Image-Based Navigation for Interventional Robotic Devices

本项目旨在开发准确和鲁棒的方法来跟踪介入设备的运动 在MRI引导下的程序中。它将生产在MRI内精确放置针头的技术 扫描仪在实时图像引导和控制下。这项工作将提供技术， 在包括癌症在内的各种医疗条件下进行侵入性图像引导治疗。具体目标 如下所示： （被动基准定位）开发精确和可靠的定位技术 通过检测MRI图像中的特征性磁化率伪影， 虽然之前已经证明了基准分割，但这项工作中的挑战是快速的 定位和高精度的大范围的运动。磁化率产生的伪影 不同的顺磁性材料将在各种成像条件下表征，以便 设计鲁棒的伪影分割和定位方法。 （实时跟踪）开发实时跟踪算法基于被动基准检测 在目标1中开发其需要最小图像支持和快速成像以提供交互式 用于操纵介入设备和机器人机构的导航。为实现这些目标将 开发新的线基准几何形状，快速图像采集协议（与 提出的研究计划）和快速基准分割算法。 （系统集成）将被动基准跟踪系统（Aim 1）与实时跟踪系统相结合 与联合开发的交互式规划和导航软件界面中的导航和控制（目标2） 本研究项目的第4和第5项。规划和导航是紧密结合的，必须 共同开发。 这项工作的目的是推进图像引导微创介入领域， 医生在指定的手术空间内以更高的准确性和信心进行操作。被动的， 基于图像的跟踪技术将适用于需要精确的 手术器械与图像空间的配准，以及实时介入跟踪， 导航虽然对于封闭的MRI扫描仪内的机器人设备的视觉伺服有吸引力， 还将为手动致动或手持设备的定位提供有价值的反馈。这项工作 将提供适用于广泛临床场所的技术，并将有助于建立最低限度的 更广泛地应用于有创影像引导治疗。

This project aims to develop accurate and robust methods for tracking the motion of interventional devices during MRI-guided procedures. It will produce technologies for precise needle placement inside MRI scanners under real-time image guidance and control. This work will provide technology for minimally invasive image-guided therapy in a broad range of medical conditions, including cancer. The specific aims are as follows: (Passive Fiducial Localization) To develop accurate and robust techniques for determining the position of needles and passive fiducials by detecting their characteristic susceptibility artifacts in MRI images. While fiducial segmentation has been demonstrated previously, the challenges in this work are rapid localization and high accuracy over a large range of motion. The susceptibility artifacts produced by different paramagnetic materials will be characterized under a variety of imaging conditions, in order to devise robust artifact segmentation and localization methods. (Real-Time Tracking) To develop real-time tracking algorithmsbased on the passive fiducial detection developed in Aim 1that require minimal image support and fast imaging to provide interactive navigation for maneuvering interventional devices and robotic mechanisms. This will be achieved by developing new line fiducial geometries, fast image acquisition protocols (in conjunction with Project 1 of the proposed research program) and fast fiducial segmentation algorithms. (System Integration) To integrate the passive fiducial tracking system (Aim 1) with real-time tracking and control (Aim 2) in an interactive planning and navigation software interface developed jointly with Projects 4 and 5 of this research program. Planning and navigation are closely coupled, and must be developed jointly. This work aims to advance the field of image-guided minimally invasive intervention by allowing the physician to maneuver within a specified surgical space with greater accuracy and confidence. The passive, image-based tracking technology will be applicable to a wide range of problems that require accurate registration of surgical devices to the image space, as well as real-time interventional tracking and navigation. While attractive for the visual-servo of robotic devices within a closed MRI-scanner, this approach will also provide valuable feedback for the positioning of manually actuated or hand-held devices. This work will provide technology that is applicable at a broad range of clinical sites, and will help to establish minimally invasive image-guided therapy more widely.