Atlas-based whole-body segmentation of mice from low-contrast Micro-CT data
Atlas-based whole-body segmentation of mice from low-contrast Micro-CT data
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DOI：
10.1016/j.media.2010.04.008
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发表时间：
2010-12-01
影响因子：
10.9
通讯作者：
Lelieveldt, Boudewijn P. F.
中科院分区：
文献类型：
--
作者：
Baiker, Martin;Milles, Julien;Lelieveldt, Boudewijn P. F.
本文提出了一种基于图谱的小鼠非对比增强Micro-CT数据全身分割的全自动方法。在这些研究中，小鼠的位置和姿势可能会在很大程度上变化，使横截面和随访研究中的数据比较复杂化。而且。Micro-CT通常只产生差的软组织对比度为腹部organs.To克服这些挑战，我们提出了一种方法，分为一个图集约束注册的基础上，在Micro-CT的高对比度器官（骨骼，肺和皮肤），和一个软组织近似的步骤，为低对比度器官的问题。我们首先提出了MOBY小鼠图谱的修改（Segars等人，2004）通过将骨架分割成单独的骨骼、通过添加解剖学上真实的关节类型以及通过定义分层图谱树描述。然后，穿过模型树层次结构，逐个配准该适配的MOBY图谱的各个骨骼以及肺。为此，我们采用迭代最近点方法，并根据关节类型和运动范围限制局部配准的自由度。这种基于图谱的策略使得该方法对扫描之间异常大的姿势差异和适度的病理性骨变形具有高度鲁棒性。躯干的皮肤注册采用一种新的方法匹配分布的测地线距离局部，受注册的骨架。由于腹部器官之间不存在图像对比度，因此使用薄板样条近似将它们从图谱内插到受试者域，薄板样条近似由已经建立的高对比度结构配准上的对应关系定义我们使用小鼠的26个非对比增强Micro-CT数据集以及皮肤配准和器官插值，使用15只小鼠的对比增强Micro-CT数据集。姿势和形状在动物之间变化显著，并且数据是在体内获得的。配准后，平均欧几里德距离分别小于骨骼和肺部的两个体素尺寸，小于皮肤的一个体素尺寸。手动分割和内插的骨骼和器官之间的体积重叠的骰子系数在肾脏的0.47 +/- 0.08和大脑的0.73 +/- 0.04之间变化。这些实验表明，该方法的有效性，克服异常大的变化的姿态，产生可接受的近似精度，即使在体内Micro-CT数据的软组织对比度的情况下，而不需要用户初始化。(c)2010爱思唯尔有限公司版权所有。
This paper presents a fully automated method for atlas-based whole-body segmentation in non-contrast-enhanced Micro-CT data of mice. The position and posture of mice in such studies may vary to a large extent, complicating data comparison in cross-sectional and follow-up studies. Moreover. Micro-CT typically yields only poor soft-tissue contrast for abdominal organs.To overcome these challenges, we propose a method that divides the problem into an atlas constrained registration based on high-contrast organs in Micro-CT (skeleton, lungs and skin), and a soft tissue approximation step for low-contrast organs. We first present a modification of the MOBY mouse atlas (Segars et al., 2004) by partitioning the skeleton into individual bones, by adding anatomically realistic joint types and by defining a hierarchical atlas tree description. The individual bones as well as the lungs of this adapted MOBY atlas are then registered one by one traversing the model tree hierarchy. To this end, we employ the Iterative Closest Point method and constrain the Degrees of Freedom of the local registration, dependent on the joint type and motion range. This atlas-based strategy renders the method highly robust to exceptionally large postural differences among scans and to moderate pathological bone deformations. The skin of the torso is registered by employing a novel method for matching distributions of geodesic distances locally, constrained by the registered skeleton. Because of the absence of image contrast between abdominal organs, they are interpolated from the atlas to the subject domain using Thin-Plate-Spline approximation, defined by correspondences on the already established registration of high-contrast structures (bones, lungs and skin).We extensively evaluate the proposed registration method, using 26 non-contrast-enhanced Micro-CT datasets of mice, and the skin registration and organ interpolation, using contrast-enhanced Micro-CT datasets of 15 mice. The posture and shape varied significantly among the animals and the data was acquired in vivo. After registration, the mean Euclidean distance was less than two voxel dimensions for the skeleton and the lungs respectively and less than one voxel dimension for the skin. Dice coefficients of volume overlap between manually segmented and interpolated skeleton and organs vary between 0.47 +/- 0.08 for the kidneys and 0.73 +/- 0.04 for the brain. These experiments demonstrate the method's effectiveness for overcoming exceptionally large variations in posture, yielding acceptable approximation accuracy even in the absence of soft-tissue contrast in in vivo Micro-CT data without requiring user initialization. (c) 2010 Elsevier B.V. All rights reserved.