Breast Cancer Detection in Digital Mammograms using Histogram Bins based Otsu Thresholding - Shanmugavadivu, P; Barveen, A. Thilshat; Kumar, Ashish (International Journal of Computer Sciences and Engineering, 2025)
Breast cancer is reported as the second most dangerous diseases in the world. Early detection of breast cancer is recorded to reduce the mortality rate by 30 to 60 percent. Digital mammography is a widely accepted as a non-invasive modality for the early detection of breast cancer, based on the abnormalities in the form of lesions, tumours and micro calcifications. The computer-based breast cancer screening involves segmentation of the abnormalities which are characterized by abrupt change in the pixel intensity, against the neighbourhood pixels. This paper presents a computationally simple and efficient enhancement technique that uses the principle of Otsu thresholding. The thresholds value for segmentation is chosen from the histogram bins of the input mammogram. The insignificant segmented partitions are discarded using morphological operations. The proposed method based on Histogram Bins based Otsu Thresholding (HBOT) is proved to segment the suspicious region accurately, as evidenced in the visual perception