ICTACT Journal on Image and Video Processing

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Classification of Cervical Cancer in Women Using Convolutional Neural Network


Affiliations
1 Department of Computer Science and Engineering, Gnanamani College of Technology, India
2 Department of Computer Science, The Quaide Milleth College for Men, India
3 Department of Mechanical Engineering, Rathinam Technical Campus, India
4 Department of Computer Science and Engineering, Sri Eshwar College of Engineering, India
5 Department of Computer Science, Cork Institute of Technology, Ireland
     

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Cervical cancer is regarded as a serious threats to humanity, globally and this is a vital disease with huge spreading of virus that affects the health of humans. The virus is spreading at a rapid rate through mosquitoes that even may kill the one who is affected with cervical cancer. In this paper, we develop a quick response system that certainly finds the disease through a faster validation process. The study uses Convolutional Neural Network (CNN) as a deep learning model that classifies and predicts the condition or the infection status of a patient. The study uses a pre-processing model and a feature extraction model to prepare the image datasets for classification. The simulation is conducted to validate the effectiveness of the model over cervical cancer image datasets i.e. the blood samples of humans. The validation shows that the proposed method effectively classifies the patients in a faster manner than the other deep learning models.

Keywords

Machine Learning, Cervical Cancer, Classification, Diagnosis.
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  • Classification of Cervical Cancer in Women Using Convolutional Neural Network

Abstract Views: 176  |  PDF Views: 1

Authors

M. Ramkumar
Department of Computer Science and Engineering, Gnanamani College of Technology, India
R. Manikandan
Department of Computer Science, The Quaide Milleth College for Men, India
M. Punithavalli
Department of Mechanical Engineering, Rathinam Technical Campus, India
V. S. Akshaya4
Department of Computer Science and Engineering, Sri Eshwar College of Engineering, India
Shanmugaraj Madasamy
Department of Computer Science, Cork Institute of Technology, Ireland

Abstract


Cervical cancer is regarded as a serious threats to humanity, globally and this is a vital disease with huge spreading of virus that affects the health of humans. The virus is spreading at a rapid rate through mosquitoes that even may kill the one who is affected with cervical cancer. In this paper, we develop a quick response system that certainly finds the disease through a faster validation process. The study uses Convolutional Neural Network (CNN) as a deep learning model that classifies and predicts the condition or the infection status of a patient. The study uses a pre-processing model and a feature extraction model to prepare the image datasets for classification. The simulation is conducted to validate the effectiveness of the model over cervical cancer image datasets i.e. the blood samples of humans. The validation shows that the proposed method effectively classifies the patients in a faster manner than the other deep learning models.

Keywords


Machine Learning, Cervical Cancer, Classification, Diagnosis.

References