Classification of cervical cancer using Dense CapsNet with Seg-UNet and denoising autoencoders

Abstract Cervical cancer is one of the deadly diseases that affects women, which requires periodic examinations to identify and treat any cancerous tumors at a preliminary stage. The most prevalent examination tool for cervical cancer prompt identification is the cervical smear (Pap smear) testing;...

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Egile Nagusiak:	Hui Yang, Walid Aydi, Nisreen Innab, Mohamed E. Ghoneim, Massimiliano Ferrara
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	Nature Portfolio 2024-12-01
Saila:	Scientific Reports
Gaiak:	Cervical cancer Deep learning Segmentation Autoencoders Dense CapsNet
Sarrera elektronikoa:	https://doi.org/10.1038/s41598-024-82489-2
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