The present invention relates to a pregnancy monitoring system, the system comprising a fetal monitoring transducer (20) arranged to detect fetal medical condition information; and a control device (48) comprising a motion assessment unit (50) and a signal output unit (52); wherein the fetal monitoring transducer (20) is arranged to detect fetal movement indicative information, wherein the motion assessment unit (50) is arranged to process fetal movement grading information, in addition to the fetal movement indicative information, wherein the signal output unit (52) is arranged to simultaneously output a fetal condition signal, particularly a fetal heart rate signal, and an augmented fetal movement signal based on the fetal movement indicative information and the fetal movement grading information, wherein a characteristic property of the original fetal movement information is still present in the augmented fetal movement signal. The disclosure further relates to a corresponding pregnancy monitoring method.

Various methods and systems are provided for display of live images. In one example, a method for motion compensation in the live images includes acquiring a first set of imaging data from a visible sector of an imaging system, the visible sector including a region of interest displayed to a user, and acquiring a second set of imaging data at an area offset from the visible sector, during the acquiring of the first set of imaging data. The second set of imaging data is used to compensate for gross motion of the region of interest resulting in displacement of at least a portion of the region of interest outside of the visible sector.

Ultrasound-based acoustic streaming for deciding whether material is fluid is dependent upon any one or more of a variety of criteria. Examples are displacement, speed (230), temporal or spatial flow variance, progressive decorrelation, slope or straightness of accumulated signal to background comparisons over time, and relative displacement to adjacent soft tissue. Echogenicity-based area identification is combinable with the above movement characteristic detection in the deciding. Fluid pool identification is performable from the area-limited acoustic streaming testing and ultrasound attenuation readings. Candidates from among the areas (210) are screenable based on specific shapes or bodily organs detected. Natural flow can be excluded from streaming detection by identification of blood vessels (206). Processing for each FAST ultrasound view (202), or for the entire procedure, is performable automatically, without need for user intervention or with user intervention to identify suspected areas.

An imaging system includes an imaging device (10) configured to acquire an image in a multi-beat acquisition mode. A quality scoring module (115) is stored in memory and is configured to evaluate changes in the image between portions of a multi-beat cycle to compute a quality score (136) indicating a suitability of the image. A display (118) is included for viewing the image and displaying the quality score as real-time feedback for the image.

A non-invasive system for concurrent monitoring cardiac, respiration activity and other body motions from a patent support device integrated with biometric sensors. Such system can also predicate a motion state to enable/disable a medical imaging device or radiotherapy device during cancer and/or cardiac arrhythmias treatment.

A perfusion imaging processing method comprising collecting a plurality of digital images comprising sequential B-Mode micro-ultrasound reflectivity data, calculating decorrelation trends of autocorrelated data to determine blood flow and perfusion level, reducing the noise content in the data using the decorrelation trends, and/or forming a visual representation based on the decorrelation trends. The present system and method provides an ultrasonic imaging system and method which provides perfusion data without requiring the use of an injected contrast agent.

An ultrasound system with a deep learning neural network feature is used to eliminate haze artifacts in B mode images of the carotid artery by analysis of orthogonal information. In a described implementation the orthogonal information comprises the structural information of a B mode image and motion information of the same field of view as that of the B mode image. In another embodiment the neural network reduces haze artifacts by reducing TGC gain at the depth of artifacts.

A method for performing shear wave elastography imaging of an observation field in a medium, the method including shear wave imaging steps to acquire sets of shear wave propagation parameters, the method further including a reliability indicator determining step during which a reliability indicator of the shear wave elastography imaging of the observation field is determined.

The present application describes a musculoskeletal diagnosis system that receives, in real-time or substantially real-time, various objects from a musculoskeletal ultrasound probe. Once the objects are received, the musculoskeletal diagnosis system analyzes the various objects to detect various pathologies and direct additional movement of the ultrasound probe as subsequent objects are taken.

An apparatus includes a processor and a display. The processor includes a combiner configured to combine contrast data acquired with a same sub-aperture, for each of a plurality of sub-apertures, to create a contrast frame for each of the sub-apertures. The processor includes a microbubble detector configured to determine positions of microbubbles in the contrast frames. The processor includes a motion estimator configured to estimate a motion field based on frames of B-mode data for each of the plurality of sub-apertures. The processor includes a motion corrector configured to motion correct the positions of the microbubbles in the contrast frames based on the motion field and time delays between emissions for the sets of contrast data and the emission for B-mode data, for each of the plurality of sub-apertures, to produce motion corrected contrast frames. The display is configured to display the motion corrected contrast frames as super resolution images.