Dufour Alexandre, Shinin Vasily, Tajbakhsh Shahragim, Guillén-Aghion Nancy, Olivo-Marin Jean-Christophe, Zimmer Christophe
Quantitative Image Analysis Group, Institut Pasteur, 75724 Paris Cedex 15, France.
IEEE Trans Image Process. 2005 Sep;14(9):1396-410. doi: 10.1109/tip.2005.852790.
Cell migrations and deformations play essential roles in biological processes, such as parasite invasion, immune response, embryonic development, and cancer. We describe a fully automatic segmentation and tracking method designed to enable quantitative analyses of cellular shape and motion from dynamic three-dimensional microscopy data. The method uses multiple active surfaces with or without edges, coupled by a penalty for overlaps, and a volume conservation constraint that improves outlining of cell/cell boundaries. Its main advantages are robustness to low signal-to-noise ratios and the ability to handle multiple cells that may touch, divide, enter, or leave the observation volume. We give quantitative validation results based on synthetic images and show two examples of applications to real biological data.
细胞迁移和变形在生物过程中发挥着重要作用，如寄生虫入侵、免疫反应、胚胎发育和癌症。我们描述了一种全自动分割和跟踪方法，旨在能够从动态三维显微镜数据中对细胞形状和运动进行定量分析。该方法使用多个有或没有边缘的活动表面，通过重叠惩罚进行耦合，并采用体积守恒约束来改善细胞/细胞边界的勾勒。其主要优点是对低信噪比具有鲁棒性，并且能够处理可能接触、分裂、进入或离开观察体积的多个细胞。我们给出了基于合成图像的定量验证结果，并展示了两个应用于真实生物数据的示例。
