Deep Learning based Computer Aided Diagnosis System for Breast Mammograms

M. Arfan

Published 2017 in International Journal of Advanced Computer Science and Applications

ABSTRACT

In this paper, a framework has been presented by using a combination of deep Convolutional Neural Network (CNN) with Support Vector Machine (SVM). Proposed method first perform preprocessing to resize the image so that it can be suitable for CNN and perform enhancement quality of the images can be enhanced. Deep Convolutional Neural Network (CNN) has been used for features extraction and classification with Support Vector Machine (SVM). Standard dataset MIAS and DDMS has been employed for testing the proposed framework by generating new images from these datasets by the process of augmentation. Different performance measures like Accuracy, Sensitivity, Specificity and area under the curve (AUC) has been employed as a quantitative measure and compared with state of the art existing methods. Results shows that proposed framework has attained accuracy 93.35% and 93% sensitivity.

PUBLICATION RECORD

  • Publication year

    2017

  • Venue

    International Journal of Advanced Computer Science and Applications

  • Publication date

    Unknown publication date

  • Fields of study

    Medicine, Computer Science

  • Identifiers
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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REFERENCES

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