课题基金 / 基金详情

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

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:
10625473
负责人:
Haoyin Zhou
金额:
$24.9万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
未结题
起止时间:
2019-09-15 至 2025-05-31
关键词:
3-DimensionalAddressAlgorithmsAnatomyApplications GrantsAreaAwardBasic ScienceBinocular VisionBloodCarbon DioxideClinicalClinical ResearchColorCompensationComputer Vision SystemsComputer softwareDataDependenceDevicesDiagnosisDiagnosticEnvironmentExcisionFamily suidaeFeedbackFundingGoalsHealthcareHemorrhageHepaticHospitalsImageInternationalKnowledgeLaboratoriesLaparoscopesLaparoscopyLearningLiverLiver neoplasmsLocationMachine LearningMalignant neoplasm of liverMapsMedicalMedical ImagingMedicineMentorsMethodsModelingMotionMultimodal ImagingNavigation SystemOperating RoomsOperative Surgical ProceduresPatientsPhasePneumoperitoneumPostdoctoral FellowProceduresPsyche structureRecoveryResearchResearch PersonnelResearch SupportRespirationRoboticsSolidStressStructureSupervisionSurfaceSurgeonSurgical InstrumentsSystemTechnologyTextureTimeTissuesTitanTrainingTraining and EducationTranslational ResearchTrauma patientUltrasonographyUncertaintyUnited States National Institutes of HealthVisualizationWomanWorkWritingX-Ray Computed Tomographycancer diagnosiscareercareer developmentcatalystdeep learningdesigndetection methoddisorder preventionexperiencefrontierhaptic feedbackhuman diseaseimage guidedimage guided therapyimage processingimage registrationimaging facilitiesimprovedin vivomachine learning algorithmmachine learning methodmedical schoolsminimally invasivenovelpostoperative recoveryprofessorprogramsprototyperadiologistreconstructionresearch and developmentresearch clinical testingsymposiumtechnology developmentthree-dimensional visualizationtissue reconstructiontooltumoruptakevirtual patient

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中文摘要
翻译
项目概要/摘要 肝脏变形是微创肝脏手术(MILS)中肿瘤定位的难点。的 本提案的目标是通过补偿肝脏,为MILS开发一种有效的手术导航工具 变形和将术前数据映射到患者的解剖结构。具体来说,我们将制定一个非刚性的 同时定位和映射(SLAM)的方法来估计肝脏表面的变形, 立体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 刚性配准算法将在GPU上实现,以实现实时性。初步数据显示, 证明了可行性。在R 00阶段,我们将主要解决临床需求,并开发新的 提供术中指导的方法。该项目将大大提高MILS中肿瘤切除的准确性。 该奖项的候选人Haoyin Zhou博士是外科规划实验室(SPL)的博士后,Brigham和 妇女医院(BWH)和哈佛医学院(HMS)。周博士拥有丰富的经验和专业知识 计算机视觉、机器学习及其在医学中的应用。BWH是一家国际领先的基础, 人类疾病的临床和转化研究,并建立了多个研究项目, 促进年轻调查员的工作和职业发展。国家图像引导中心 治疗和先进的多模态图像引导操作(AMIGO)套件将大大支持这项研究。 博士周的长期研究目标是开发和应用先进的计算机视觉和机器学习 提高对疾病的理解、诊断、治疗和预防的技术,以改善医疗保健。 他的长期职业目标是成为一名在医学影像前沿工作的独立调查员 处理和图像引导治疗。为了实现这些目标,周博士计划接受更多的教育, 在以下四个方面进行培训:(1)在医院进行转化研究的关键培训 与外科医生和放射科医生的环境,(2)在外科手术技术的发展知识, 指导,(3)机器学习及其在医学中的应用培训,以及(4)写作补助金培训 独立申请并寻求资助。周博士将参加从哈佛挑选的正式课程, 哈佛催化剂,麻省理工学院CSAIL和斯坦福大学课程。他将参加每周在BWH,HMS和麻省理工学院的研讨会。他 他还将每年参加一到两次学术会议,讨论他的工作,并与该领域的专家会面。 一个强大的指导团队,包括一名主要导师,三名共同导师和两名合作者, 该奖项的K99阶段,这将提供研究和职业生涯的坚实支持 周博士的发展基于他们在不同研究领域的成熟专业知识。William M. 威尔斯三世(主要导师)是医学图像处理教授。Jayender Jagadeesan教授(共同导师) 是外科机器人和外科导航的助理教授。Ali Tavakkoli博士和Jiping Wang博士(合作伙伴) 导师)是经验丰富的外科医生。所有的导师和合作者都来自BWH,HMS。
英文摘要
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.
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Real-time Non-Rigid 3D Reconstruction and Registration for Laparoscopic-guided Minimally Invasive Liver Surgery
  • 批准号:
    10611559
  • 项目类别:
  • 资助金额:
    $24.9万
  • 财政年份:
    2019
  • 负责人:
    Haoyin Zhou
  • 依托单位:
Real-time Non-Rigid 3D Reconstruction and Registration for Laparoscopic-guided Minimally Invasive Liver Surgery
  • 批准号:
    10017968
  • 项目类别:
  • 资助金额:
    $9.32万
  • 财政年份:
    2019
  • 负责人:
    Haoyin Zhou
  • 依托单位:
海外基金