The ongoing COVID-19 pandemic, caused by the highly contagious SARS-CoV-2 virus, has overwhelmed healthcare systems worldwide, putting medical professionals at a high risk of getting infected themselves due to a global shortage of personal protective equipment. This has in-turn led to understaffed hospitals unable to handle new patient influx. To help alleviate these problems, we design and develop a contactless patient positioning system that can enable scanning patients in a completely remote and contactless fashion. Our key design objective is to reduce the physical contact time with a patient as much as possible, which we achieve with our contactless workflow. Our system comprises automated calibration, positioning, and multi-view synthesis components that enable patient scan without physical proximity. Our calibration routine ensures system calibration at all times and can be executed without any manual intervention. Our patient positioning routine comprises a novel robust dynamic fusion (RDF) algorithm for accurate 3D patient body modeling. With its multi-modal inference capability, RDF can be trained once and used across different applications (without re-training) having various sensor choices, a key feature to enable system deployment at scale. Our multi-view synthesizer ensures multi-view positioning visualization for the technician to verify positioning accuracy prior to initiating the patient scan. We conduct extensive experiments with publicly available and proprietary datasets to demonstrate efficacy. Our system has already been used, and had a positive impact on, hospitals and technicians on the front lines of the COVID-19 pandemic, and we expect to see its use increase substantially globally.

中文翻译：

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迈向非接触式患者定位。

由高度传染性的SARS-CoV-2病毒引起的持续的COVID-19大流行已经使全世界的医疗系统不堪重负，由于全球个人防护设备的短缺，医疗专业人员极有可能被感染。反过来，这导致人员不足的医院无法处理新患者涌入的情况。为了帮助减轻这些问题，我们设计和开发了一种非接触式患者定位系统，该系统可以使患者以完全远程且非接触的方式进行扫描。我们的主要设计目标是尽可能减少与患者的身体接触时间，这是我们通过非接触式工作流程实现的。我们的系统包括自动校准，定位和多视图合成组件，使患者无需物理接近即可进行扫描。我们的校准程序可确保始终进行系统校准，无需任何人工干预即可执行。我们的患者定位程序包括一种新颖的鲁棒动态融合（RDF）算法，用于精确的3D患者身体建模。凭借其多模式推理功能，RDF可以进行一次训练，并可以在具有各种传感器选择的不同应用程序中使用（无需重新训练），这是实现大规模系统部署的关键功能。我们的多视图合成器可确保多视图定位可视化，以便技术人员在启动患者扫描之前验证定位准确性。我们使用公开可用的专有数据集进行了广泛的实验，以证明疗效。我们的系统已经在COVID-19大流行的前线使用过，并对医院和技术人员产生了积极影响，