This short article describes the method of digital cytopathology using Z-stack scanning with or without extended focusing. This technology is suitable to observe such thick clusters as adenocarcinoma on cytologic specimens. Artificial intelligence (AI) has been applied to histological images, but its application on cytologic images is still limited. This article describes our attempt to apply AI technology to cytologic digital images. For molecular analysis, cytologic materials, such as smear, LBC, and cell blocks, have been successfully used for targeted single gene detection and multiplex gene analysis with next-generation sequencing. As a future perspective, the system can be connected to full automation by combining digital cytopathology with AI application to detect target cancer cells and to perform molecular analysis. The literature review is updated according to the subjects.
Acta Cytologica

中文翻译：

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分子细胞学检测的数字/计算技术：带有文献综述的简短技术说明

这篇简短的文章描述了使用 Z-stack 扫描进行数字细胞病理学的方法，有或没有扩展聚焦。该技术适用于在细胞学标本上观察像腺癌这样的厚簇。人工智能（AI）已经应用于组织学图像，但其在细胞学图像上的应用仍然有限。本文描述了我们将 AI 技术应用于细胞学数字图像的尝试。在分子分析方面，细胞学材料，如涂片、LBC 和细胞块，已成功用于靶向单基因检测和二代测序的多重基因分析。从未来的角度来看，该系统可以通过将数字细胞病理学与人工智能应用相结合来实现全自动连接，以检测目标癌细胞并进行分子分析。
细胞学学报