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Spline-based elastic image registration: integration of landmark errors and orientation attributes

机译:基于样条的弹性图像配准:界标误差和方向属性的集成

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We introduce a spline-based elastic registration scheme which is based on a well-defined minimizing functional for which the solution can be stated analytically. In this work, we consider the integration of anisotropic landmark errors as well as additional attributes at landmarks. As attributes we use orientations at landmarks and we incorporate the corresponding constraints through scalar products. With our approximation scheme it is thus possible to integrate statistical as well as geometric information as additional knowledge in elastic image registration. On the basis of synthetic as well as real tomographic images we show that this additional knowledge can significantly improve the registration result. In particular, we demonstrate that our scheme incorporating orientation attributes can preserve the shape of rigid structures (such as bone) embedded in an otherwise elastic material. This is achieved without selecting further landmarks and without a full segmentation of the rigid structures. (C) 2003 Elsevier Science (USA). All rights reserved. [References: 40]
机译:我们介绍了基于样条的弹性配准方案,该方案基于定义明确的最小化函数,可以针对该函数解析地说明。在这项工作中,我们考虑了各向异性界标误差的集成以及界标处的其他属性。作为属性,我们在地标处使用方向,并通过标量乘积合并相应的约束。利用我们的近似方案,因此可以将统计信息和几何信息集成为弹性图像配准中的附加知识。根据合成的和真实的断层图像,我们显示出这些额外的知识可以显着改善配准结果。特别是,我们证明了结合方向属性的方案可以保留嵌入弹性材料中的刚性结构(例如骨骼)的形状。无需选择其他界标,也无需完全分割刚性结构即可实现。 (C)2003 Elsevier Science(美国)。版权所有。 [参考:40]

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