AN IMPROVED CLASSIFICATION OF MR IMAGES FOR CERVICAL CANCER USING CONVOLUTIONAL NEURAL NETWORKS

Abstract
Cervical cancer is the biggest cause of death in the field of women gynaecology. Patient treatment outcomes are influenced by the stage and nodal status of their cancers as well as their tumour size and histological classes. In this paper, we develop a classification model using a state-of-art heuristic mechanism that enables the use of deep learning algorithm to classify the MRI image from the input cervical images. The classification is conducted with highly dense network that helps to reduce the errors during the testing process. The simulation is conducted in matlab to test the efficacy of the model and the results of simulation shows that the proposed method achieves higher grade of classification accuracy than the other existing methods.

Authors
S Gowri1,Judith Justin2,R Vanithamani3
Avinashilingam Institute for Home Science and Higher Education for Women, India1,Avinashilingam Institute for Home Science and Higher Education for Women, India2, Avinashilingam Institute for Home Science and Higher Education for Women, India3

Keywords
Classification, MR Image, Cervical Cancer, CNN
Published By :
ICTACT
Published In :
ICTACT Journal on Image and Video Processing
( Volume: 12 , Issue: 2 )
Date of Publication :
November 2021
DOI :

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