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首页> 外文期刊>Medical image analysis >Piecewise-diffeomorphic image registration: application to the motion estimation between 3D CT lung images with sliding conditions.
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Piecewise-diffeomorphic image registration: application to the motion estimation between 3D CT lung images with sliding conditions.

机译：分段微分图像配准：应用于具有滑动条件的3D CT肺部图像之间的运动估计。

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In this paper, we propose a new strategy for modelling sliding conditions when registering 3D images in a piecewise-diffeomorphic framework. More specifically, our main contribution is the development of a mathematical formalism to perform Large Deformation Diffeomorphic Metric Mapping registration with sliding conditions. We also show how to adapt this formalism to the LogDemons diffeomorphic registration framework. We finally show how to apply this strategy to estimate the respiratory motion between 3D CT pulmonary images. Quantitative tests are performed on 2D and 3D synthetic images, as well as on real 3D lung images from the MICCAI EMPIRE10 challenge. Results show that our strategy estimates accurate mappings of entire 3D thoracic image volumes that exhibit a sliding motion, as opposed to conventional registration methods which are not capable of capturing discontinuous deformations at the thoracic cage boundary. They also show that although the deformations are not smooth across the location of sliding conditions, they are almost always invertible in the whole image domain. This would be helpful for radiotherapy planning and delivery.
机译：在本文中，我们提出了一种在分段微分框架中配准3D图像时对滑动条件建模的新策略。更具体地说，我们的主要贡献是开发了一种数学形式主义，以执行带有滑动条件的大变形微分度量映射。我们还展示了如何使这种形式主义适应LogDemons微分注册框架。我们最终展示了如何应用该策略来估计3D CT肺图像之间的呼吸运动。对2D和3D合成图像以及来自MICCAI EMPIRE10挑战的真实3D肺部图像进行定量测试。结果表明，与无法捕获胸廓边界处不连续变形的常规配准方法相反，我们的策略估计了呈现滑动运动的整个3D胸腔图像体积的精确映射。他们还表明，尽管变形在滑动条件的位置上并不平滑，但在整个图像域中几乎总是可逆的。这将有助于放射治疗的计划和交付。

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