Nucleus Detection on Pap Smear Images for Cervical Cancer Diagnosis: A Review Analysis

Abstract

Cervical cancer is a cell disease in the cervix that develops out of control in the female body. The cervix links the vagina (birth canal) with the upper section of the uterus, which can only be found in the female body. This is the second leading cause of death among women around the world. However, cervical cancer is currently one of the most preventable cancers if early detection is identified. The effect of unidentified cancer may increase the risk of death when the cell disease spreads to other parts of the female anatomy (metastasize). The Papanicolaou test is a cervical cancer screening technique used to identify potentially precancerous and cancerous cells in women’s cervix. In this paper, a few popular detection method was applying and experimented on pap smear images. A few image quality assessment (IQA) was obtained in order to determine the best of detection method. The nucleus detection will help pathologists to diagnosis in early stages of cancer. The early detection is very important stage in order to reduce the cancer incidence and mortality. The method that needs to be invented in this study is the detection method. Image detection is the process of partitioning the image into multiple regions. The detection method is object detection and recognition as well as the boundary in images. The segmented Pap Smear image is one of the detection tools with many different methods that generated different results from different issues. The solution was by analysing different existing detection methods in order to compare the dissimilar performance of existing processes. The precision of the system performance needs to be improved in order to invent a new method. As predicted from the result, the innovative construction method must be proposed and compared in order to find accurate, comprehensive measures and proper sampling procedures by the features of the selection method.