Yoda Hiromi, Abe Kazuya, Takeo Hideya, Takamura-Enya Takeji, Koike-Takeshita Ayumi
Biomedical Research Center, Kanagawa Institute of Technology, 1030 Shimo-Ogino, Atsugi, Kanagawa, 243-0292, Japan.
Department of Applied Biosciences, Kanagawa Institute of Technology, Atsugi, Japan.
Genes Environ. 2024 Apr 24;46(1):11. doi: 10.1186/s41021-024-00305-9.
An in vitro micronucleus assay is a standard genotoxicity test. Although the technique and interpretation of the results are simple, manual counting of the total and micronucleus-containing cells in a microscopic field is tedious. To address this issue, several systems have been developed for quick and efficient micronucleus counting, including flow cytometry and automated detection based on specialized software and detection systems that analyze images.
Here, we present a simple and effective method for automated micronucleus counting using image recognition technology. Our process involves separating the RGB channels in a color micrograph of cells stained with acridine orange. The cell nuclei and micronuclei were detected by scaling the G image, whereas the cytoplasm was recognized from a composite image of the R and G images. Finally, we identified cells with overlapping cytoplasm and micronuclei as micronucleated cells, and the application displayed the number of micronucleated cells and the total number of cells. Our method yielded results that were comparable to manually measured values.
Our micronucleus detection (MN/cell detection software) system can accurately detect the total number of cells and micronucleus-forming cells in microscopic images with the same level of precision as achieved through manual counting. The accuracy of micronucleus numbers depends on the cell staining conditions; however, the software has options by which users can easily manually optimize parameters such as threshold, denoise, and binary to achieve the best results. The optimization process is easy to handle and requires less effort, making it an efficient way to obtain accurate results.
体外微核试验是一种标准的遗传毒性试验。尽管该技术和结果解读很简单，但在显微镜视野中手动计数总细胞数和含微核细胞数很繁琐。为解决这一问题，已开发出多种系统用于快速高效的微核计数，包括流式细胞术以及基于专门软件和图像分析检测系统的自动检测。
在此，我们提出一种使用图像识别技术进行自动微核计数的简单有效方法。我们的过程包括在吖啶橙染色的细胞彩色显微照片中分离RGB通道。通过缩放G图像检测细胞核和微核，而从R和G图像的合成图像中识别细胞质。最后，我们将细胞质和微核重叠的细胞识别为微核化细胞，该应用程序显示了微核化细胞的数量和细胞总数。我们的方法产生的结果与手动测量值相当。
我们的微核检测（MN/细胞检测软件）系统能够以与手动计数相同的精度准确检测显微图像中的细胞总数和形成微核的细胞数。微核数量的准确性取决于细胞染色条件；然而，该软件有一些选项，用户可以通过这些选项轻松手动优化诸如阈值、去噪和二值化等参数以获得最佳结果。优化过程易于操作且所需工作量较少，是获得准确结果的有效方法。
