Various Methods in Texture Analysis and Classification Techniques used in Cervical Cancer Detection

Cancer is one of the deadliest diseases which puts human life at risk. Among various types of cancer, the most common malignancy among women that results in mortality is cervical cancer. Early detection of Cervical cancer is hard to detect because it does not have any external manifestation of the disease. A Pap smear is one of the clinical procedures to find cervical cancer but it is not accurate always. Also, it is a very sensitive process and also consumes a lot of time. Several diagnostic techniques like MRI, CT, etc, can be used with various imaging methods to detect cervical cancer. This review paper aims at analyzing various images acquired by imaging tools for the detection of malignant tissues in the cervical region using image processing techniques and feature extraction techniques. The work also gives a comprehensive study on Texture analysis and methods used in the classification of textured images using AI, Machine learning, and deep learning processes.