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用于微分同胚图像配准的变形场参数化及其在心肌轮廓描绘中的应用。

A parameterization of deformation fields for diffeomorphic image registration and its application to myocardial delineation.

作者信息

Chen Hua-Mei, Goela Aashish, Garvin Gregory J, Li Shuo

机构信息

Department of Medical Biophysics, UWO, London, Ontario.

出版信息

Med Image Comput Comput Assist Interv. 2010;13(Pt 1):340-8. doi: 10.1007/978-3-642-15705-9_42.

Abstract

This study investigates a new parameterization of deformation fields for image registration. Instead of standard displacements, this parameterization describes a deformation field with its transformation Jacobian and curl of end velocity field. It has two important features which make it appealing to image registration: 1) it relaxes the need of an explicit regularization term and the corresponding ad hoc weight in the cost functional; 2) explicit constraints on transformation Jacobian such as topology preserving and incompressibility constraints are straightforward to impose in a unified framework. In addition, this parameterization naturally describes a deformation field in terms of radial and rotational components, making it especially suited for processing cardiac data. We formulate diffeomorphic image registration as a constrained optimization problem which we solve with a step-then-correct strategy. The effectiveness of the algorithm is demonstrated with several examples and a comprehensive evaluation of myocardial delineation over 120 short-axis cardiac cine MRIs acquired from 20 subjects. It shows competitive performance in comparison to two recent segmentation based approaches.

摘要

本研究探讨了一种用于图像配准的变形场新参数化方法。该参数化方法不是用标准位移,而是用变换雅可比行列式和末速度场的旋度来描述变形场。它有两个重要特性,使其在图像配准中颇具吸引力:1)它放宽了对显式正则化项以及代价函数中相应临时权重的需求;2)对变换雅可比行列式的显式约束,如拓扑保持和不可压缩性约束,在统一框架中易于施加。此外,这种参数化方法自然地根据径向和旋转分量描述变形场,使其特别适合处理心脏数据。我们将微分同胚图像配准公式化为一个约束优化问题,并采用先逐步求解再校正的策略来解决。通过几个例子展示了该算法的有效性,并对从20名受试者获取的120幅短轴心脏电影磁共振成像进行了心肌轮廓的综合评估。与最近的两种基于分割的方法相比,它表现出了有竞争力的性能。

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