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Classification of Cervical Cancer Cells in Pap Smear Screening Test


Affiliations
1 Department of Centre for Information Technology and Engineering, Manonmaniam Sundaranar University, India
2 Department of Computer Application, Sengamala Thayaar Educational Trust Women’s College, India
     

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Cervical cancer is second topmost cancers among women but also, it was a curable one. Regular smear test can discover the sign of precancerous cell and treated the patient according to the result. However sometimes the detection errors can be occurred by smear thickness, cell overlapping or by un-wanted particles in the smear and cytotechnologists faulty diagnosis. Therefore the reason automatic cancer detection was developed. This was help to increase cancer cell mindfulness, diagnosis accuracy with low cost. This detection process consists of some techniques of the image preprocessing that is segmentation and effective texture feature extraction with SVM classification. Then the Final Classification Results of this proposed technique was compared to the previous classification techniques of KNN and ANN and the result would be very useful to cytotechnologists for their further analysis.

Keywords

Cancer, Cervical Cancer, Classification.
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Abstract Views: 278

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  • Classification of Cervical Cancer Cells in Pap Smear Screening Test

Abstract Views: 278  |  PDF Views: 2

Authors

S. Athinarayanan
Department of Centre for Information Technology and Engineering, Manonmaniam Sundaranar University, India
M. V. Srinath
Department of Computer Application, Sengamala Thayaar Educational Trust Women’s College, India

Abstract


Cervical cancer is second topmost cancers among women but also, it was a curable one. Regular smear test can discover the sign of precancerous cell and treated the patient according to the result. However sometimes the detection errors can be occurred by smear thickness, cell overlapping or by un-wanted particles in the smear and cytotechnologists faulty diagnosis. Therefore the reason automatic cancer detection was developed. This was help to increase cancer cell mindfulness, diagnosis accuracy with low cost. This detection process consists of some techniques of the image preprocessing that is segmentation and effective texture feature extraction with SVM classification. Then the Final Classification Results of this proposed technique was compared to the previous classification techniques of KNN and ANN and the result would be very useful to cytotechnologists for their further analysis.

Keywords


Cancer, Cervical Cancer, Classification.