In automated screening of cervical cytology, the morphological features of cell play a determining role. To avoid false diagnosis, urgent need of precise extraction of these features led to emergence of new segmentation models. In this paper author aspire to present literature review of research done in the field of segmentation stage in automatic screening of cervical smear images. Total of 78 publications are considered for the time period of 40 years. A detailed study of segmentation technique proposed in each publication is considered, which presents a chronological development and up-gradation of segmentation models. This review assist researcher to have thorough knowledge of various state-of-art segmentation models and the problems and complexities required to be tackled, for unambiguous determination of malignancies in cervical cytology.

中文翻译：

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用于宫颈癌自动筛查的宫颈细胞分割：综述

在宫颈细胞学自动筛查中，细胞的形态特征起着决定性的作用。为了避免误诊，迫切需要精确提取这些特征导致了新的分割模型的出现。在本文中，作者渴望对在宫颈涂片图像自动筛选中的分割阶段领域所做的研究进行文献综述。在 40 年的时间段内，总共考虑了 78 篇出版物。考虑了对每个出版物中提出的分割技术的详细研究，其中介绍了分割模型的时间顺序发展和升级。该综述有助于研究人员全面了解各种最先进的分割模型以及需要解决的问题和复杂性，以便明确确定宫颈细胞学中的恶性肿瘤。