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

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.