Improvement of Multi Layer Perceptron Classification on Cervical Pap smear data with Feature Extraction
نویسندگان
چکیده
Artificial Neural Network (ANN) is an effective technique of Soft Computing can model ComputerAided Diagnosis (CAD) system efficiently. CAD system is an essential for the prediction of Malignancy in Cervical Cancer. Cervical Cancer can be cured if it is diagnosed in early stages. Hence, for the effective screening of cancer lesions in the Cervical cell images which are captured using Pap smear test the successful ANN structure Multi Layer Perceptron (MLP) is used in this study. MLP network is trained with Cervical Pap Smear images database with original features and then only with extracted features. Classification performance of MLP in the two cases is calculated and analyzed with the help of network measures such as Classification Accuracy, Recall, Precision, Mean Squared Error (MSE) and Time.
منابع مشابه
Pap Smear Screening Test and It’s Applications in Cervical Cancer Detection and Classification
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