Van Amsterdam, B;
Clarkson, MJ;
Stoyanov, D;
(2020)
Multi-Task Recurrent Neural Network for Surgical Gesture Recognition and Progress Prediction.
In:
2020 IEEE International Conference on Robotics and Automation (ICRA).
(pp. pp. 1380-1386).
IEEE: Paris, France.
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Abstract
Surgical gesture recognition is important for surgical data science and computer-aided intervention. Even with robotic kinematic information, automatically segmenting surgical steps presents numerous challenges because surgical demonstrations are characterized by high variability in style, duration and order of actions. In order to extract discriminative features from the kinematic signals and boost recognition accuracy, we propose a multi-task recurrent neural network for simultaneous recognition of surgical gestures and estimation of a novel formulation of surgical task progress. To show the effectiveness of the presented approach, we evaluate its application on the JIGSAWS dataset, that is currently the only publicly available dataset for surgical gesture recognition featuring robot kinematic data. We demonstrate that recognition performance improves in multi-task frameworks with progress estimation without any additional manual labelling and training
| Type: | Proceedings paper |
|---|---|
| Title: | Multi-Task Recurrent Neural Network for Surgical Gesture Recognition and Progress Prediction |
| Event: | 2020 IEEE International Conference on Robotics and Automation (ICRA) |
| ISBN-13: | 9781728173955 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/ICRA40945.2020.9197301 |
| Publisher version: | https://doi.org/10.1109/ICRA40945.2020.9197301 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10111216 |
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