods are provided for motion corrected wide-band pulse inversion ultrasonic imaging. A first pulse is transmitted, a second pulse is then transmitted after a delay, with the second pulse having different polarity. Echoes of the first pulse and the second pulse are received, using a reception bandwidth that enables capturing at least a portion of a fundamental portion of each pulse. The echoes are processed, and corresponding ultrasound images are generated based on processing. The processing includes determining displacement data between the first pulse echo and the echo of the second pulse for at least one structure in an imaged area; determining one or more displacement corrections based on the displacement data; applying at least one displacement correction to at least one of the first pulse echo and the echo of the second pulse; and combining the first pulse echo and the echo of the second pulse.