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In this paper, we propose a method that automatically estimates surgical phases in a specified workflow with a multi-camera system. More specifically, our goal is to output an appropriate phase label for each one-second of input videos captured by multiple cameras in an operating room. The fundamental idea behind our work lies in constructing a hidden Markov model based on motion features, which are...
In this paper, we present a robust method to improve the accuracy of phases segmentation problem in a specified surgical workflow (SW) by learning a topic model from the optical flow (OF) motion features of general working contexts, such as the medical staffs, equipments and materials. We have an awareness of such working contexts by capturing the SW with multiple synchronized cameras. The main problems...
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