论文标题
用于评估医疗应用中运动计划者的临床数据集
A Clinical Dataset for the Evaluation of Motion Planners in Medical Applications
论文作者
论文摘要
使用自主机器人增强医生的能力并实现新颖程序的前景导致了在开发医疗机器人和合并自主能力方面的巨大努力。运动计划是任何此类系统中工作的核心组成部分，该系统需要接近完美的安全性，可靠性和精度。尽管已经为医疗机器人开发运动规划师的广泛而有前途的工作，但它是一种比较现有算法并评估新颖的计划者和机器人的标准化和临床上的方法。我们介绍了医疗运动计划数据集（MED-MPD），这是一个在各种器官中的真实临床方案的公开数据集，目的是评估最低侵入性医疗机器人的运动计划者。我们的目标是，该数据集是创建更大的强大医疗运动计划基准框架，提高对医疗运动计划者的研究以及负担产生医疗评估数据的负担的第一步。
The prospect of using autonomous robots to enhance the capabilities of physicians and enable novel procedures has led to considerable efforts in developing medical robots and incorporating autonomous capabilities. Motion planning is a core component for any such system working in an environment that demands near perfect levels of safety, reliability, and precision. Despite the extensive and promising work that has gone into developing motion planners for medical robots, a standardized and clinically-meaningful way to compare existing algorithms and evaluate novel planners and robots is not well established. We present the Medical Motion Planning Dataset (Med-MPD), a publicly-available dataset of real clinical scenarios in various organs for the purpose of evaluating motion planners for minimally-invasive medical robots. Our goal is that this dataset serve as a first step towards creating a larger robust medical motion planning benchmark framework, advance research into medical motion planners, and lift some of the burden of generating medical evaluation data.
