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Coupled segmentation of nuclear and membrane-bound macromolecules through voting and multiphase level set

机译:通过投票和多相水平集耦合分割核和膜结合大分子

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Membrane-bound macromolecules play an important role in tissue architecture and cell-cell communication, and is regulated by almost one-third of the genome. At the optical scale, one group of membrane proteins expresses themselves as linear structures along the cell surface boundaries, while others are sequestered; and this paper targets the former group. Segmentation of these membrane proteins on a cell-by-cell basis enables the quantitative assessment of localization for comparative analysis. However, such membrane proteins typically lack continuity, and their intensity distributions are often very heterogeneous; moreover, nuclei can form large clump, which further impedes the quantification of membrane signals on a cell-by-cell basis. To tackle these problems, we introduce a three-step process to (i) regularize the membrane signal through iterative tangential voting, (ii) constrain the location of surface proteins by nuclear features, where clumps of nuclei are segmented through a delaunay triangulation approach, and (iii) assign membrane-bound macromolecules to individual cells through an application of multi-phase geodesic level-set. We have validated our method using both synthetic data and a dataset of 200 images, and are able to demonstrate the efficacy of our approach with superior performance. (C) 2014 Elsevier Ltd. All rights reserved.
机译:膜结合的大分子在组织结构和细胞间的通讯中起着重要的作用,并受近三分之一基因组的调控。在光学尺度上,一组膜蛋白沿着细胞表面边界表达为线性结构,而另一组则被隔离。本文针对的是前一组。这些膜蛋白在逐个细胞的基础上进行细分,可以对定位进行定量评估,以进行比较分析。但是,这种膜蛋白通常缺乏连续性,并且它们的强度分布通常非常不均一。此外,核可形成大团块,这进一步阻碍了逐细胞基础上膜信号的定量。为了解决这些问题,我们引入了一个三步过程:(i)通过迭代切向投票对膜信号进行正则化;(ii)通过核特征(通过delaunay三角剖分法对核团进行分段)来限制表面蛋白的位置, (iii)通过应用多相测地线水平集将膜结合的大分子分配给单个细胞。我们已经使用合成数据和200个图像的数据集验证了我们的方法,并且能够以优异的性能证明我们方法的有效性。 (C)2014 Elsevier Ltd.保留所有权利。

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