Abstract: A method includes accessing training images that collectively depict multiple stages of a surgical procedure. The method also includes accessing labels that indicate, for each of the training images, characteristics of one or more surgical tools depicted and a stage of the multiple stages of the surgical procedure depicted. The method also includes training a computational model, using the training images and the labels, to associate runtime images with a stage of the multiple stages based on characteristics of one or more surgical tools that are depicted by the runtime images. Another method includes associating, using a computational model, runtime images with a stage of a surgical procedure based on characteristics of one or more surgical tools depicted by the runtime images and generating output that indicates the stage associated with each of the runtime images.

Abstract: A method includes classifying, via a computational model, images of a source image stream as valid images or invalid images based on whether the images include biological tissue or a surgical tool; and generating a condensed image stream that includes the valid images. Another method includes classifying input images as valid images or invalid images using: a clustering algorithm that classifies each of the input images into either a first group or a second group and using labels that indicate whether the input images include a surgical tool. The method also includes training a computational model to identify the valid images based on whether the valid images include biological tissue or a surgical tool, or whether the valid images have at least a threshold level of clarity.