Mammogram Classification Using Discrete Wavelet Transform Features and a Novel Vector Quantization Technique for Breast Cancer Detection

Journal Title: Current Journal of Applied Science and Technology - Year 2017, Vol 19, Issue 1

Abstract

In this paper, a digital mammogram classification system is presented. The proposed system uses the Discrete Wavelet Transform (DWT) to obtain features from the input mammogram image. The proposed system suggests a new algorithm for generating the codebook used by the vector quantization (VQ) algorithm to classify the input mammogram (malignant, benign, or normal). The obtained results on the DDSM database indicate the significant performance and superiority of the proposed method in comparison with the state of the art approaches. Simulation results show that the proposed system achieves a high accuracy and sensitivity.

Authors and Affiliations

Ahmad M. Sarhan, Radaan A. Al-Dosari

Keywords

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  • EP ID EP318468
  • DOI 10.9734/BJAST/2017/30420
  • Views 101
  • Downloads 0

How To Cite

Ahmad M. Sarhan, Radaan A. Al-Dosari (2017). Mammogram Classification Using Discrete Wavelet Transform Features and a Novel Vector Quantization Technique for Breast Cancer Detection. Current Journal of Applied Science and Technology, 19(1), 1-14. https://europub.co.uk./articles/-A-318468