Open AccessCervix Type and Cervical Cancer Classification System Using Deep Learning Techniques
Author(s) -
Lidiya Wubshet Habtemariam,
Elbetel Taye Zewde,
Gizeaddis Lamesgin Simegn
Publication year - 2022
Publication title -
medical devices
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.482
H-Index - 30
ISSN - 1179-1470
DOI - 10.2147/mder.s366303
Subject(s) - cervical cancer , cervix , medicine , colposcopy , artificial intelligence , region of interest , cancer , histopathology , cohen's kappa , pap test , radiology , computer science , pathology , machine learning , cervical cancer screening
Cervical cancer is the 4th most common cancer among women, worldwide. Incidence and mortality rates are consistently increasing, especially in developing countries, due to the shortage of screening facilities, limited skilled professionals, and lack of awareness. Cervical cancer is screened using visual inspection after application of acetic acid (VIA), papanicolaou (Pap) test, human papillomavirus (HPV) test and histopathology test. Inter- and intra-observer variability may occur during the manual diagnosis procedure, resulting in misdiagnosis. The purpose of this study was to develop an integrated and robust system for automatic cervix type and cervical cancer classification using deep learning techniques.