Pap Smear Images Classification for Early Detection of Cervical Cancer

In this presents the analyses of the Pap smear cervical cell images for cervical screening and detection. Initially preprocessed the cell images to remove unwanted noises, Followed by extraction of the cell from the background to obtain the cytoplasm and nucleus of the cell which is the region of in...

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Bibliographic Details
Published in:International journal of computer applications 2015-01, Vol.118 (7), p.10-16
Main Authors: Mbaga, Ayubu Hassan, Zhijun, Pei
Format: Article
Language:English
Subjects:
Algorithms
Background noise
Cervical cancer
Feature extraction
Image classification
Image detection
Screening
Smear
Support vector machines
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Summary:In this presents the analyses of the Pap smear cervical cell images for cervical screening and detection. Initially preprocessed the cell images to remove unwanted noises, Followed by extraction of the cell from the background to obtain the cytoplasm and nucleus of the cell which is the region of interest. It is the only parts of the cell which can be used to differentiate normal cell from abnormal one. 20 salient features were extracted for training of support vector machine. SVM-RFE is used for features selection; the RFE algorithm removes unimportant features based on backward sequential selection by iteratively deleting one feature at a time, resulting in suboptimal combination of r(r
ISSN:0975-8887
0975-8887
DOI:10.5120/20756-3159