Designing a robotic system that functions effectively within the specific environment of a Magnetic Resonance Imaging (MRI) scanner requires solving numerous technical issues, such as maintaining the robot's precision and stability under strong magnetic fields. This research focuses on enhancing MRI's role in medical imaging, especially in its application to guide intravascular interventions using robot-assisted devices. A newly developed computational system is introduced, designed for seamless integration with the MRI scanner, including a computational unit and user interface. This system processes MR images to delineate the vascular network, establishing virtual paths and boundaries within vessels to prevent procedural damage. Key findings reveal the system's capability to create tailored magnetic field gradient patterns for device control, considering the vessel's geometry and safety norms, and adapting to different blood flow characteristics for finer navigation. Additionally, the system's modeling aspect assesses the safety and feasibility of navigating pre-set vascular paths. Conclusively, this system, based on the Qt framework and C/C++, with specialized software modules, represents a major step forward in merging imaging technology with robotic aid, significantly enhancing precision and safety in intravascular procedures.

翻译：设计一种能在磁共振成像（MRI）扫描仪特定环境中有效运行的机器人系统，需要解决众多技术难题，例如在强磁场下保持机器人的精度与稳定性。本研究旨在增强MRI在医学成像中的作用，特别是在机器人辅助设备引导血管内介入治疗中的应用。本文介绍了一种新开发的计算系统，该系统设计用于与MRI扫描仪无缝集成，包含计算单元与用户界面。该系统通过处理MR图像来描绘血管网络，在血管内建立虚拟路径与边界，以防止手术损伤。关键结果表明，该系统能够根据血管几何形状与安全规范，生成用于设备控制的定制化磁场梯度模式，并能适应不同的血流特性以实现更精细的导航。此外，系统的建模功能可评估沿预设血管路径导航的安全性与可行性。总之，该系统基于Qt框架与C/C++语言开发，配备专用软件模块，代表了成像技术与机器人辅助融合的重要进展，显著提升了血管内手术的精确度与安全性。