A review of Image Analysis and Machine Learning Techniques for Automated Cervical Cancer Screening from pap-smear image - Wasswa, William; Ware, Andrew; Basaza-Ejiri, Annabella Habinka; Obungoloch, Johnes (Computer methods and programs in biomedicine, 2018)
Early diagnosis and classification of a cancer type can help facilitate the subsequent clinical management of the patient. Cervical cancer ranks as the fourth most prevalent cancer affecting women worldwide and its early detection provides the opportunity to help save life. To that end, automated diagnosis and classification of cervical cancer from pap-smear images has become a necessity as it enables accurate, reliable and timely analysis of the condition's progress. This paper presents an overview of the state of the art as articulated in prominent recent publications focusing on automated detection of cervical cancer from pap-smear images.
Keywords: Machine learning; Medical imaging; Segmentation; Pap-smear images; Classification; Cervical cancer; Pap-smear