Robot-assisted prostate surgery using augmented reality with deformable models

使用增强现实和可变形模型进行机器人辅助前列腺手术

基本信息

  • 批准号:
    8206964
  • 负责人:
  • 金额:
    $ 10万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2011
  • 资助国家:
    美国
  • 起止时间:
    2011-09-15 至 2013-08-31
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): In this application, we describe our proposed work to develop an augmented display for improved visualization of the prostate and surrounding critical anatomy for robot-assisted prostate surgery. Prostate cancer is the second leading cause of cancer-related deaths in men in the United States. It is estimated that 217,730 men will be diagnosed with and 32,050 men will die of cancer of the prostate in 2010. Approximately 1 man in 6 will be diagnosed with prostate cancer during his lifetime and 1 in 36 will die from the disease. Early stage prostate cancer is potentially cured by surgery, which can be performed in a traditional, open fashion or laparoscopically. Recently, robot-assisted laparoscopic radical prostatectomy (RALP) using the da Vinci(R) surgical robot system has gained wide acceptance. Robotic systems improve surgeon dexterity by incorporating additional degrees of freedom at the end of the tools and offer increased precision and stability of movements. However, since the procedure is performed through small incisions, this technique reduces free sight and tactile feedback compared to open surgery. Surgeons also lose the ability to palpate the prostate to locate tumors and other critical structures such as neurovascular bundles (NVB). Surgeons must rely on visual cues from the video monitor and mentally correlate them with the underlying anatomy, often using information from medical images obtained prior to the procedure. Further complications arise from local deformations in the prostate tissue that occurs throughout the prostatectomy procedure due to the interaction between the surgical instruments and the prostate tissue. Subsequently, the anatomical model generated pre-operatively will need to be updated during the procedure to reflect this deformation. To address the clinical need for more accurate and reliable guidance, we propose to develop a navigation system that provides surgeons with an augmented reality (AR) view that fuses a pre-operative MRI model of the prostate, tumor and surrounding tissues with the da Vinci system laparoscopic video, while compensating for non-rigid prostate tissue deformation using intra-operative transrectal ultrasound (TRUS) imaging. PUBLIC HEALTH RELEVANCE: Prostate cancer is the second leading cause of cancer-related deaths in men in the United States. It is estimated that 217,730 men will be diagnosed with and 32,050 men will die of cancer of the prostate in 2010. Early stage prostate cancer is potentially cured by surgery, which can be performed using robot-assistance. However, current robot technology does not offer accurate and reliable visual guidance system for surgeons. To address this need, we propose to develop an augmented reality display for improved visualization of the prostate and surrounding critical anatomy robot-assisted prostate surgery.
描述(由申请人提供):在本申请中,我们描述了我们提出的开发增强显示器的工作,该增强显示器用于机器人辅助的前列腺手术的前列腺和周围关键解剖结构的改进的可视化。 前列腺癌是美国男性癌症相关死亡的第二大原因。 据估计,2010年将有217,730名男性被诊断患有前列腺癌,32,050名男性将死于前列腺癌。 大约六分之一的男性在其一生中会被诊断出患有前列腺癌,三十六分之一的男性会死于这种疾病。 早期前列腺癌有可能通过手术治愈,手术可以以传统的开放式方式或腹腔镜进行。 最近,使用da芬奇(R)手术机器人系统的机器人辅助腹腔镜根治性直肠癌切除术(RALP)已获得广泛接受。 机器人系统通过在工具末端增加额外的自由度来提高外科医生的灵活性,并提供更高的运动精度和稳定性。 然而,由于该手术是通过小切口进行的,因此与开放手术相比,该技术减少了自由视觉和触觉反馈。 外科医生也失去了触诊前列腺定位肿瘤和其他关键结构,如神经血管束(NVB)的能力。 外科医生必须依靠来自视频监视器的视觉提示,并在心理上将它们与底层解剖结构相关联,通常使用来自手术前获得的医学图像的信息。 由于手术器械和前列腺组织之间的相互作用,在整个前列腺切除术过程中发生的前列腺组织中的局部变形引起了进一步的并发症。 随后,需要在手术期间更新术前生成的解剖模型,以反映这种变形。 为了满足对更准确和可靠引导的临床需求,我们建议开发一种导航系统,为外科医生提供增强现实(AR)视图,将前列腺、肿瘤和周围组织的术前MRI模型与da芬奇系统腹腔镜视频融合,同时使用术中经直肠超声(TRUS)成像补偿非刚性前列腺组织变形。 公共卫生相关性:前列腺癌是美国男性癌症相关死亡的第二大原因。 据估计,2010年将有217,730名男性被诊断患有前列腺癌,32,050名男性将死于前列腺癌。 早期前列腺癌有可能通过手术治愈,手术可以使用机器人辅助进行。 然而,目前的机器人技术并不能为外科医生提供准确可靠的视觉引导系统。 为了满足这一需求,我们建议开发一种增强现实显示器,用于改善前列腺和周围关键解剖结构的可视化机器人辅助前列腺手术。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Andinet Asmamaw Enquobahrie其他文献

