Ct3d：使用一种新的共分割方法在 3D 中追踪小胶质细胞的运动。

Ct3d: tracking microglia motility in 3D using a novel cosegmentation approach.

机构信息

Department of Biophysics, Institute of Neuroscience, Shanghai Institutes for Biological Sciences, 200031 Shanghai, China.

出版信息

Bioinformatics. 2011 Feb 15;27(4):564-71. doi: 10.1093/bioinformatics/btq691. Epub 2010 Dec 24.

DOI:10.1093/bioinformatics/btq691

PMID:21186244

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3035800/

Abstract

MOTIVATION

Cell tracking is an important method to quantitatively analyze time-lapse microscopy data. While numerous methods and tools exist for tracking cells in 2D time-lapse images, only few and very application-specific tracking tools are available for 3D time-lapse images, which is of high relevance in immunoimaging, in particular for studying the motility of microglia in vivo.

RESULTS

We introduce a novel algorithm for tracking cells in 3D time-lapse microscopy data, based on computing cosegmentations between component trees representing individual time frames using the so-called tree-assignments. For the first time, our method allows to track microglia in three dimensional confocal time-lapse microscopy images. We also evaluate our method on synthetically generated data, demonstrating that our algorithm is robust even in the presence of different types of inhomogeneous background noise.

AVAILABILITY

Our algorithm is implemented in the ct3d package, which is available under http://www.picb.ac.cn/patterns/Software/ct3d; supplementary videos are available from http://www.picb.ac.cn/patterns/Supplements/ct3d.

摘要

动机

细胞跟踪是定量分析延时显微镜数据的重要方法。虽然有许多方法和工具可用于跟踪 2D 延时图像中的细胞，但只有少数非常特定于应用的跟踪工具可用于 3D 延时图像，这在免疫成像中非常重要，特别是对于研究体内小胶质细胞的运动性。

结果

我们介绍了一种用于 3D 延时显微镜数据的新型细胞跟踪算法，该算法基于使用所谓的树分配在表示各个时间帧的分量树之间计算共分割。我们的方法首次允许在三维共聚焦延时显微镜图像中跟踪小胶质细胞。我们还在合成生成的数据上评估了我们的方法，证明即使在存在不同类型的不均匀背景噪声的情况下，我们的算法也是稳健的。