Abstract: A computer-implemented method of assessing operator behavior during a medical procedure involving medical equipment, is provided. The method includes: receiving operator interaction data representing operator interactions with the medical equipment during the medical procedure; inputting the operator interaction data into a machine-learning model; and outputting a characteristic of the operator behavior based on a position of a latent space encoding of the operator interaction data generated by the machine-learning model, with respect to a distribution of latent space encodings of training data representing operator interactions with the medical equipment having known characteristics of the operator behavior.

Abstract: A computer-implemented method of performing motion compensation on a temporal sequence of digital subtraction angiography, DSA, images includes: inputting (S120) a temporal sequence of DSA images (110) into a neural network (120) trained to predict, from the inputted temporal sequence (110), a composite motion-compensated DSA image (130) representing the inputted temporal sequence (110) and which includes compensation for motion of the vasculature between successive contrast-enhanced images in the temporal sequence, and which also includes compensation for motion of the vasculature between acquisition of contrast-enhanced images in the temporal sequence and acquisition of the mask image; and outputting (S130) the predicted composite motion-compensated DSA image (130).

Abstract: An ultrasound imaging system may analyze motion of landmarks in a temporal sequence of image frames to determine mobility of one or more landmarks. In some examples, the sequence of image frames may be analyzed by one or more artificial intelligence models to detect landmarks and generate flow fields for the detected landmarks. The flow fields may be analyzed to determine the isotropy of the movement of the landmarks. The isotropy analysis may be used to generate a quantitative mobility index.

Abstract: A diagnostic ultrasound system has a 2D array transducer which is operated with 1×N patches, patches which are only a single element wide. The “N” length of the patches extends in the elevation direction of a scanned 2D image plane, with the single element width extending in the lateral (azimuth) direction. Focusing is done along each patch in the elevation direction by a microbeamformer, and focusing in the lateral (azimuth) direction is done by the system beamformer. The minimal width of each patch in the azimuth direction enables the production of images highly resolved in the azimuthal plane of a 2D image, including the reception of highly resolved multilines for high frame rate imaging.

Abstract: Systems and methods for ultrasound image acquisition, tracking and review are disclosed. The systems can include an ultrasound probe coupled with at least one tracking device configured to determine a position of the probe based on a combination of ultrasound image data and probe orientation data. The image data can be used to determine a physical reference point and superior-inferior probe coordinates within a patient being imaged, which can be supplemented with the probe orientation data to determine lateral coordinates of the probe. A graphical user interface can display imaging zones corresponding to a scan protocol, along with an imaging status of each zone based at least in part on the probe position. Ultrasound images acquired by the systems can be tagged with spatial indicators and severity indicators, after which the images can be stored for later retrieval and expert review.

Abstract: A computer-implemented method of reducing temporal motion artifacts in temporal intracardiac sensor data, includes: inputting (S120) temporal intracardiac sensor data (110), into a neural network (130) trained to predict, from the temporal intracardiac sensor data (110), temporal motion data (140, 150) representing the temporal motion artifacts (120); and compensating (S130) for the temporal motion artifacts (120) in the received 5 temporal intracardiac sensor data (110) based on the predicted temporal motion data (140, 150).

Abstract: An ultrasound (US) system (10) includes a US scanner (14) and a US probe (12) operatively connected to the US scanner.

Abstract: A vibration actuator (10) for mechanically generating a shear wave comprises a plurality of n rotational vibrators (141, 142, 143), an accelerometer (16), and a controller (18). The plurality of n rotational vibrators enables generation of a vibration vector with desired directional behavior selected from a plurality of vibration vectors (34, 36, 38) of different directional behaviors. Each rotational vibrator comprises an independently controllable motor (20) having a drive shaft (22) and an eccentric disk (24). The accelerometer is arranged to detect a vibration vector generated by at least two of the plurality of n rotational vibrators.

Abstract: A computer-implemented method of providing an endovascular coil specification of an endovascular coil for treating an aneurysm in a coil embolization procedure, includes: inputting (S120) X-ray image data (110), comprising one or more X-ray images including an aneurysm (120), into a neural network (130, 230) trained to predict, from the X-ray image data (110), endovascular coil data (140, 150) of an endovascular coil for treating the aneurysm (120); and outputting (S130) the endovascular coil data (140, 150) to provide the endovascular coil specification.

Abstract: A method is provided for determining whether a section of a lead has adhered to a blood vessel. The method comprises obtaining data corresponding to the blood vessel with a lead inside and determining motion vectors corresponding to the lead from the data corresponding to the blood vessel. The motion vectors are input into a machine learning algorithm trained to learn the correlation between the motion vectors and whether a section of a lead has adhered to a blood vessel and output an adherence level for segments of the lead.

Abstract: A computer-implemented method of locating a vascular constriction in a temporal sequence of angiographic images, includes identifying (S130), from a temporal sequence of differential images, temporal sequences of a subset of sub-regions (120i,j) of the vasculature wherein contrast agent enters the sub-region, and the contrast agent subsequently leaves the sub-region; and inputting (S140) the identified temporal sequences of the subset into a neural network (130) trained to classify, from temporal sequences of angiographic images of the vasculature, a sub-region (120i,j) of the vasculature as including a vascular constriction (140).

Abstract: A system performs a medical procedure in a region of interest of a patient. The system includes an interventional medical device insertable into the region of interest, and a sensor attached to a portion of the interventional device, the sensor being configured to convert an ultrasonic wave from an ultrasound imaging probe to a corresponding electrical radio frequency (RF) signal. The corresponding RF signal is received by a wireless receiver outside the region of interest, enabling determination of a location of the sensor within the region of interest.

Abstract: A controller for determining shape of an interventional device includes a memory that stores instructions, and a processor that executes the instructions. When executed by the processor, the instructions cause the controller to execute a process that includes controlling an imaging probe to emit at least one tracking beam to an interventional medical device over a period of time comprising multiple different points of time. The process also includes determining a shape of the interventional medical device, based on a response to the tracking beams received over the period of time from a first sensor that moves along the interventional medical device during the period of time relative to a fixed location on the interventional medical device for the period of time.

Abstract: A sensor device includes a flexible planar strip with a plurality of layers is described. The flexible planar strip is configured to at least partially encapsulate a medical device. The flexible planar strip includes a first dielectric layer, a second dielectric layer, and a patterned conductive layer including a sensor electrode disposed on the second dielectric layer. According to one aspect an ultrasound sensor including a piezoelectric polymer. The ultrasound sensor is disposed on the sensor electrode such that a first surface of the ultrasound sensor is in electrical contact with the sensor electrode and such that a second surface of the ultrasound sensor is exposed for making electrical contact with a medical device.

Abstract: A controller for reducing noise in an ultrasound environment includes memory that stores instructions; and a processor that executes the instructions. When executed by the processor, the instructions cause the controller to execute a process that includes controlling emission, by an ultrasound probe, of multiple beams each at a different combination of time of emission and angle of emission relative to the ultrasound probe. The process also includes identifying repetitive noise from a first source received with the imaging beams at a sensor on an interventional medical device, including a rate at which the repetitive noise from the first source repeats and times at which the repetitive noise from the first source is received. The process also includes interpolating signals based on the imaging beams received at the sensor to offset the repetitive noise from the first source at the times at which the repetitive noise from the first source is received.

Abstract: An interventional device includes an elongate shaft (101) with a longitudinal axis (A-A?), and an ultrasound detector (102). The ultrasound detector (102) comprises a PVDF homopolymer foil strip (103). The foil strip (103) is wrapped around the longitudinal axis (A-A?) of the elongate shaft (101) to provide a band having an axial length (L) along the longitudinal axis (A-A?). The axial length (L) is in the range 80-120 microns.

Abstract: A system (200) performs a medical procedure in a region of interest of a patient. The system includes an interventional medical device (214) insertable into the region of interest, and a sensor (215) attached to a portion of the interventional device, the sensor being configured to convert an ultrasonic wave from an ultrasound imaging probe (211) to a corresponding electrical radio frequency (RF) signal. The corresponding RF signal is received by a wireless receiver (209) outside the region of interest, enabling determination of a location of the sensor within the region of interest.

Abstract: An ultrasound imaging system may determine whether a proper cardiac view has been acquired. When a proper cardiac view has been acquired, the ultrasound imaging system may adjust the imaging parameters to visualize epicardial adipose tissue (EAT). Once an image with the adjusted imaging parameters is acquired, the ultrasound imaging system may segment the EAT from the image. Measurements of the EAT may be acquired from the segmented image. In some examples, a report on whether a patient requires follow-up may be generated based on the EAT measurements and patient information.

Abstract: The present disclosure relates to a method for a federated learning system in hybrid operating room environment, in which a global machine-learning model learns from a subset of local participants selected based on predefined selection criteria. The local participants amongst the subset respectively provide an update matrix and a quality score to train the global machine-learning model. A combination of the update matrix and the quality score is applied to the global machine-learning model, in which each update matrix is weighed based on the quality score of the local participant.

Abstract: A method and system are provided for performing an interventional procedure by a user on a subject.