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Region-Based PDEs for Cells Counting and Segmentation in 3D+Time Images of Vertebrate Early Embryogenesis

机译:基于区域的PDE用于脊椎动物早期胚胎发生的3D +时间图像中的细胞计数和分割

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This paper is devoted to the segmentation of cell nuclei from time lapse confocal microscopy images, taken throughout early Zebrafish embryogenesis. The segmentation allows to identify and quantify the number of cells in the animal model. This kind of information is relevant to estimate important biological parameters such as the cell proliferation rate in time and space. Our approach is based on the active contour model without edges. We compare two different formulations of the model equation and evaluate their performances in segmenting nuclei of different shapes and sizes. Qualitative and quantitative comparisons are performed on both synthetic and real data, by means of suitable gold standard. The best approach is then applied on a number of time lapses for the segmentation and counting of cells during the development of a zebrafish embryo between the sphere and the shield stage.
机译:本文致力于通过在整个斑马鱼早期胚胎发生过程中的延时共聚焦显微镜图像对细胞核进行分割。分割允许识别和量化动物模型中的细胞数量。这种信息与估计重要的生物学参数有关,例如时间和空间上的细胞增殖率。我们的方法基于没有边缘的主动轮廓模型。我们比较了模型方程的两种不同公式,并评估了它们在分割不同形状和大小的核中的性能。借助于合适的黄金标准,可以对合成数据和真实数据进行定性和定量比较。然后将最佳方法应用于多个时间段,以在球体和屏蔽阶段之间的斑马鱼胚胎发育过程中对细胞进行分割和计数。

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