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The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

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Research Article | Open Access |

Abnormalities Detection in Digital Mammography Using Template Matching

Author 1: Ahmed M. Farrag
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 7, No. 2 · Published 2016

DOI: https://doi.org/10.14569/IJACSA.2016.070271

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Abstract

Breast cancer affects 1 in 8 women in the United States. Early detection and diagnosis is key to recovery. Computer-Aided Detection (CAD) of breast cancer helps decrease morbidity and mortality rates. In this study we apply Template Matching as a method for breast cancer detection to a novel data set comprised of mammograms annotated according to ground truth. Performance is evaluated in terms of Area Under the Receiver Operator Characteristic Curve (Area Under ROC) and Free-response ROC.

Keywords

Classification Detection Image Processing Dig-ital Mammography Breast Cancer Computer Aided Detection (CAD) Template Matching.

How to Cite this Article

Farrag, A. M. (2016). Abnormalities Detection in Digital Mammography Using Template Matching. International Journal of Advanced Computer Science and Applications, 7(2). https://doi.org/10.14569/IJACSA.2016.070271

Farrag, Ahmed M.. "Abnormalities Detection in Digital Mammography Using Template Matching." International Journal of Advanced Computer Science and Applications, vol. 7, no. 2, 2016, https://doi.org/10.14569/IJACSA.2016.070271.

@article{Farrag2016,
  title     = {Abnormalities Detection in Digital Mammography Using Template Matching},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {7},
  number    = {2},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {Ahmed M. Farrag},
  doi       = {10.14569/IJACSA.2016.070271},
  url       = {https://doi.org/10.14569/IJACSA.2016.070271}
}

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