STATISTICAL DETECTION OF BREAST CANCER BY MAMMOGRAM IMAGE

  • Rajini gk VIT University
  • Shaik Naseera Associate Professor, School of Computing Science and Engineering, VIT University, Vellore
  • Saravanan M VIT university

Abstract

Objective: To create awareness about the breast cancer which has become one of the most common diseases among women that leads to death if not recognized at early stage.

Methods: The technique of acquiring breast image is called mammography and is a diagnostic and screening tool to detect cancer. A cascade algorithm based on these statistical parameters is implemented on these mammogram images to segregate normal, benign, and malignant diseases.

Results: Statistical features - such as mean, median, standard deviation, perimeter, and skewness - were extracted from mammogram images to describe their intensity and nature of distribution using ImageJ.

Conclusion: A noninvasive technique which includes statistical features to determine and classify normal, benign, and malignant images are identified.

Keywords: Breast cancer, Benign, Malignant, Mammogram image, ImageJ.

References

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How to Cite
gk, R., S. Naseera, and S. M. “STATISTICAL DETECTION OF BREAST CANCER BY MAMMOGRAM IMAGE”. Asian Journal of Pharmaceutical and Clinical Research, Vol. 10, no. 1, Jan. 2017, pp. 227-9, doi:10.22159/ajpcr.2017.v10i1.15003.
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Original Article(s)