A Comprehensive Survey on Diagnostic Microscopic Imaging Modalities, Challenges, Taxonomy, and Future Directions for Cervical Abnormality Detection and Grading

Abstract

Cancer is one of the most severe diseases, affecting the lives of many people in the modern world. Among the various types of cancer, cervical cancer is one of the most frequently occurring cancers in the female population. In most cases, doctors and practitioners can typically only identify cervical cancer in its latter stages. Planning cancer therapy and increasing patient survival rates become very difficult as the disease progresses. As a result, diagnosing cervical cancer in its initial stages has become imperative to arrange proper therapy and surgery. In this article, we present a survey of automatic computerized methods for diagnosing cervical abnormalities based on microscopic imaging modalities. The present survey was conducted by defining a novel taxonomy of the surveyed techniques based on the approaches they used. We also discuss the challenges and subchallenges associated with an automatic cervical cancer diagnosis based on microscopic imaging modalities. Additionally, surveys on various public and private datasets used by the research community for developing new methods are presented. In this article, the performances of published papers are compared. The article concludes by suggesting possible research directions in these fields.