Image-Based Navigation for Interventional Robotic Devices

介入机器人设备的基于图像的导航

• 批准号: 7255004
• 负责人: RANDALL P. ELLIS
• 金额: $ 19.07万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-04-01 至 2012-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7255004
• 关键词: Address; Algorithms; Anatomy; Architecture; Area; Articular Range of Motion; Biopsy; Cessation of life; Characteristics; Communities; Computer Interface; Computer software; Condition; Coupled; Detection; Devices; Diagnostic; Environment; Feedback; Focused Ultrasound Therapy; Hand; Hospitals; Image; Intervention; Invasive; Link; Location; Magnetic Resonance Imaging; Malignant Neoplasms; Malignant neoplasm of prostate; Medical; Medical Imaging; Methodology; Methods; Modality; Monitor; Morphologic artifacts; Motion; Navigation System; Needles; Numbers; Operative Surgical Procedures; Optics; Patients; Performance; Physicians; Placement; Positioning Attribute; Predisposition; Procedures; Prostate; Protocols documentation; Range; Range of motion exercise; Rate; Research; Resolution; Robotics; Sampling; Shapes; Specific qualifier value; Speed; Stereotaxis; Structure; Surgical Instruments; System; Systems Integration; Techniques; Technology; Therapeutic Intervention; Time; Tissues; United States; Update; Visual; Woman; Work; base; cancer therapy; clinical research site; design; image guided intervention; image guided therapy; image processing; instrument; magnetic field; multidisciplinary; programs; robotic device; soft tissue

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.

该项目旨在开发准确和健壮的方法来跟踪介入设备的运动。 在核磁共振引导的手术过程中。它将生产在核磁共振内精确放置针头的技术 扫描仪在实时图像引导和控制下。这项工作将为最低限度地 在包括癌症在内的各种医疗条件下的侵入性图像引导治疗。具体目标 详情如下： (被动基准定位)以开发准确和稳健的位置确定技术 通过在MRI图像中检测针头和被动基准点特有的敏感性伪影来检测针头和被动基准点。 虽然之前已经演示了基准分割，但这项工作面临的挑战很快 在大范围运动范围内的定位和高精度。产生的磁化率伪影 不同的顺磁材料将在不同的成像条件下进行表征，以便 设计稳健的伪影分割和定位方法。 (实时跟踪)开发基于被动基准检测的实时跟踪算法 在AIM 1中开发，只需最少的图像支持和快速成像即可提供交互 机动介入设备和机器人机构的导航。这将通过以下方式实现 开发新的直线基准几何图形、快速图像采集协议(与 所提出的研究方案)和快速基准分割算法。 (系统集成)将被动基准跟踪系统(目标1)与实时跟踪相结合 和控制(目标2)在与联合开发的交互式规划和导航软件界面中 本研究计划的项目4和5。规划和导航是紧密结合的，而且必须 共同开发。 这项工作旨在通过允许图像引导的微创介入治疗 医生以更高的精确度和信心在指定的手术空间内进行操作。被动的， 基于图像的跟踪技术将适用于广泛的需要精确跟踪的问题 将手术设备配准到图像空间，以及实时介入跟踪和 导航。虽然对于封闭核磁共振扫描仪中的机器人设备的视觉伺服很有吸引力，但这种方法 还将为手动或手持设备的定位提供有价值的反馈。这部作品 将提供适用于广泛临床站点的技术，并将有助于建立最低限度的 影像引导下的侵入性治疗越来越广泛。