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: A method for aligning a real-world object with a virtual object includes capturing images, video, or both of the real-world object from a first viewpoint and from a second viewpoint. The first and second viewpoints are different. The method also includes simultaneously superimposing the virtual object at least partially over the real-world object from the first viewpoint in a first augmented reality (AR) display and from the second viewpoint in a second AR display based at least in part on the images, video, or both. The method also includes adjusting a position of the real-world object to at least partially align the real-world object with the virtual object from the first viewpoint in the first AR display and from the second viewpoint in the second AR display.