Surgical phase recognition is a basic component for different context-aware
applications in computer- and robot-assisted surgery. In recent years, several
methods for automatic surgical phase recognition have been proposed, showing
promising results. However, a meaningful comparison of these methods is
difficult due to differences in the evaluation process and incomplete reporting
of evaluation details. In particular, the details of metric computation can
vary widely between different studies. To raise awareness of potential
inconsistencies, this paper summarizes common deviations in the evaluation of
phase recognition algorithms on the Cholec80 benchmark. In addition, a
structured overview of previously reported evaluation results on Cholec80 is
provided, taking known differences in evaluation protocols into account.
Greater attention to evaluation details could help achieve more consistent and
comparable results on the surgical phase recognition task, leading to more
reliable conclusions about advancements in the field and, finally, translation
into clinical practice.

本文概述了自动手术阶段识别方法的评估过程中常见的偏差和对先前报告的结果进行了结构化的概述，以考虑评估协议的差异，并提出更加注重评估细节可能有助于在手术阶段识别任务上获得更一致和可比较的结果，并最终实现对该领域进展的可靠结论及其在临床实践中的应用。