C3VFC: A Method for Tracing and Quantification of Microglia in 3D Temporal Images
C3VFC: A Method for Tracing and Quantification of Microglia in 3D Temporal Images
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DOI：
10.3390/app11136078
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发表时间：
2021-06
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影响因子：
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通讯作者：
Tiffany T. Ly;Jie Wang;K. Bisht;Ukpong B. Eyo;S. Acton
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作者：
Tiffany T. Ly;Jie Wang;K. Bisht;Ukpong B. Eyo;S. Acton
胶质细胞的自动重建对于小胶质细胞运动和形态的动态分析是必不可少的，特别是在神经退行性疾病的研究中。在本文中，我们提出了一个自动的三维跟踪算法，称为C3VFC，使用矢量场卷积找到临界点沿着的中心线的对象和跟踪路径，遍历回的索马的每个细胞在图像中。该解决方案提供随时间推移对图像中的多个细胞的检测和标记，从而实现多目标重建。重建结果可用于从不同环境下的时间数据中提取生物信息。C3VFC重建结果发现，与下一个最佳性能的最先进的跟踪方法相比，提高了53%。C3VFC在五种不同测量中的四种中达到了与基线结果相关的最高准确度分数：整体结构平均值、平均双向整体结构平均值、不同结构平均值和不同结构的百分比。
Automatic glia reconstruction is essential for the dynamic analysis of microglia motility and morphology, notably so in research on neurodegenerative diseases. In this paper, we propose an automatic 3D tracing algorithm called C3VFC that uses vector field convolution to find the critical points along the centerline of an object and trace paths that traverse back to the soma of every cell in an image. The solution provides detection and labeling of multiple cells in an image over time, leading to multi-object reconstruction. The reconstruction results can be used to extract bioinformatics from temporal data in different settings. The C3VFC reconstruction results found up to a 53% improvement on the next best performing state-of-the-art tracing method. C3VFC achieved the highest accuracy scores, in relation to the baseline results, in four of the five different measures: Entire structure average, the average bi-directional entire structure average, the different structure average, and the percentage of different structures.