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ITR: Data-driven Human Knee Modeling for Expert Surgical Planning Systems

ITR: Data-driven Human Knee Modeling for Expert Surgical Planning Systems
ITR:用于专家手术计划系统的数据驱动的人体膝关节建模
批准号:
0325920
负责人:
Branislav Jaramaz
金额:
$104.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2003
资助国家:
美国
项目状态:
已结题
起止时间:
2003-09-15 至 2008-08-31
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项目摘要

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中文摘要
翻译
这项工作正在开发一种患者专用的模拟工具,它结合了医学图像和功能运动测量,以创建一个可靠的生物力学模型,适合于在植入植入物后对患者的膝关节生物力学进行术前和术中模拟。目前还没有患者专用的生物力学模拟器,应该通过产生理想的医疗器械和移植物放置的能力来改善患者的预后和生活质量。这项工作包括开发一种基于平行运动学结构的新型膝关节生物力学结构;从磁共振图像中自动生成患者特定的关节解剖几何模型,并从运动捕获数据中推导出软组织信息;以及手术规划器,以确定所需植入位置的性能,找到最佳植入位置,并模拟术后关节性能。平行运动学描述更真实地描述了膝关节的运动,目前的技术试图通过串联链中的简单旋转关节来模拟复杂的扭转运动。然后,通过将植入物插入到平行结构中并模拟结果,并优化植入物的放置以最大限度地提高手术的积极结果,来模拟潜在的手术结果。除了这项研究的技术成果外,更广泛的结果将包括改善接受膝关节植入和移植手术的患者的手术结果和生活质量。
英文摘要
This work is developing a patient specific simulation tool that combines medical images and functional motion measurements to create a reliable biomechanical model suitable for pre- and intraoperative simulation of a patient's knee biomechanics after insertion of a implant. There currently exists no patient specific biomechanics simulator, and patient outcomes and quality of life should be improved through the ability to produce an ideal placement of medical devices and grafts. The work involves development of a novel knee biomechanical structure, based on parallel kinematic structures; automatic generation of patient-specific geometric models of joint anatomy from magnetic resonance images and deduction of soft-tissue information from motion capture data; and a surgical planner to determine the performance of a desired implant location, find the optimal placement of the implant, and simulate postoperative joint performance.The parallel kinematic description more faithfully represents the motion of a knee, which undergoes complex twist motions that current techniques attempt to model with simple revolute joints in a serial chain. Potential surgical outcomes are then modeled by inserting implants into the parallel structure and simulating the outcome, and optimizing the placement of the implant to maximally improve the positive results of the procedure. In addition to the technical achievements of this research, the broader outcome will include improved surgical results and quality of life for patients undergoing knee implant and graft procedures.
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国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    40万元
  • 批准年份:
    2020
  • 负责人:
    Vikrant Gupta
  • 依托单位:
基于Linked Open Data的Web服务语义互操作关键技术
  • 批准号:
    61373035
  • 项目类别:
    面上项目
  • 资助金额:
    77.0万元
  • 批准年份:
    2013
  • 负责人:
    冯志勇
  • 依托单位: