Cervix Type Classification Using Convolutional Neural Networks

Abstract

Cervical cancer is still a significant cause of death, especially in developing countries. The detection and correct treatment of the disease is vital in its early stages. One of the key factors in selecting appropriate treatment is the identification of the cervix type. The objective of this work is to propose a Convolutional Neural Network (CNN) architecture to perform a classification of the cervix from a set of images published by Intel and MobileODT. The proposed architecture is combined with a preprocessing algorithm based on an assembly of color models to select the region of interest in the image. The obtained model provides better results than other models in which transfer learning is used or there is no preprocessing stage.