Abstract: Breast cancer is a disease that arises due to the growth of breast tissue cells that are not normal. The detection of breast cancer malignancy level / stage relies heavily on the results of the analysis of the doctor. To assist the analysis, this research aims to develop a software that can determine the stage of breast cancer based on the size of the cancerous tissue. Steps of the research consist of mammogram image acquisition, determining the ROI (Region of Interest), using Region growing segmentation method, measuring the area of suspected cancer, and determine the stage classification of the area on the mammogram image by using Sample K-Means Clustering method. Based on 33 malignant (abnormal) mammogram sample images taken from the mini mammography database of MIAS, the proposed method can detect stage of breast cancer is in malignant group.

Karmilasari , Suryarini Widodo, Matrissya Hermita, Nur Putri Agustiyani, Yuhilza Hanum and Lussiana ETP, “Sample K-Means Clustering Method for Determining the Stage of Breast Cancer Malignancy Based on Cancer Size on Mammogram Image Basis” International Journal of Advanced Computer Science and Applications(IJACSA), 5(3), 2014. http://dx.doi.org/10.14569/IJACSA.2014.050312

@article{2014,
title = {Sample K-Means Clustering Method for Determining the Stage of Breast Cancer Malignancy Based on Cancer Size on Mammogram Image Basis},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2014.050312},
url = {http://dx.doi.org/10.14569/IJACSA.2014.050312},
year = {2014},
publisher = {The Science and Information Organization},
volume = {5},
number = {3},
author = {Karmilasari and Suryarini Widodo and Matrissya Hermita and Nur Putri Agustiyani and Yuhilza Hanum and Lussiana ETP}
}