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Non-rigid Diffeomorphic Image Registration of Medical Images Using Polynomial Expansion

机译:使用多项式展开的医学图像非刚性微分图像配准

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The use of polynomial expansion in image registration has previously been shown to be beneficial due to fast convergence and high accuracy. However, earlier work has only briefly out-lined how non-rigid image registration is handled, e.g. not discussing issues like regularization of the displacement field or how to accumulate the displacement field. In this work, it is shown how non-rigid image registration based upon polynomial expansion can be integrated into a generic framework for non-rigid image registration achieving diffeomorphic displacement fields. The proposed non-rigid image registration algorithm using diffeomorphic field accumulation is evaluated on both synthetically deformed data and real image data and compared to additive field accumulation. The results clearly demonstrate the power of the diffeomorphic field accumulation.
机译:由于快速收敛和高精度,先前已证明在图像配准中使用多项式展开是有益的。但是,早期的工作只是简要概述了如何处理非刚性图像配准,例如没有讨论诸如位移场正则化或如何累积位移场之类的问题。在这项工作中,显示了如何将基于多项式展开的非刚性图像配准如何集成到用于实现非定形位移场的非刚性图像配准的通用框架中。拟议的使用非定形场累积的非刚性图像配准算法对合成变形数据和真实图像数据均进行了评估,并与加性场累积进行了比较。结果清楚地证明了微晶场积累的力量。

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