Cooperative Control Robotics and Computer Vision: Development of Semi-Autonomous Temporal Bone and Skull Base Surgery

协作控制机器人和计算机视觉：半自主颞骨和颅底手术的发展

• 批准号: 10283480
• 负责人: Francis Xavier Creighton
• 金额: $ 19.18万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-06-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10283480
• 关键词: 3-Dimensional; Address; Adoption; Algorithms; Anatomy; Area; Atlases; Automobile Driving; Automobiles; Biomedical Engineering; Cadaver; Cochlea; Complex; Computer Vision Systems; Computers; Consumption; Data; Drug Delivery Systems; Dura Mater; Electromagnetics; Engineering; Equilibrium; Ethics; Facial nerve structure; Feedback; Future; Goals; Hand; Head and Neck Surgery; Hearing; Human; Image; Image-Guided Surgery; Intervention; Judgment; K-Series Research Career Programs; Knowledge; Labyrinth; Lateral; Left; Manuals; Mentors; Methods; Microscope; Modeling; Modernization; Monitor; Motion; Movement; Operative Surgical Procedures; Otolaryngology; Outcome; Patients; Positioning Attribute; Postoperative Period; Procedures; Process; Research; Research Personnel; Robot; Robotics; Safety; Scientist; Shapes; Sigmoid colon; Site; Speed; Structure; Surface; Surgeon; Surgical Instruments; Surgical complication; System; Tactile; Techniques; Technology; Temporal bone structure; Testing; Time; Training; Tremor; Update; Work; X-Ray Computed Tomography; automated segmentation; base; career; computer science; deep learning; digital; digital imaging; image guided; image registration; improved; instrument; learning network; medical schools; microscopic imaging; millimeter; multidisciplinary; neurovascular; novel; professor; responsible research conduct; robot control; simulation; skills; skull base; stereoscopic; success; surgery outcome; three-dimensional modeling; virtual; vision development

Project Summary I am an assistant professor in the department of Otolaryngology-Head and Neck Surgery at the Johns Hopkins School of Medicine, where my practice is focused on neurotology and lateral skull base surgery. I am applying for a mentored surgeon-scientist career development award (CDA) to obtain further training in robotics, deep learning and computer vision. This will further my long-term career goals of improving neurotologic surgical outcomes through novel applications of engineering methods and ultimately to investigate semi-autonomous, robotic interventions in the inner ear and skull base which are beyond the limits of the human hand alone. Operating in the temporal bone and lateral skull base is technically demanding due to complex three- dimensional anatomy, small working spaces and delicate neurovascular structures. Many of these challenges are ideally suited to semi-autonomous surgical platforms to augment a surgeon’s skills with robotic and image- guided assistance. Despite the widespread implementation of robotic surgery and image guidance in other areas of the body, the field of neurotology has had relatively little adoption of this technology. We believe one reason for this is the precise registration needed in this field, where millimeter differences differentiate a successful from a catastrophic result. This CDA proposes expanding on my prior work investigating cooperative control robotics and virtual safety barriers by using computer vision and deep learning networks to develop highly accurate surgical image registration. This CDA aims to provide me with multi-disciplinary training in the departments of Otolaryngology, Biomedical Engineering and Computer Science. Specific training goals include: (1) Training in robotics, statistical shape modeling and computer tomography landmark segmentation, (2) Training in deep learning networks and computer vision video image registration, (3) Integrating this training, with my knowledge of temporal bone and skull base surgery to develop into an independent investigator (4) Pursue additional training in the ethical and responsible conduct of research. The research plan addresses the hypothesis that virtual safety barriers can be accurately enforced by a cooperative control robot, and computer vision methods can be used to automate accurate placement and registration of these safety barriers. I believe that the integration of these techniques will allow for semi- autonomous surgical methods resulting in improved surgical safety and efficiency. The specific aims of the proposal are to: (1) Develop and Validate Cooperative Control Robot Enforced Virtual Safety Barriers for Cortical Mastoidectomy (2) Develop and Test Autonomous Segmentation of Lateral Skull Base Anatomy (3) Develop Video-Based, Fiducial-less, Surgical Image Registration to Detect and Update the 3-D Position of Temporal Bone Anatomy from Intraoperative Stereoscopic Microscope Video.

项目概要 我是约翰·霍普金斯大学耳鼻喉头颈外科系的助理教授 医学院，我的实践重点是神经外科和侧颅底手术。我正在申请 获得受指导的外科医生科学家职业发展奖（CDA），以获得机器人技术的进一步培训，深入 学习和计算机视觉。这将进一步推进我改善神经外科手术的长期职业目标 通过工程方法的新颖应用并最终研究半自主、 机器人对内耳和颅底的干预超出了人手的极限。 由于复杂的三层结构，在颞骨和侧颅底进行手术对技术要求很高。 立体解剖学、狭小的工作空间和精致的神经血管结构。其中许多挑战 非常适合半自主手术平台，通过机器人和图像增强外科医生的技能 指导帮助。尽管机器人手术和图像引导在其他领域得到广泛应用 在身体方面，神经学领域相对较少采用这项技术。我们相信一个原因 因为这是该领域所需的精确配准，毫米的差异区分了成功与否 灾难性的结果。该 CDA 建议扩展我之前研究合作控制的工作 通过使用计算机视觉和深度学习网络来开发高度机器人技术和虚拟安全屏障 准确的手术图像配准。该 CDA 旨在为我提供多学科培训 耳鼻喉科、生物医学工程和计算机科学系。具体培训目标包括： (1) 机器人技术、统计形状建模和计算机断层扫描地标分割方面的培训，(2) 深度学习网络和计算机视觉视频图像配准方面的培训，（3）整合本次培训， 凭借我对颞骨和颅底手术的了解，发展成为一名独立研究者 (4) 接受有关道德和负责任的研究行为的额外培训。 该研究计划提出了这样一个假设：虚拟安全屏障可以通过 协作控制机器人，利用计算机视觉方法，可实现自动化精确放置和 注册这些安全屏障。我相信这些技术的整合将允许半 自主手术方法提高了手术安全性和效率。该计划的具体目标 提案旨在： (1) 开发并验证协作控制机器人强制皮质虚拟安全屏障 乳突切除术 (2) 开发和测试横向颅底解剖结构的自主分割 (3) 开发 基于视频的无基准手术图像配准，用于检测和更新颞叶的 3D 位置 术中立体显微镜视频中的骨解剖。