Towards Unified Surgical Skill Assessment
- URL: http://arxiv.org/abs/2106.01035v1
- Date: Wed, 2 Jun 2021 09:06:43 GMT
- Title: Towards Unified Surgical Skill Assessment
- Authors: Daochang Liu, Qiyue Li, Tingting Jiang, Yizhou Wang, Rulin Miao, Fei
Shan, Ziyu Li
- Abstract summary: We propose a unified multi-path framework for automatic surgical skill assessment.
We conduct experiments on the JIGSAWS dataset of simulated surgical tasks, and a new clinical dataset of real laparoscopic surgeries.
- Score: 18.601526803020885
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Surgical skills have a great influence on surgical safety and patients'
well-being. Traditional assessment of surgical skills involves strenuous manual
efforts, which lacks efficiency and repeatability. Therefore, we attempt to
automatically predict how well the surgery is performed using the surgical
video. In this paper, a unified multi-path framework for automatic surgical
skill assessment is proposed, which takes care of multiple composing aspects of
surgical skills, including surgical tool usage, intraoperative event pattern,
and other skill proxies. The dependency relationships among these different
aspects are specially modeled by a path dependency module in the framework. We
conduct extensive experiments on the JIGSAWS dataset of simulated surgical
tasks, and a new clinical dataset of real laparoscopic surgeries. The proposed
framework achieves promising results on both datasets, with the
state-of-the-art on the simulated dataset advanced from 0.71 Spearman's
correlation to 0.80. It is also shown that combining multiple skill aspects
yields better performance than relying on a single aspect.
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