Bio-inspired Model Classification of Squamous Cell Carcinoma in Cervical Cancer using SVM

摘要

Cervical cancer is a deadly cancer which occurs in women's of all age group without any pre-symptoms. This cancer can be detected at the earliest by the manual screening of Pap smear test and LCB test which suffers from high false positive rate and cost effectiveness. To overcome this disadvantage an automatic computerised system is used to enhance the efficiency and sensitivity in the detection of cervical cancer. There are three types of tissues in the cervix region of uterus as Columnar Epithelium (CE), Squamous epithelium (SE) and the Aceto white (AW) region. The AW region, when immersed in 5% acetic shows a change of white colour as abnormal cervical cells. In this paper, a bio-inspired model is used for the automatic detection of cervical cancer where a support vector machine is used to classify the squamous cell carcinoma which will produce more accurate results by reducing the false positive rates.