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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...
In this paper, we present two new methods to integrate latent Dirichlet allocation (LDA) which is a topic model for surgical workflow phase estimation with a hidden Markov model (HMM). The proposed methods are able to detect surgical phases automatically based on codebook which is built by quantizing the extracted optical flow vectors from the recorded videos of surgical processes. To detect the current...
In this paper, we proposed a method to estimate phases in a workflow. The workflow is defined as certain works that have to be done in a certain order. The goal of the proposed method is to estimate the current phases that represent the works from the recorded data of workflow. The assumed workflow in this paper is a cholecystectomy surgery that is a kind of laparoscopic surgery and the surgery can...
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