Data-Derived Models for Segmentation with Application to Surgical Assessment and Training

@article{Varadarajan2009DataDerivedMF,
  title={Data-Derived Models for Segmentation with Application to Surgical Assessment and Training},
  author={Balakrishnan Varadarajan and Carol E. Reiley and Henry Lin and Sanjeev Khudanpur and Gregory D. Hager},
  journal={Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention},
  year={2009},
  volume={12 Pt 1},
  pages={426-34}
}
This paper addresses automatic skill assessment in robotic minimally invasive surgery. Hidden Markov models (HMMs) are developed for individual surgical gestures (or surgemes) that comprise a typical bench-top surgical training task. It is known that such HMMs can be used to recognize and segment surgemes in previously unseen trials. Here, the topology of each surgeme HMM is designed in a data-driven manner, mixing trials from multiple surgeons with varying skill levels, resulting in HMM states… CONTINUE READING

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