Fourier Transform Based Early Detection of Breast Cancer by Mammogram Image Processing

Authors

  • Mohammed Tarique Ajman University of Science and Technology P.O. Box 2202 Fujairah, United Arab Emirates
  • Fatmah ElZahra Department of Electrical Engineering, Ajman University of Science and Technology, Fujairah, United Arab
  • Ameena Hateem Department of Electrical Engineering, Ajman University of Science and Technology, Fujairah, United Arab
  • Mussab Mohammad Department of Electrical Engineering, Ajman University of Science and Technology, Fujairah, United Arab

DOI:

https://doi.org/10.14738/jbemi.24.1308

Keywords:

Breast cancer, calcification, image enhancement, image segmentation, edge detection, Fourier Transform

Abstract

Breast cancer is very common among the World’s women population. Early detection of breast cancer can save life. Mammography based diagnosis is considered as the most effective to detect breast cancer. But, mammogram images often lead to misdiagnosis due to their low contrast nature. Recent studies show that mammography based diagnosis fails to detect cancerous lumps in the breast in ten out of one hundred patients. In this paper we address this issue. We propose a computer aided breast cancer detection technique in this paper. In the proposed method mammogram images are enhanced and segmented to locate the malignant lumps in the women’s breast. The segmented image is then compared with a template image in order to determine the stage of breast cancer. Some statistical characteristics have also been presented in this paper to identify the malignant lumps from the benign ones.   

Author Biography

Mohammed Tarique, Ajman University of Science and Technology P.O. Box 2202 Fujairah, United Arab Emirates

Dr. Mohammed Tarique

Assistant Professor

Department of Electrical Engineering 

References

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Published

2015-09-02

How to Cite

Tarique, M., ElZahra, F., Hateem, A., & Mohammad, M. (2015). Fourier Transform Based Early Detection of Breast Cancer by Mammogram Image Processing. British Journal of Healthcare and Medical Research, 2(4), 17. https://doi.org/10.14738/jbemi.24.1308