文章基本信息

标题：Improvement of Multi Layer Perceptron Classification on Cervical Pap smear data with Feature Extraction
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作者：K. Hemalatha ; Dr. K. Usha Rani
期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2016
卷号：5
期号：12
页码：20419
DOI：10.15680/IJIRSET.2016.0512024
出版社：S&S Publications
摘要：Artificial Neural Network (ANN) is an effective technique of Soft Computing can model Computer-Aided Diagnosis (CAD) system efficiently. CAD system is an essential for the prediction of Malignancy in CervicalCancer. Cervical Cancer can be cured if it is diagnosed in early stages. Hence, for the effective screening of cancerlesions in the Cervical cell images which are captured using Pap smear test the successful ANN structure Multi LayerPerceptron (MLP) is used in this study. MLP network is trained with Cervical Pap Smear images database withoriginal features and then only with extracted features. Classification performance of MLP in the two cases iscalculated and analyzed with the help of network measures such as Classification Accuracy, Recall, Precision, MeanSquared Error (MSE) and Time.
关键词：Artificial Neural Network; Computer-Aided Diagnosis; Multi Layer Perceptron; Cervical Pap smear;image; Classification.