An energy-based three-dimensional segmentation approach for the quantitative interpretation of electron tomograms
An energy-based three-dimensional segmentation approach for the quantitative interpretation of electron tomograms
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DOI：
10.1109/tip.2005.852467
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发表时间：
2005-09-01
影响因子：
10.6
通讯作者：
Subramaniam, S
中科院分区：
文献类型：
--
作者：
Bartesaghi, A;Sapiro, G;Subramaniam, S
电子断层扫描允许以比光学显微镜可能的分辨率显著更高的分辨率确定细胞和组织的三维结构。原则上，电子断层图像包含大量关于大量亚细胞组装体和细胞器的位置和结构的信息。由于生物电子显微镜图像固有的低信噪比，发展可靠的定量方法来分析断层图像中的特征是一个重要的问题，并且是一个具有挑战性的前景。这在一定程度上是生物标本极其复杂的结果。我们报告了一种新的方法，用于自动分割的HIV颗粒和选定的细胞室的电子断层扫描记录从固定的，塑料包埋的部分来自HIV感染的人巨噬细胞。使用一种新的强大的算法，发现它们的边界作为全球最小的表面在度量空间中定义的图像特征的断层图像中的各个功能进行分割。优化是在一个变换的球形域中进行的，中心是感兴趣的粒子的内部点，为快速准确地最小化分割能量提供了适当的设置。该方法提供了用于在细胞中组装的不同阶段对HIV颗粒进行半自动检测和统计评估的工具，并提供了与HIV感染的生化标志物相关的机会。这里开发的分割算法形成的电子断层图像的自动分析的基础上，将是特别有用的数据采集速率的快速增加。它还可以使研究更大的数据集，如那些可能从断层扫描分析艾滋病毒感染细胞的研究大人口。
Electron tomography allows for the determination of the three-dimensional structures of cells and tissues at resolutions significantly higher than that which is possible with optical microscopy. Electron tomograms contain, in principle, vast amounts of information on the locations and architectures of large numbers of subcellular assemblies and organelles. The development of reliable quantitative approaches for the analysis of features in tomograms is an important problem, and a challenging prospect due to the low signal-to-noise ratios that are inherent to biological electron microscopic images. This is, in part, a consequence of the tremendous complexity of biological specimens. We report on a new method for the automated segmentation of HIV particles and selected cellular compartments in electron tomograms recorded from fixed, plastic-embedded sections derived from HIV-infected human macrophages. Individual features in the tomogram are segmented using a novel robust algorithm that finds their boundaries as global minimal surfaces in a metric space defined by image features. The optimization is carried out in a transformed spherical domain with the center an interior point of the particle of interest, providing a proper setting for the fast and accurate minimization of the segmentation energy. This method provides tools for the semi-automated detection and statistical evaluation of HIV particles at different stages of assembly in the cells and presents opportunities for correlation with biochemical markers of HIV infection. The segmentation algorithm developed here forms the basis of the automated analysis of electron tomograms and will be especially useful given the rapid increases in the rate of data acquisition. It could also enable studies of much larger data sets, such as those which might be obtained from the tomographic analysis of HIV-infected cells from studies of large populations.