Validation Methods for Cell Cycle Analysis Algorithms in Confocal Fluorescence Images

D. Padfield, J. Rutscher, N. Thomas, B. Roysam
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Abstract

Automated analysis of live cells over extended time periods requires both novel assays and automated image analysis algorithms. Among other applications, this is necessary for studying the effect of inhibitor compounds that are designed to block the replication of cancerous cells. Due to their toxicity, fluorescent dyes that bind to the nuclear DNA cannot be used to mark nuclei, and traditional non-toxic nuclear markers do not yield information about the cell cycle phases. Instead, a non-toxic cell cycle phase marker can be used. We previously described a set of image analysis methods designed to automatically segment nuclei in such 2D time-lapse images. While the methods show promise, it is necessary to provide a validation framework for these methods. This paper introduces methods for validating the various stages of the algorithm in order to demonstrate their viability for automatic cell cycle analysis
共聚焦荧光图像细胞周期分析算法的验证方法
长时间内活细胞的自动分析需要新的分析方法和自动图像分析算法。在其他应用中,这对于研究旨在阻止癌细胞复制的抑制剂化合物的作用是必要的。由于其毒性,与细胞核DNA结合的荧光染料不能用于标记细胞核,而传统的无毒细胞核标记不能提供有关细胞周期阶段的信息。相反,可以使用无毒的细胞周期阶段标记物。我们之前描述了一套图像分析方法,旨在自动分割这种二维延时图像中的核。虽然这些方法很有前途,但有必要为这些方法提供一个验证框架。本文介绍了验证算法的各个阶段的方法,以证明它们在自动细胞周期分析中的可行性
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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