Classifying Papanicolaou cervical smears through a cell merger approach by deep learning technique

作者：

Highlights：

• Proposed a deep learning model to detect cervical cancer.

• Proposed a cell merger model to classify in a similar way to real smear examination.

• Classification of squamous cells without prior image preprocessing.

• Classification of squamous cells in HSIL, LSIL, ASCUS and normal.

• Detection of cervical squamous atypiae with 88.8% accuracy in classification.

摘要

•Proposed a deep learning model to detect cervical cancer.•Proposed a cell merger model to classify in a similar way to real smear examination.•Classification of squamous cells without prior image preprocessing.•Classification of squamous cells in HSIL, LSIL, ASCUS and normal.•Detection of cervical squamous atypiae with 88.8% accuracy in classification.

论文关键词：Papanicolaou Cervical Smears,Deep Learning,Convolutional Neural Network,Image classification

论文评审过程：Received 7 April 2020, Revised 31 May 2020, Accepted 29 June 2020, Available online 19 July 2020, Version of Record 28 July 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113707