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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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Published in: | International journal of computer applications 2015-01, Vol.118 (7), p.10-16 |
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container_title | International journal of computer applications |
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creator | Mbaga, Ayubu Hassan Zhijun, Pei |
description | 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 |
doi_str_mv | 10.5120/20756-3159 |
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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. 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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. 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subjects | Algorithms Background noise Cervical cancer Feature extraction Image classification Image detection Screening Smear Support vector machines |
title | Pap Smear Images Classification for Early Detection of Cervical Cancer |
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