Mammography Images Segmentation Based on Fuzzy Set and Thresholding


  • Ali Mohammed Salih Department of Physics, College of Science, Mustansiriyah University
  • Mohammed Y. Kamil Department of Physics, College of Science, Mustansiriyah University



Mammography, Segmentation, Fuzzy logic, Mass detection, Thresholding


Breast cancer is the most widespread cancer that influences ladies about the world. Early recognition of breast tumor is a standout amongst the hugest variables influencing the probability of recuperation from the illness. Hence, mammography remains the most precise and best device for distinguishing breast malignancy. This paper presents a method for segment the boundary of breast masses regions in mammograms via a proposed algorithm based on fuzzy set techniques. Firstly, it was used data set (mini-MIAS) for evaluate algorithm. it was preprocessing the data set to remove noise and propose a fuzzy set by using fuzzy inference system by generated two input parameters (employs image gradient), then used thresholding filter. Then it was evaluated this proposed method, qualitative and quantitative results were obtained to demonstrate the efficiency of this method and confirm the possibility of its use in improving the diagnosis.


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How to Cite

A. M. Salih and M. Y. Kamil, “Mammography Images Segmentation Based on Fuzzy Set and Thresholding”, Al-Mustansiriyah Journal of Science, vol. 29, no. 3, pp. 168–175, Mar. 2019.