Automated Mitosis Detection of Stem Cell Populations in Phase-Contrast Microscopy Images
Automated Mitosis Detection of Stem Cell Populations in Phase-Contrast Microscopy Images
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DOI：
10.1109/tmi.2010.2089384
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发表时间：
2011-03-01
影响因子：
10.6
通讯作者：
Kanade, Takeo
中科院分区：
文献类型：
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作者：
Huh, Seungil;Ker, Dai Fei Elmer;Kanade, Takeo
由于干细胞对再生医学的巨大潜力和影响，人们对以自动化和高通量方式分析和表征这些细胞体外行为的工具的兴趣迅速增长。在这些行为中，有丝分裂或细胞分裂是重要的，因为干细胞通过有丝分裂增殖和更新自己。然而，目前用于测量细胞增殖的自动化系统通常需要破坏性或牺牲性的细胞操作方法，例如细胞裂解或体外染色。在本文中，我们提出了一种有效的方法，自动有丝分裂检测使用相位对比延时显微镜，这是一种非破坏性的成像方式，从而允许连续监测培养中的细胞。在我们的方法中，我们提出了一个事件检测的概率模型，它可以同时1）识别时空补丁序列，包含有丝分裂事件和2）本地化的出生事件，定义为细胞分裂完成的时间和位置，两个子细胞出生。我们的方法显着优于以前的方法在检测精度和计算效率方面，当应用于多能C3 H10 T12间充质和C2 C12成肌细胞干细胞群体。
Due to the enormous potential and impact that stem cells may have on regenerative medicine, there has been a rapidly growing interest for tools to analyze and characterize the behaviors of these cells in vitro in an automated and high throughput fashion. Among these behaviors, mitosis, or cell division, is important since stem cells proliferate and renew themselves through mitosis. However, current automated systems for measuring cell proliferation often require destructive or sacrificial methods of cell manipulation such as cell lysis or in vitro staining. In this paper, we propose an effective approach for automated mitosis detection using phase-contrast time-lapse microscopy, which is a nondestructive imaging modality, thereby allowing continuous monitoring of cells in culture. In our approach, we present a probabilistic model for event detection, which can simultaneously 1) identify spatio-temporal patch sequences that contain a mitotic event and 2) localize a birth event, defined as the time and location at which cell division is completed and two daughter cells are born. Our approach significantly outperforms previous approaches in terms of both detection accuracy and computational efficiency, when applied to multipotent C3H10T1/2 mesenchymal and C2C12 myoblastic stem cell populations.