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Objective: State-of-the-art techniques for surgical data analysis report promising results for automated skill assessment and action recognition. The contributions of many of these techniques, however, are limited to study-specific data and validation metrics, making assessment of progress across the field extremely challenging. Methods: In this paper, we address two major problems for surgical data...
Automated segmentation and recognition of fine-grained activities is important for enabling new applications in industrial automation, human-robot collaboration, and surgical training. Many existing approaches to activity recognition assume that a video has already been segmented and perform classification using an abstract representation based on spatio-temporal features. While some approaches perform...
In the future of surgery, tele-operated robotic assistants will offer the possibility of performing certain commonly occurring tasks autonomously. Using a natural division of tasks into subtasks, we propose a novel surgical Human-Machine Collaborative (HMC) system in which portions of a surgical task are performed autonomously under complete surgeon's control, and other portions manually. Our system...
Robotic surgical assistants offer the possibility of automating portions of a task that are time consuming and tedious in order to reduce the cognitive workload of a surgeon. This paper proposes using programming by demonstration to build generative models and generate smooth trajectories that capture the underlying structure of the motion data recorded from expert demonstrations. Specifically, motion...
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