Diffeomorphic Registration with Density Changes for the Analysis of Imbalanced Shapes
Diffeomorphic Registration with Density Changes for the Analysis of Imbalanced Shapes
复制标题
用于不平衡形状分析的密度变化微分同胚配准
DOI：
10.1007/978-3-030-78191-0_3
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Charon, Nicolas.
中科院分区：
文献类型：
--
作者：
Hsieh, Hsi-Wei;Charon, Nicolas.
本文介绍了微分配准的扩展，使具有固有密度变化和不平衡的数据结构的形态分析成为可能。基于大差分对称度量匹配（LDDMM）配准和形状测量表示的框架，我们提出了一个额外的密度（或质量）转换过程来增强先前的测量变形方法。然后，我们推导了一个变分公式，用于联合估计两个测量之间的最佳变形和密度变化。基于所获得的最优性条件，我们推导了一种射击算法来数值估计解，并说明了该模型对几种几何数据（如纤维密度不一致的纤维束或不完整表面）的实际意义。
This paper introduces an extension of diffeomorphic registration to enable the morphological analysis of data structures with inherent density variations and imbalances. Building on the framework of Large Diffeomorphic Metric Matching (LDDMM) registration and measure representations of shapes, we propose to augment previous measure deformation approaches with an additional density (or mass) transformation process. We then derive a variational formulation for the joint estimation of optimal deformation and density change between two measures. Based on the obtained optimality conditions, we deduce a shooting algorithm to numerically estimate solutions and illustrate the practical interest of this model for several types of geometric data such as fiber bundles with inconsistent fiber densities or incomplete surfaces.
影响因子：
0.8
作者：
Richardson, Casey L.;Younes, Laurent
通讯作者：
Younes, Laurent
影响因子：
10.9
作者：
Durrleman, Stanley;Pennec, Xavier;Ayache, Nicholas
通讯作者：
Ayache, Nicholas
影响因子：
2.1
作者：
Charon, Nicolas;Trouve, Alain
通讯作者：
Trouve, Alain