Segmentation of Precursor Lesions in Cervical Cancer Using Convolutional Neural Networks

Abstract

Cervical carcinoma is one of the frequently seen cancers in the world and in our country, develops from precursor lesions. These precursor lesions are analyzed by pathologists so that the diagnosis of the disease can be made. In this study, a system that performs automatic detection of pre-cancerous lesions was performed using the convolutional neural networks (CNNs). In the training phase, lesion recognition performance of the proposed system has reached 92%. Thereafter, whole image was segmented by using 60 x 60 pixel tiles during the training phase. After all, the precursor lesions were segmented with 81.71% Dice coefficient.