A Comprehensive Analysis of AI Methods for Cervical Cancer Detection
R.S. Remya, Kumudha Raimond · 2024
Cervical cancer is a significant health concern, being the fourth most common and deadliest cancer among women. Early detection is crucial for successful treatment, with the Pap smear test being the most commonly used method. However, manual screening can be time-consuming and prone to human error, leading to high false positive rates. In order to improve screening accuracy, researchers have developed many machine learning as well as deep learning approaches for the automatic segmentation and classification of cell pictures. In this paper, we conducted a comprehensive study of the different computer-aided diagnostic methods used for analysing cervical cytology images. The research findings offer valuable insights into the state-of-the-art in this field, highlighting the potential of these advanced technologies to enhance cervical cancer screening and save lives.