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Deep Learning for Image-based Cervical Cancer Detection and Diagnosis — A Survey

机译:深度学习用于基于图像的宫颈癌的检测和诊断—一项调查

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Cervical cancer is the fourth most common type of cancer found in females with a record of 570,000 incidences and 311,000 deaths in the year 2018 worldwide. It is caused by a virus known as Human Papilloma Virus (HPV). Screening if done early can reduce this prevalence. However, manual screening methods are not efficient in the detection of cervical cancer as a result of some factors. This, however, results in misdiagnosis and over-treatment. Therefore, researchers proposed screening cervical automatically by using traditional and deep learning techniques. This paper aims to review past work that has been done particularly in the deep learning domain and discusses future directions in the automated detection of cervical cancer. It is believed that this will ensure proper diagnosis and could potentially reduce the prevalence of cervical cancer.
机译:宫颈癌是女性中发现的第四大常见癌症类型,2018年全世界有570,000例发病和311,000例死亡记录。它是由一种称为人乳头瘤病毒(HPV)的病毒引起的。如果尽早进行筛查可以降低这种患病率。但是,由于某些因素,手动筛查方法在检测子宫颈癌方面效率不高。但是,这会导致误诊和过度治疗。因此,研究人员提出了使用传统的深度学习技术自动筛查宫颈的方法。本文旨在回顾过去特别是在深度学习领域所做的工作,并讨论了宫颈癌自动检测的未来方向。相信这将确保正确的诊断,并有可能降低子宫颈癌的患病率。

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