Recent advancement in cervical cancer diagnosis for automated screening: a detailed review

Abstract

Cervical cancer is one of the most common and dangerous diseases for women. Initial diagnosis and classification of cervical cancer are to reduce the mortality rate. The Pap smear images are widely employed for the detection of cervical cancer in an automated manner; thereby, it enables reliable and accurate results. Recently, different kinds of soft computing techniques are used to deal with cervical cancer detection. In order to gain insight into recent advancements in the fields of study, this paper analyses most research papers between January 2010 and December 2020. This paper presents the graphical and organized view of the recent research works. The study explored the scope for further research in soft computing methods for the segmentation and classification of cervical cancer. The review also carried out an analysis of cervical cancer detection by categorizing the referred papers into techniques focused on soft computing. This study will provide information for researchers, publishers, and experts to examine emerging research patterns in the field of cervical cancer detection from pap smear images.