Time‐lapse confocal fluorescence microscopy images from mouse embryonic stem cells (ESCs) carrying reporter genes, histone H2B‐mCherry and Mvh‐Venus, have been used to monitor dynamic changes in cellular/differentiation characteristics of live ESCs. Accurate cell nucleus segmentation is required to analyse the ESC dynamics and differentiation at a single cell resolution. Several methods used concavities on nucleus contours to segment overlapping cell nuclei. Our proposed method evaluates not only the concavities but also the size and shape of every 2D nucleus region to determine if any of the strait, extrusion, convexity and large diameter criteria is satisfied to segment overlapping nuclei inside the region. We then use a 3D segmentation method to reconstruct simple, convex, and reasonably sized 3D nuclei along the image stacking direction using the radius and centre of every segmented region in respective microscopy images. To avoid false concavities on nucleus boundaries, fluorescence images of the H2B‐mCherry reporter are used for localisation of cell nuclei and Venus fluorescence images are used for determining the cell colony ranges. We use a series of image preprocessing procedures to remove noise outside and inside cell colonies, and in respective nuclei, and to smooth nucleus boundaries based on the colony ranges. We propose dynamic data structures to record every segmented nucleus region and solid in sets (volumes) of 3D confocal images. The experimental results show that the proposed image preprocessing method preserves the areas of mouse ESC nuclei on microscopy images and that the segmentation method effectively segment out every nucleus with a reasonable size and shape. All 3D nuclei in a set (volume) of confocal microscopy images can be accessed by the dynamic data structures for 3D reconstruction. The 3D nuclei in time‐lapse confocal microscopy images can be tracked to calculate cell movement and proliferation in consecutive volumes for understanding the dynamics of the differentiation characteristics about ESCs.

中文翻译：

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利用多通道共聚焦荧光图像自动三维分割小鼠胚胎干细胞核

来自携带报告基因、组蛋白 H2B-mCherry 和 Mvh-Venus 的小鼠胚胎干细胞 (ESC) 的延时共聚焦荧光显微镜图像已被用于监测活 ESC 细胞/分化特征的动态变化。在单细胞分辨率下分析 ESC 动力学和分化需要准确的细胞核分割。几种方法使用细胞核轮廓上的凹面来分割重叠的细胞核。我们提出的方法不仅评估凹度，还评估每个二维核区域的大小和形状，以确定是否满足任何海峡、挤压、凸度和大直径标准来分割区域内的重叠核。然后我们使用 3D 分割方法来重建简单的、凸的、并使用相应显微镜图像中每个分割区域的半径和中心沿图像堆叠方向合理大小的 3D 核。为避免细胞核边界出现错误的凹陷，H2B-mCherry 报告基因的荧光图像用于定位细胞核，而金星荧光图像用于确定细胞集落范围。我们使用一系列图像预处理程序来去除细胞集落内外以及各个细胞核中的噪声，并根据集落范围平滑细胞核边界。我们提出动态数据结构来记录每个分割的核区域和实体的 3D 共聚焦图像集（体积）。实验结果表明，所提出的图像预处理方法在显微图像上保留了小鼠 ESC 细胞核的区域，并且分割方法有效地分割出具有合理尺寸和形状的每个细胞核。一组（体积）共聚焦显微镜图像中的所有 3D 原子核都可以通过用于 3D 重建的动态数据结构访问。可以跟踪延时共聚焦显微镜图像中的 3D 细胞核，以计算连续体积中的细胞运动和增殖，从而了解 ESC 分化特征的动态。