vioft2nntf2t|tblJournal|Abstract_paper|0xf4ff4e312c0000008fea0a0001000300 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.
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
Classification, MR Image, Cervical Cancer, CNN
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| Published By :
ICTACT
Published In :
ICTACT Journal on Image and Video Processing
( Volume: 12 , Issue: 2 , Pages: 2605-2609 )
Date of Publication :
November 2021
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269
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