Andinet Asmamaw Enquobahrie的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Andinet Asmamaw Enquobahrie', 18)}}的其他基金

Virtual Rotator Cuff Arthroscopic Skill Trainer
虚拟肩袖关节镜技能训练器
  • 批准号:
    10248494
  • 财政年份:
    2019
  • 资助金额:
    $ 10万
  • 项目类别:
Imaging biomarkers of severe respiratory infections in premature infants Phase II
早产儿严重呼吸道感染的影像生物标志物 II 期
  • 批准号:
    10491039
  • 财政年份:
    2018
  • 资助金额:
    $ 10万
  • 项目类别:
Advanced virtual simulator for real-time ultrasound-guided renal biopsy training
用于实时超声引导肾活检训练的先进虚拟模拟器
  • 批准号:
    9408987
  • 财政年份:
    2017
  • 资助金额:
    $ 10万
  • 项目类别:
Real-time Image Guidance for Improved Orthognathic Surgery
实时图像引导改善正颌手术
  • 批准号:
    8710950
  • 财政年份:
    2014
  • 资助金额:
    $ 10万
  • 项目类别:
Image-guided planning system for skull correction in children with craniosynostos
颅缝早闭儿童颅骨矫正的图像引导规划系统
  • 批准号:
    8778815
  • 财政年份:
    2014
  • 资助金额:
    $ 10万
  • 项目类别:
Calibrated Methods for Quantitative PET/CT Imaging Phase II
定量 PET/CT 成像第二阶段的校准方法
  • 批准号:
    8979242
  • 财政年份:
    2012
  • 资助金额:
    $ 10万
  • 项目类别:
Approach-specific, multi-GPU, multi-tool, high-realism neurosurgery simulation
特定方法、多 GPU、多工具、高真实感神经外科模拟
  • 批准号:
    8037100
  • 财政年份:
    2010
  • 资助金额:
    $ 10万
  • 项目类别:

相似海外基金

DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks
DMS-EPSRC:机器学习中在线训练算法的渐近分析:循环、图形和深度神经网络
  • 批准号:
    EP/Y029089/1
  • 财政年份:
    2024
  • 资助金额:
    $ 10万
  • 项目类别:
    Research Grant
CAREER: Blessing of Nonconvexity in Machine Learning - Landscape Analysis and Efficient Algorithms
职业:机器学习中非凸性的祝福 - 景观分析和高效算法
  • 批准号:
    2337776
  • 财政年份:
    2024
  • 资助金额:
    $ 10万
  • 项目类别:
    Continuing Grant
CAREER: From Dynamic Algorithms to Fast Optimization and Back
职业:从动态算法到快速优化并返回
  • 批准号:
    2338816
  • 财政年份:
    2024
  • 资助金额:
    $ 10万
  • 项目类别:
    Continuing Grant
CAREER: Structured Minimax Optimization: Theory, Algorithms, and Applications in Robust Learning
职业:结构化极小极大优化:稳健学习中的理论、算法和应用
  • 批准号:
    2338846
  • 财政年份:
    2024
  • 资助金额:
    $ 10万
  • 项目类别:
    Continuing Grant
CRII: SaTC: Reliable Hardware Architectures Against Side-Channel Attacks for Post-Quantum Cryptographic Algorithms
CRII:SaTC:针对后量子密码算法的侧通道攻击的可靠硬件架构
  • 批准号:
    2348261
  • 财政年份:
    2024
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
CRII: AF: The Impact of Knowledge on the Performance of Distributed Algorithms
CRII:AF:知识对分布式算法性能的影响
  • 批准号:
    2348346
  • 财政年份:
    2024
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
CRII: CSR: From Bloom Filters to Noise Reduction Streaming Algorithms
CRII:CSR:从布隆过滤器到降噪流算法
  • 批准号:
    2348457
  • 财政年份:
    2024
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
EAGER: Search-Accelerated Markov Chain Monte Carlo Algorithms for Bayesian Neural Networks and Trillion-Dimensional Problems
EAGER:贝叶斯神经网络和万亿维问题的搜索加速马尔可夫链蒙特卡罗算法
  • 批准号:
    2404989
  • 财政年份:
    2024
  • 资助金额:
    $ 10万
  • 项目类别:
    Standard Grant
CAREER: Efficient Algorithms for Modern Computer Architecture
职业:现代计算机架构的高效算法
  • 批准号:
    2339310
  • 财政年份:
    2024
  • 资助金额:
    $ 10万
  • 项目类别:
    Continuing Grant
CAREER: Improving Real-world Performance of AI Biosignal Algorithms
职业:提高人工智能生物信号算法的实际性能
  • 批准号:
    2339669
  • 财政年份:
    2024
  • 资助金额:
    $ 10万
  • 项目类别:
    Continuing Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了