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In-vivo kinematic analysis of the ACL-reconstructed knee using fuzzy ROI based 2-D/3-D image matching

使用基于模糊 ROI 的 2-D/3-D 图像匹配对 ACL 重建膝关节进行体内运动学分析

基本信息

批准号：
18591681
负责人：
YAGI Masayoshi
金额：
$ 2.08万
依托单位：
Hyogo College of Medicine
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2006
资助国家：
日本
起止时间：
2006 至 2007
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-18591681/
关键词：
Knee Kinematics Ligament CT

项目摘要

INTRODUCTION2-D/3-D image matching has been investigated as one of the attempts in kinematic analysis of the knees with ligamentous injuries. To date, however, high accuracy has not been achieved, and the clinical application is still limited. In this study, we proposed a fuzzy ROI (region of interest) based registration technique to improve the measurement quality. The purpose of this study was to evaluate the accuracy of our proposed method, and to assess its feasibility in the evaluation of the ACL-reconstructed knee.METHODSThe 3-D MDCT image was obtained using a 16-MDCT scanner, while the 2-D image was obtained with a digital radiography equipment fitted with a wide-vision flat panel detector. In the fuzzy ROI (region of interest) based2-D/3-D image mating, two types of ROIs (“attention region" with characteristic bony land mark and "taboo region" with murky bony contour) were determined. In the subsequent analysis, different values were applied to the ROIs and matching score was calculated. In the error analysis, computer-simulated image was generated and analyzed. The calculated errors were compared between the conventional gradient based registration and the fuzzy ROI based registration. Subsequently, our proposed method was applied to the ACL-reconstructed knees.RESULTSApplication of the fuzzy ROI based registration resulted in improved accuracy. The resultant error in rotation was calculated to be less than 0.5 degree with the application of our proposed method. In the analysis of the ACL-reconstructed knee and the contralateral intact knee, both overconstrained and underconstrained kinematic patterns were quatitatively identified.DISCUSSIONThis study showed that introduction of fuzzy ROI logic into the 2-D/3-D image matching could improve accuracy and efficiency of the analysis. Kinematic comparison between the normal and ACL-reconstructed knees will provide valuable information in evaluation of the quality of our surgical procedure.

引言2-D/3-D图像匹配已被调查的尝试之一，在膝关节韧带损伤的运动学分析。然而，迄今为止，尚未实现高精度，并且临床应用仍然受到限制。在这项研究中，我们提出了一个模糊的ROI（感兴趣区域）为基础的配准技术，以提高测量质量。本研究的目的是评估我们提出的方法的准确性，并评估其在ACL重建knee.METHODSThe 3-D MDCT图像的评价的可行性获得使用16-MDCT扫描仪，而2-D图像获得与数字化X线摄影设备配备了宽视野平板探测器。在基于2-D/3-D图像匹配的模糊感兴趣区域（regionofinterest，ROI）中，确定了两种类型的ROI：具有特征性骨性标志的“关注区域”和具有模糊骨性轮廓的“禁忌区域”。在随后的分析中，将不同的值应用于ROI并计算匹配分数。在误差分析中，生成了计算机模拟图像并进行了分析。比较了传统的基于梯度的配准方法和基于模糊感兴趣区域的配准方法的误差。随后，我们提出的方法被应用到ACL重建的膝盖上。计算结果表明，所提出的方法的应用，旋转误差小于0.5度。在ACL重建的膝关节和对侧完整的膝关节的分析中，过约束和欠约束的运动学模式都被quatiquietly identified. ExclusionThis研究表明，引入模糊ROI逻辑的2-D/3-D图像匹配可以提高分析的准确性和效率。正常膝关节和ACL重建膝关节之间的运动学比较将为评估我们的手术质量提供有价值的信息。