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: 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: 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: 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.

Abstract: A computer-implemented method of predicting a success metric, achieved by performing a treatment procedure on a thrombus, is provided. The method includes: receiving angiographic image data, including one or more angiographic images comprising the thrombus; inputting the angiographic image data into a model, comprising a neural network, configured to output a prediction related to the treatment procedure; and calculating the success metric based on the output of the model.

Abstract: Methods and systems for autonomous cardiac mapping are disclosed. An example system for autonomous cardiac mapping of a heart chamber includes a processor being configured to acquire a representative geometric shell of the heart chamber, control a robotic device to autonomously navigate a mapping probe to a plurality of locations within the heart chamber based at least in part on the representative geometric shell, and generate a three-dimensional electroanatomical map of the heart chamber based on electrical data collected by the probe at the plurality of locations.

Abstract: A medical device may comprise a distal tip having a viewing element, a lighting element, and at least one feature configured to removably couple the distal tip to a shaft. The medical device may also comprise a working channel coupled to the distal tip and defining a central lumen configured to receive a tool. A wall of the working channel may define at least one additional lumen. The working channel may be configured to be removably inserted into the shaft. The medical device may also comprise at least one of a wire, a cable, or a conduit passing through the at least one additional lumen.

Abstract: A medical introducer sheath comprises a tubular shaft and an ultrasonic transducer array. The tubular shaft has a proximal end, a distal end opposite the proximal end, an inner surface, and an outer surface. The shaft defines a longitudinal axis extending between the proximal end and the distal end. The inner surface and the outer surface define a wall having a shaft wall thickness, the wall defining a distal wall face proximate the distal end of the shaft extending at an oblique angle relative to the longitudinal axis. The ultrasonic transducer array includes a plurality of ultrasound transducers disposed within the wall of the tubular shaft at the distal end thereof. The ultrasound transducers include an emitting/receiving surface generally aligned with the distal wall face, such that ultrasonic energy emitted from each of the ultrasound transducers is oriented directed generally at an oblique angle relative to the longitudinal axis.

Abstract: A medical system including a catheter, a sheath, and a controller. The catheter having a catheter distal end that includes multiple electrodes, the sheath configured to receive the catheter and having a sheath distal end configured to cover one or more of the multiple electrodes, and the controller configured to supply a current between electrodes of the multiple electrodes and to measure voltages from at least two of the multiple electrodes to determine whether one or more of the multiple electrodes is covered by the sheath.

Abstract: Methods and systems for autonomous cardiac mapping are disclosed. An example system for autonomous cardiac mapping of a heart chamber includes a processor being configured to acquire a representative geometric shell of the heart chamber, control a robotic device to autonomously navigate a mapping probe to a plurality of locations within the heart chamber based at least in part on the representative geometric shell, and generate a three-dimensional electroanatomical map of the heart chamber based on electrical data collected by the probe at the plurality of locations.