Publication Date: 2023/04/13
Abstract: Cervical cancer is one of the main reasons of death from cancer in women. The complication of this cancer can be limited if it is diagnosed and treated at an early stage. Traditional screening of cervical cancer type classification majorly depends on the pathologist’s experience, which also has less accuracy. Colposcopy is a critical component of cervical cancer prevention. In conjunction with pre-cancer screening and treatment, colposcopy has played an essential role in lowering the incidence and mortality from cervical cancer over the last 50 years. However, due to the increase in workload, vision screening causes misdiagnosis and low diagnostic efficiency. Medical image processing using the convolutional neural network (CNN) model shows its superiority for the classification of cervical cancer type in the field of deep learning. In this work of ours we have made an attempt to develop a CNN model that identifies type of Cervical Cancer. And in turn helps doctors to treat as per the cancer stages.
Keywords: Cervical Cancer, CNN, Colposcopy
DOI: https://doi.org/10.5281/zenodo.7824611
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT23MAR2022.pdf
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