Performance Evaluation of Optimized Artificial Neural Network Classifier for Mammography

  • Authors

    • Amit Sehgal
    • Satish Saini
    • Ritu Vijay
    2018-12-13
    https://doi.org/10.14419/ijet.v7i4.39.24108
  • Mammogram, Computer Aided Diagnosis, Artificial Neural Network

  • Abstract

    This paper works on the detection of the breast cancer at initial stage, by utilizing the mammogram images. The contrast of the mammogram image has been enhanced by pre-processing using histogram equalization. The extracted grey level co-occurrence matrix (GLCM) features have been reduced to the significant subset of features. Then, an ANN classifier has been used to classify the image as malignant or benign. The improvement in sensitivity, specificity, accuracy and f-measure signifies effectiveness of the work.

     

  • References

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  • How to Cite

    Sehgal, A., Saini, S., & Vijay, R. (2018). Performance Evaluation of Optimized Artificial Neural Network Classifier for Mammography. International Journal of Engineering & Technology, 7(4.39), 396-400. https://doi.org/10.14419/ijet.v7i4.39.24108

    Received date: 2018-12-16

    Accepted date: 2018-12-16

    Published date: 2018-12-13