A Review of Deep Learning Methods in Cervical Cancer Detection

Title

A Review of Deep Learning Methods in Cervical Cancer Detection

Creator

Lalasa M.; Thomas J.

Description

Cervical cancer is one of the most widespread and lethal malignancy that affects women aged 25 to 55 across the globe. Early detection of cervical cancer reduces burden of living and mortality drastically. Cervical cancer is caused through human papillomavirus transmitted sexually. Since the hereditary aspect is absent in cervical cancer, it can be cured completely if diagnosed early. Cervix cell image analysis is gold standard for classifying cervical cancer. Also known as pap smear, this histopathological test can provide dependable, and accurate diagnostic support. The current study examines the most recent research breakthroughs in deep learning models to classify cervical cancer. Three benchmark datasets are comprehensively described. Selective key classification models were implemented and comparative analysis was conducted on their performance. The findings of this study will allow researchers, publishers, and professionals to examine developing research patterns. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Source

Lecture Notes in Networks and Systems, Vol-648 LNNS, pp. 624-633.

Date

2023-01-01

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

Cervical Cancer; Deep Learning; Medical Image Classification

Coverage

Lalasa M., CHRIST (Deemed to be University), Kengeri, Bangalore, 560075, India; Thomas J., CHRIST (Deemed to be University), Kengeri, Bangalore, 560075, India

Rights

Restricted Access

Relation

ISSN: 23673370; ISBN: 978-303127523-4

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-3-031-27524-1_60

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152560734&doi=10.1007%2f978-3-031-27524-1_60&partnerID=40&md5=ceff89f97e84d867503c9c5f4f6b8483