A High-Resolution Atlas and Statistical Model of the Human Heart From Multislice CT
A High-Resolution Atlas and Statistical Model of the Human Heart From Multislice CT
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DOI：
10.1109/tmi.2012.2230015
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发表时间：
2013-01-01
影响因子：
10.6
通讯作者：
Frangi, Alejandro F.
中科院分区：
文献类型：
--
作者：
Hoogendoorn, Corne;Duchateau, Nicolas;Frangi, Alejandro F.
图谱和统计模型在心脏生理学的个性化和模拟中起着重要的作用。然而，对于心脏的研究，建立全面的地图集和时空模型面临着许多挑战，特别是需要处理大量和高度可变的图像数据集，心脏的多区域性质，以及复杂和小型心血管结构的存在。本文提出了一种基于大量3D+时间多层螺旋CT序列的详细的人体心脏图谱和时空统计模型，以及构建该模型的框架。它使用基于非刚性图像配准的空间归一化来合成群体平均图像，并建立该平均图像与群体中对象之间的空间关系。然后应用时间图像配准来解析每个受试者特定的心脏运动，并且所产生的变换被用于扭曲图谱的表面网格表示以适应每个受试者中剩余心脏时相的图像。随后，我们演示了形状时空统计模型的构建，从而适当地分离了主体间和动态变异源。该框架被应用于138个受试者的3D+时间数据集。这些数据来自不同的病理学，这有利于将其推广到新的学科和生理研究。与以前发表的大多数心脏模型相比，该图谱获得的细节水平和可扩充性具有优势。
Atlases and statistical models play important roles in the personalization and simulation of cardiac physiology. For the study of the heart, however, the construction of comprehensive atlases and spatio-temporal models is faced with a number of challenges, in particular the need to handle large and highly variable image datasets, the multi-region nature of the heart, and the presence of complex as well as small cardiovascular structures. In this paper, we present a detailed atlas and spatio-temporal statistical model of the human heart based on a large population of 3D+ time multi-slice computed tomography sequences, and the framework for its construction. It uses spatial normalization based on non-rigid image registration to synthesize a population mean image and establish the spatial relationships between the mean and the subjects in the population. Temporal image registration is then applied to resolve each subject-specific cardiac motion and the resulting transformations are used to warp a surface mesh representation of the atlas to fit the images of the remaining cardiac phases in each subject. Subsequently, we demonstrate the construction of a spatio-temporal statistical model of shape such that the inter-subject and dynamic sources of variation are suitably separated. The framework is applied to a 3D+ time data set of 138 subjects. The data is drawn from a variety of pathologies, which benefits its generalization to new subjects and physiological studies. The obtained level of detail and the extendability of the atlas present an advantage over most cardiac models published previously.