Development of novel techniques for tracking surgical tools

开发追踪手术工具的新技术

• 批准号: 549831-2020
• 负责人: Rivaz, Hassan
• 金额: $ 2.19万
• 依托单位: Concordia University
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=700808
• 关键词: Development; novel; techniques; tracking; surgical

This project aims to solve two issues we currently face in reliable localization and tracking of surgical tools, which is of paramount importance in orthopedic surgeries. To localize and track surgical tools, Think Surgical has developed a novel six-camera system to localize four markers (called fiducials) that are attached to each tool. Aim 1 focuses on reducing tracking error caused either by a transition of a fiducial marker out of the field of view of a tracking camera, or by an object (such as operator's hand) occluding one of the cameras within the field of view. We propose to fuse the physics of how the tools can move with sensory data of the six-camera system to address these issues. The physical prior information includes the fact that the velocity and acceleration of the tool cannot be infinity. Aim 2 focuses on detecting inaccurate localization of the surgical tools caused by an object partially covering a fiducial. Examples include a drop of blood or scrubs, which substantially increase the tracking error of the six-camera system. We propose two approaches to tackle this issue. First, we will build on the technique developed in Aim 1 to detect inaccurate sensory data. If all or few cameras localize a fiducial with a large error, the user will be alerted to inspect and clean that fiducial. Second, we will develop a machine learning technique to automatically classify each camera image of a fiducial as accurate or inaccurate. This research partnership can lead to development of novel technologies that enable more accurate and reliable localization of the surgical tools, potentially improving the outcome of orthopedic surgeries. It will also lead to training of two highly qualified personnel (HQP) working in close collaboration with a Canadian company.

该项目旨在解决我们目前面临的两个问题，即手术工具的可靠定位和跟踪，这在骨科手术中至关重要。为了定位和跟踪手术工具，Think Surgical开发了一种新颖的六摄像头系统，用于定位连接到每个工具的四个标记（称为基准点）。目标1集中于减少由基准标记过渡到跟踪相机的视场之外或由遮挡视场内的相机之一的物体（诸如操作者的手）引起的跟踪误差。我们建议将工具如何移动的物理特性与六摄像头系统的传感数据融合在一起，以解决这些问题。物理先验信息包括工具的速度和加速度不可能是无穷大的事实。目标2集中于检测由部分覆盖基准的物体引起的手术工具的不准确定位。例如，一滴血或擦洗，这大大增加了六相机系统的跟踪误差。我们提出两种方法来解决这个问题。首先，我们将在目标1中开发的技术基础上检测不准确的传感数据。如果所有或少数相机定位具有大误差的基准，则将提醒用户检查并清洁该基准。其次，我们将开发一种机器学习技术，自动将基准点的每个相机图像分类为准确或不准确。 这种研究伙伴关系可以导致新技术的开发，使手术工具的定位更加准确和可靠，从而可能改善骨科手术的结果。它还将导致培训两名与一家加拿大公司密切合作的高素质人员。