Mammogram Images Thresholding for Breast Cancer Detection Using Different Thresholding Methods

Moumena Al-Bayati, Ali El-Zaart

Department of Mathematics and Computer Science, Beirut Arab University, Beirut, Lebanon.

DOI: 10.4236/abcr.2013.23013                

Abstract

The purpose of this study is to apply different thresholding in mammogram images, and then we will determine which technique is the best in thresholding (extraction) malignant and benign tumors from the rest breast tissues. The used technique is Otsu method, because it is one of the most effective methods for most real world views with regard to uniformity and shape measures. Also, we present all the thresholding methods that used the concept of between class variance. We found from the experimental results that all the used thresholding techniques work well in detection normal breast tissues. But in abnormal tissues (breast tumors), we found that only neighborhood valley emphasis method gave best detection of malignant tumors. Also, the results demonstrate that variance and intensity contrast technique is the best in extraction the micro calcifications which represent the first signs of breast cancer.

Keywords

Breast Cancer; Mammogram; Segmentation; Threshold; Otsu Method

Conflicts of Interest

The authors declare no conflicts of interest.

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