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British Journal of Applied Science & Technology

British Journal of Applied Science & Technology, ISSN: 2231-0843,Vol.: 19, Issue.: 1


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


Ahmad M. Sarhan1* and Radaan A. Al-Dosari2

1Department of Computer Engineering, College of Computers and Information Technology, Taif University, Taif, Saudi Arabia.

2Saudi Electricity Company, Riyadh, Saudi Arabia.


Article Information
(1) Vitaly Kober, Department of Computer Science, CICESE, Mexico.
(1) Giovanni Lucca França da Silva, Universidade Federal do Maranhão, Brazil.
(2) Heydy Castillejos Fenández, National Polytechnic Institute, Mexico.
(3) Valliappan Raman, Swinburne University of Technology, Malaysia.
Complete Peer review History: http://www.sciencedomain.org/review-history/17858




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.


Keywords :

Medical images; breast cancer; discrete wavelet transform (DWT); vector quantization (VQ); mammogram.


Full Article - PDF    Page 1-14    Article Metrics


DOI : 10.9734/BJAST/2017/30420

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