An Efficient Automatic Mass Classification Method In Digitized Mammograms Using Artificial Neural Network - Computer Science > Computer Vision and Pattern RecognitionReportar como inadecuado




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Abstract: In this paper we present an efficient computer aided mass classificationmethod in digitized mammograms using Artificial Neural Network ANN, whichperforms benign-malignant classification on region of interest ROI thatcontains mass. One of the major mammographic characteristics for massclassification is texture. ANN exploits this important factor to classify themass into benign or malignant. The statistical textural features used incharacterizing the masses are mean, standard deviation, entropy, skewness,kurtosis and uniformity. The main aim of the method is to increase theeffectiveness and efficiency of the classification process in an objectivemanner to reduce the numbers of false-positive of malignancies. Three layersartificial neural network ANN with seven features was proposed forclassifying the marked regions into benign and malignant and 90.91% sensitivityand 83.87% specificity is achieved that is very much promising compare to theradiologist-s sensitivity 75%.



Autor: Mohammed J. Islam, Majid Ahmadi, Maher A. Sid-Ahmed University of Windsor, Canada

Fuente: https://arxiv.org/







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