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 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: In some examples, one or more three dimensional (3D) objects may be rendered in relation to a two dimensional (2D) imaging slice. The 3D object may be rendered such that the 3D object casts a colored shadow on the 2D imaging slice. In some examples, the 3D object may be rendered in colors where different colors indicate a distance from the portion of the 3D object from the 2D imaging slice.

Abstract: An end effector state estimation system for use in minimally invasive surgery (MIS) applications performs sensing and prediction algorithms to determine and visualize the state of an implantable therapeutic device during deployment. The end effector state estimation system includes a flexible elongate member, a therapeutic device coupled to a distal portion of the flexible elongate member, a sensor that measures at least one parameter related to the deployment state of the therapeutic device, and a processor. The processor receives image data from an imaging system representative of the therapeutic device positioned within the body cavity of the patient and the at least one parameter from the sensor, determines the deployment state of the therapeutic device based on the image data and the at least one parameter, outputs a graphical representation of the deployment state of the therapeutic device.