计算机科学与探索2025，Vol.19Issue(6)：1476-1493,18.DOI:10.3778/j.issn.1673-9418.2407079
深度学习在宫颈细胞分割中的应用综述
Review of Application of Deep Learning in Cervical Cell Segmentation
摘要
Abstract
Cervical cancer is a common malignant tumor that threatens women's life and health.Its early diagnosis and treatment are very important for patients'life safety.However,due to the shortcomings of traditional manual examination in efficiency and consistency of results,it is urgent to use computer-aided technology to improve the accuracy and effi-ciency of diagnosis.In recent years,the rapid development of deep learning technology has been applied to the field of cervical cell segmentation,which has greatly improved the accuracy and speed of segmentation,and thus significantly im-proved the accuracy and efficiency of cervical cytology examination,providing strong technical support for the early diag-nosis of cervical cancer.In order to better understand the research status and progress of deep learning technology in the field of cervical cell segmentation,firstly,the widely used public cervical cell segmentation datasets are summarized.At the same time,the commonly used evaluation indicators are systematically summarized to better understand the perfor-mance of different models.Then,the specific application of deep learning technology in the field of cervical cell segmenta-tion is discussed,and the main improvement strategies,actual effects and limitations of different algorithms are compared in detail.Finally,the current challenges and problems in this field are analyzed,and the future research direction is pro-posed.关键词
宫颈癌/计算机辅助技术/深度学习/宫颈细胞分割Key words
cervical cancer/computer-aided technology/deep learning/cervical cell segmentation分类
计算机与自动化引用本文复制引用
朱佳音,李杨,李明,马金刚..深度学习在宫颈细胞分割中的应用综述[J].计算机科学与探索,2025,19(6):1476-1493,18.基金项目
国家自然科学基金(81973981,82074579) （81973981,82074579）
2022年山东省研究生优质教育教学资源项目(SDYAL2022041). This work was supported by the National Natural Science Foundation of China(81973981,82074579),and the Graduate High-Quality Education Teaching Resources Project of Shandong Province in 2022(SDYAL2022041). （SDYAL2022041）
