Real-time Non-Rigid 3D Reconstruction and Registration for Laparoscopic-guided Minimally Invasive Liver Surgery

腹腔镜引导微创肝脏手术的实时非刚性 3D 重建和配准

• 批准号: 10611559
• 负责人: Haoyin Zhou
• 金额: $ 24.9万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-15 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10611559
• 关键词: 3-Dimensional; Address; Algorithms; Anatomy; Applications Grants; Area; Award; Basic Science; Binocular Vision; Blood; Carbon Dioxide; Clinical; Clinical Research; Color; Computer Vision Systems; Computer software; Data; Dependence; Devices; Diagnosis; Diagnostic; Environment; Excision; Family suidae; Feedback; Funding; Goals; Healthcare; Hemorrhage; Hepatic; Hospitals; Image; International; Knowledge; Laboratories; Laparoscopes; Laparoscopy; Learning; Liver; Liver neoplasms; Location; Machine Learning; Malignant neoplasm of liver; Maps; Medical; Medical Imaging; Medicine; Mentors; Methods; Modeling; Motion; Multimodal Imaging; Navigation System; Operating Rooms; Operative Surgical Procedures; Patients; Phase; Pneumoperitoneum; Postdoctoral Fellow; Procedures; Psyche structure; Recovery; Research; Research Personnel; Research Support; Respiration; Robotics; Solid; Stress; Structure; Supervision; Surface; Surgeon; Surgical Instruments; System; Technology; Texture; Time; Tissues; Titan; Training; Training and Education; Translational Research; Trauma patient; Ultrasonography; Uncertainty; United States National Institutes of Health; Woman; Work; Writing; X-Ray Computed Tomography; base; cancer diagnosis; career; career development; catalyst; deep learning; design; detection method; disorder prevention; experience; frontier; haptic feedback; human disease; image guided; image guided therapy; image processing; image registration; imaging facilities; improved; in vivo; machine learning algorithm; machine learning method; medical schools; minimally invasive; novel; postoperative recovery; professor; programs; prototype; radiologist; reconstruction; research and development; research clinical testing; symposium; technology development; three-dimensional visualization; tissue reconstruction; tool; tumor; uptake; virtual patient

Project Summary/Abstract Liver deformation leads to difficulties in tumor localization during minimally invasive liver surgery (MILS). The goal of this proposal is to develop an efficient surgical navigation tool for MILS by compensating for liver deformation and mapping preoperative data to the patient’s anatomy. Specifically, we will develop a non-rigid simultaneously localization and mapping (SLAM) approach to estimate the deformation of liver surface from stereo laparoscopy videos. We will develop machine-learning methods to detect landmarks and perform non- rigid registration. The algorithms will be implemented on a GPU to achieve real-time. Preliminary data has demonstrated the feasibility. During the R00 phase, we will mainly address the clinical needs and develop novel ways to provide intraoperative guidance. This project will greatly improve the tumor resection accuracy in MILS. The candidate for this award Dr. Haoyin Zhou is a postdoc at Surgical Planning Laboratory (SPL), Brigham and Women’s Hospital (BWH) and Harvard Medical School (HMS). Dr. Zhou has extensive experience and expertise in computer vision, machine learning and their applications in medicine. BWH is an international leader in basic, clinical and translational research on human diseases, and has established multiple research programs to promote the work and professional career development of young investigators. National Center for Image Guided Therapy, and Advanced Multi-modality Image Guided Operating (AMIGO) suite will greatly support this research. Dr. Zhou’s long-term research goal is to develop and apply advanced computer vision and machine learning technologies to improve understanding, diagnosis, treatment, and prevention of diseases for better health care. His long-term career goal is to become an independent investigator working at the frontier of medical image processing and image-guided therapy. To achieve these goals, Dr. Zhou plans to receive more education and training in the following four areas: (1) Critical training in conducting translational research in the hospital environment with surgeons and radiologists, (2) knowledge in the development of technologies for surgical guidance, (3) training in machine learning and its applications in medicine, and (4) training on writing grant applications independently and seeking funding. Dr. Zhou will participate in formal courses selected from Harvard, Harvard Catalyst, MIT CSAIL and Stanford Courses. He will attend weekly seminars at BWH, HMS and MIT. He will also attend one or two academic conferences per year to discuss his work and meet with experts in the field. A strong mentoring team, including one primary mentor, three co-mentors, and two collaborators, has been organized for the K99 phase of this award, which will provide solid support on both research and career development to Dr. Zhou based on their well-established expertise in diverse research fields. Prof. William M. Wells III (primary mentor) is a professor in medical image processing. Prof. Jayender Jagadeesan (co-mentor) is an assistant professor in surgical robotics and surgical navigation. Drs. Ali Tavakkoli and Jiping Wang (co- mentors) are experienced surgeons. All mentors and collaborators are from BWH, HMS.

项目摘要/摘要 在微创肝手术（MILS）期间，肝脏变形导致肿瘤定位难度。 该建议的目标是通过补偿肝脏开发有效的MILS手术导航工具 术前数据的变形和映射到患者的解剖结构中。具体来说，我们将发展一个非刚性 同样，定位和映射方法（猛击）方法可以估计肝表面的变形 立体声腹腔镜视频。我们将开发机器学习方法来检测地标并执行非 - 严格的注册。该算法将在GPU上实现以实现实时。初步数据具有 证明了可行性。在R00阶段，我们将主要满足临床需求并发展新颖 提供术中指导的方法。该项目将大大提高MILS的肿瘤切除精度。 该奖项的候选人Haoyin Zhou博士是外科计划实验室（SPL），Brigham和 妇女医院（BWH）和哈佛医学院（HMS）。 Zhou博士拥有丰富的经验和专业知识 在计算机视觉，机器学习及其在医学中的应用。 BWH是基本的国际领导者， 关于人类疾病的临床和翻译研究，并建立了多个研究计划 促进年轻调查员的工作和职业发展。国家图像指导中心 治疗和先进的多模式图像指导操作（Amigo）套件将极大地支持这项研究。 周博士的长期研究目标是开发和应用高级计算机视觉和机器学习 改善对疾病的理解，诊断，治疗和预防疾病的技术。 他的长期职业目标是成为在医学形象边界工作的独立研究员 加工和图像引导疗法。为了实现这些目标，周博士计划接受更多的教育和 在以下四个领域进行培训：（1）在医院进行转化研究的重要培训 与外科医生和放射科医生的环境，（2）在开发外科的技术方面 指导，（3）机器学习及其在医学中的应用以及（4）写作授予的培训 独立申请并寻求资金。周博士将参加从哈佛大学选出的正式课程， 哈佛大学催化剂，麻省理工学院Csail和斯坦福课程。他将在BWH，HMS和MIT参加每周的半手。他 还将每年参加一两个学术会议，讨论他的工作并与该领域的专家会面。 一支强大的心理团队，包括一名主要心理，三名联合主机和两个合作者 为该奖项的K99阶段组织，该奖项将为研究和职业提供可靠的支持 基于他们在潜水员研究领域的良好专业知识，向周博士开发。威廉·M。教授 Wells III（主要导师）是医学图像处理的教授。 Jayender Jagadeesan教授（联合学） 是手术机器人技术和外科导航的助理教授。博士。 Ali Tavakkoli和Jiping Wang（共同 导师）是经验丰富的外科医生。所有导师和合作者均来自HMS的BWH。