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MEDICAL IMAGES REGISTRATION WITH A HIERARCHICAL ATLAS

机译:分层图集进行医学图像注册

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摘要

Atlas-based medical image segmentation is a well known method for including prior knowledge in medical image analysis. It requires as basic component the registration of an atlas with the image. In this paper, we introduce the concept of hierarchical atlas and show how to efficiently include it in a state-of-the-art non-rigid registration algorithm. We first present how to build a hierarchical atlas. Then we present the extension of a non-rigid registration algorithm, namely the B-spline Free Form Deformation (FFD), to a hierarchical version. The procedure includes first an affine registration to bring the atlas and the patient image in global correspondence. Then the non-rigid registration is performed layer by layer, i.e. registering the image with each layer of the hierarchical atlas, using the result of the registration of the previous layer as initial condition for the registration of the next layer. We show on 2D CT images that this approach gives better results than the non-rigid registration algorithm alone, in terms of registration accuracy.
机译:基于地图集的医学图像分割是一种在医学图像分析中包括先验知识的众所周知的方法。它要求将图集与图像配准作为基本组件。在本文中,我们介绍了分层图集的概念,并展示了如何有效地将其包含在最新的非刚性配准算法中。我们首先介绍如何构建分层图集。然后,我们提出了非刚性配准算法(即B样条自由格式变形(FFD))的扩展到分层版本。该过程首先包括仿射配准,以使图集和患者图像处于全局对应关系。然后,使用前一层的注册结果作为下一层注册的初始条件,逐层执行非刚性注册,即将图像注册到分层地图集的每一层。我们在2D CT图像上显示,就配准精度而言,此方法比单独的非刚性配准算法可提供更好的结果。

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