Automated Detection and Classification of Cervical Cancer Using Pap Smear Microscopic Images: A Comprehensive Review and Future Perspectives

Abstract

Computer aided categorization of smear images has been considered challenging in the past few decades. Cervical cancer is a main cause of mortality among women worldwide and more prevalent in underdeveloped countries. This disease can be successfully treated, even fully cured, if detected at its early phase. Computerized image analysis methods are primarily of great interest as they provide significant benefits for clinicians with reliable and timely diagnosis of the samples. Dedicated image analysis algorithms provide mathematical description of the region of interest which provide a great support to pathologists for decision making. In this review, we have outlined state of the art techniques expressed in prominent publications on computer assisted diagnostic system for cancer detection. By utilizing the domain aspects of cervical cancer, suitable methods and techniques are explored and presented. This review also presents a knowledge to assess the methodology used in the literature and emphasized some of the inadequacies and weaknesses in the reviewed methods. The study accentuates the future directions pertinent to the development of cost-effective, automated disease classification system that should be a significant advantage for countries with limited resources and treatment services.

Digital health interventions for cervical cancer care: A systematic review and future research opportunities

“…Shanthi et al [24] conducted a comprehensive review of several algorithms for cervical cancer screening with the help of pap smear microscopic images. The authors of this article encouraged the adoption of machine learning based algorithms in cervical cancer diagnosis after reviewing several machine learning algorithms utilised in different studies.…”

Deep Neural Network for the Detection and Classification of Spontaneous Abortion Associated with Cervical Cancer

“…Regular screening can enhance cervical cancer prognosis at an early stage and improve the survival rate. If cervical cancer is accurately detected early, the mortality rate of patients can be decreased [1]. Analysis of pap smear images is utilized to obtain the diagnosis.…”

Exploring usability problems of mHealth applications developed for cervical cancer: An empirical study

“… 9 However, a number of studies have also been conducted to explore and evaluate the related scopes. 10 – 12 Mobile applications as well as online platforms can help to detect and prevent cervical cancer in its premature phase. For example, in Muljo et al, 13 a mobile is developed following the analysis, design, development, implementation, evaluation approach for early detection of cervical cancer in Indonesia.…”

“…In another study, Quercia et al 9 explored the uses of a mHealth application to collect data related to cervical cancer screening campaigns for monitoring the women participation in such campaigns. As such, cervical-cancer-related mobile apps can provide a solution for the detection, 10 classification, 12 and screening 16 of cervix cancer and creation of awareness among people to diminish health disparity through learning apps. 17 , 18 Moreover, the use of mobile health applications may provide betterment of the safety and gratification of the patient retaining the up-to-date health information.…”