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Construction of statistical shape model of femoral bone using MR images

机译:利用MR图像构建股骨统计形状模型

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Due to inherent characteristic of having priori-information about the shape and appearance, statistical shape models (SSMs) are considered as powerful tools in 3D-MR image analysis. Such as, the SSMs of femoral bone can be used for quantification in knee surgeries, in particular, automated segmentation of femoral bony region to be applied in computer-aided surgical planning of anterior cruciate ligament (ACL) reconstruction. This paper mainly focuses on a method of automatically determining femoral coordinate system, and also constructing SSM of the femoral bone. The coordinate system is exploited to align MR images to a base space of equal voxel size for the purpose of registration. Finally, principal component analysis (PCA) is applied on high dimensional data obtained from signed distances of the registered images. The implemented model is evaluated by reconstructing images, utilizing standard deviation (SD) ratio for each eigenvector obtained from the model.
机译:由于具有关于形状和外观的先验信息的固有特性,统计形状模型(SSM)被认为是3D-MR图像分析中的强大工具。例如,股骨的SSM可用于膝盖外科手术中的量化,特别是股骨骨区域的自动分割,将其应用于前交叉韧带(ACL)重建的计算机辅助手术计划中。本文主要研究一种自动确定股骨坐标系的方法,并构建股骨的SSM。出于配准的目的,利用坐标系将MR图像对齐到体素大小相等的基本空间。最后,将主成分分析(PCA)应用于从配准图像的签名距离获得的高维数据。通过使用标准偏差(SD)比从从模型获得的每个特征向量重建图像来评估实现的模型。

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