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Fuzzy ROI Based 2-D/3-D Registration for Kinetic Analysis after Anterior Cruciate Ligament Reconstruction

机译:基于模糊ROI的2-D / 3-D用于动力学分析后的动力学分析重建后的动力学分析

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Rupture of anterior cruciate ligament (ACL) is a serious problem for playing sports, which causes in functional stability of the knee joint. To restore this problem, various operation techniques of ACL reconstruction are proposed. Thus, it is important to numerically characterize the knee kinematics after ACL reconstruction. Then, we proposed an analysis method to estimate the three-dimensional (3-D) knee kinematics. However, the estimation accuracy was not enough. Because the target image did not have high contrast, for example, at the boundary between the femoral bone and the tibial bone. Then, born regions can not be extracted preciously because the target image has low contrast. In this paper, we propose a fuzzy ROI (region of interests) based image registration. This method attend the region where has clear contour of bone region and ignore the region where has murky contour of bone region, by using fuzzy degree map which is assigned by the fuzzy region of interests (ROI).
机译:前十字架韧带(ACL)的破裂是运动运动的严重问题,这导致膝关节的功能稳定性。为了恢复这个问题,提出了ACL重建的各种操作技术。因此,重要的是在ACL重建后数值表征膝关节运动学。然后,我们提出了一种分析方法来估计三维(3-D)膝关节运动学。但是,估计准确性还不够。因为目标图像没有高对比度,例如,在股骨骨和胫骨之间的边界处。然后,由于目标图像对比度,因此不能精确地提取出生的区域。在本文中,我们提出了一种基于图像配准的模糊ROI(利益区域)。该方法参加骨区域清晰轮廓的区域,并通过使用由模糊的感兴趣区域(ROI)分配的模糊程度图来忽略骨骼区域的阴影轮廓的区域。

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