Devices, systems, and methods are provided in which noise or artifacts generated by motion of a probe are attenuated in acquired physiological data, such as auscultation or ultrasound data. One such method includes acquiring physiological data of a patient by a handheld device. Motion of the handheld device is sensed, and a determination is made as to whether the sensed motion of the handheld device exceeds a motion threshold. The method further includes generating conditioned physiological data of the patient by attenuating a portion of the acquired physiological data in response to determining that the sensed motion of the handheld device exceeds the motion threshold.

An ultrasound diagnostic apparatus according to embodiments includes processing circuitry. The processing circuitry acquires a plurality of pieces of medical image data arranged in time series over at least one cardiac cycle in which a region including a pulsative target of a subject is imaged. The processing circuitry performs a plurality of motion estimation processes using a pattern matching at frame intervals different from each other on an identical position for the pieces of medical image data and determines most likely second motion information from among a plurality of pieces of first motion information estimated by the motion estimation processes.

The present invention proposes an ultrasound system and a method of detecting lung sliding on the basis of a temporal sequence of ultrasound data frames of a first region of interest. The first region of interest includes a pleural interface of a lung. A sub-region identifier (410) is configured to identify, for each of the ultrasound data frames, a sub-region of a scanned region of the ultrasound data frame, the sub-region comprising at least part of the pleural interface; a lung sliding detector (420) is configured to derive a parametric map for the sub-region on the basis of at least two ultrasound data frames of the temporal sequence, parametric values of the parametric map indicating a degree of tissue motion over the at least two ultrasound frames; wherein the lung sliding detector is further configured to extract data of the sub-regions from the at least two ultrasound data frames, and to derive the parametric map on the basis of the extracted data.

An ultrasonic diagnostic imaging system acquires received beams of echo signals produced in response to a plurality of transmit events. The received beams are combined with refocusing to account for differences in receive beam to transmit event locations. The delays and weights used in the refocusing are supplemented with delays and weights which correct for reverberation artifacts. The received echo signals are processed to detect the presence of reverberation artifacts and a simulated transmission of reverberation signal components to virtual point sources in the image field is calculated. This simulation produces the delays and weights used for reverberation signal compensation, or estimated reverberation signals which can be subtracted from received echo signals to reduce reverberation artifacts.

The present disclosure concerns a system for determining vital signs of a subject, such as heart activity profile (e.g. heart rate and heart rate variability), respiration rate or blood pressure. The above vital signs can be extracted from analyzing the movement profile of the chest due to heartbeat, e.g. ballistocardiography (BCG), and respiration process.

The monitoring system processes and analyzes measured data of acoustic signals that are obtained by transmitting acoustic signals, in particular, ultrasonic signals, towards a subject and detecting the reflected signals therefrom. The transducer/transmitter of the acoustic signals is positioned remotely from the subject such that the signal communication between the measured subject and the transducer is contact-free. The analysis includes determining a variation profile of phase and frequency between the transmitted signals and the reflections thereof from the subject, and said variation profile is indicative of vital signs of the subject.

Systems and methods for triggering the acquisition of elastography measurements based on motion data are disclosed. Motion data may be acquired by Doppler mode imaging in some embodiments. The motion data may be used to generate a trigger signal. The trigger signal may be provided to a transmit controller. The transmit controller may cause an ultrasound transducer to acquire elastography measurements responsive to the trigger signal.

In some embodiments, ultrasound receive beamforming yields beamformed samples, based upon which spatially intermediate pixels (232, 242, 244) are dynamically reconstructed. The samples have been correspondingly derived from acquisition through respectively different acoustic windows (218, 220). The reconstructing is further based on temporal weighting of the samples. In some embodiments, the sampling is via synchronized ultrasound phased-array data acquisition from a pair of side-by-side, spaced apart (211) acoustic windows respectively facing opposite sides of a central region (244) to be imaged. In particular, the pair is used interleavingly to dynamically scan jointly in a single lateral direction in imaging the region. The acquisition in the scan is, along a synchronization line (222) extending laterally across the region, monotonically progressive in that direction. Rotational scans respectively from the window pair are synchronizable into a composite scan of a moving object. The synchronization line (222) can be defined by the focuses of the transmits. The progression may strictly increase.

An ultrasonic diagnostic imaging for analyzing shear wave characteristics utilizes a background motion compensation subsystem which acts as a spatial filter of pulse-to-pulse autocorrelation phases over the ROI of tracking pulse vectors to compensate for background motion. The subsystem is configured to compute the sum of all lag-1 autocorrelations of tracking line ensemble data over the tracking ROI, for each PRI. The inventive technique does not significantly reduce sensitivity to shear waves, because the shear wave is spatially smaller than the ROI.

Systems and techniques for determining degree of motion using machine learning to improve medical image quality are presented. In one example, a system generates, based on a convolutional neural network, motion probability data indicative of a probability distribution of a degree of motion for medical imaging data generated by a medical imaging device. The system also determines motion score data for the medical imaging data based on the motion probability data.

A computing device is provided having at least one processor (104) operative to facilitate motion correction in a medical image file (102). The at least one processor (104) is configured to generate at least one unified frame file (110) based on motion image data (204), depth map data (206) corresponding to the motion image data, and region of interest data (200). Further, at least one corrected image file derived from the medical image file (102) is generated by performing the motion correction based on the at least one unified frame file (110) using the processor (104). Subsequently, the at least one corrected image file is outputted for display to one or more display devices (122).